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The Emperor's New Drugs: Exploding the Antidepressant Myth (Paperback)
Title Page
Dedication
Epigraph
Brand Names
Acknowledgements
Preface
Chapter 1 - Listening to Prozac,
but Hearing Placebo
ARE ALL DRUGS CREATED EQUAL?
DOUBLE-BLIND OR DOUBLE-TALK
ANTIDEPRESSANTS AS ACTIVE PLACEBOS
Chapter 2 - The ‘Dirty Little
Secret’
THE VANISHING DRUG EFFECT
DEPRESSION SEVERITY AND
ANTIDEPRESSANT EFFICACY
A LITTLE GOES A LONG WAY
SECRETS AND REVELATIONS
WHY WERE THE DRUGS APPROVED?
VOODOO SCIENCE
THE ASSAY SASHAY
Chapter 3 - Countering the Critics
‘ANTIDEPRESSANTS WORK IN CLINICAL
PRACTICE’
CLINICAL PRACTICE VERSUS CLINICAL
TRIALS: THE STAR*D TRIAL
CLINICAL TRIALS ARE FLAWED
SUBSEQUENT TRIALS SHOW DIFFERENT
RESULTS
OIL AND WATER OR GUNS AND KNIVES?
Chapter 4 - The Myth of the
Chemical Imbalance
HOW THE BRAIN WORKS
INVENTION OF THE
CHEMICAL-IMBALANCE THEORY
THE EMPIRICAL BASIS OF THE
CHEMICAL-IMBALANCE THEORY
DEPRESSION, DISEASE AND THE BRAIN
Chapter 5 - The Placebo Effect and
the Power of Belief
THE DISCOVERY OF THE PLACEBO
EFFECT
THE POWER OF PLACEBO
DEPRESSION AS A NOCEBO EFFECT
Chapter 6 - How Placebos Work
THE THERAPEUTIC RELATIONSHIP
FEELING GOOD
THE SPECIFICS OF ‘NON-SPECIFIC’
EFFECTS
HARNESSING THE PLACEBO EFFECT IN
CLINICAL PRACTICE
Chapter 7 - Beyond Antidepressants
WARNING: DO NOT DISCONTINUE
ANTIDEPRESSANTS WITHOUT CONSULTATION
PRESCRIBING PLACEBOS
PLACEBOS WITHOUT DECEPTION
PSYCHOTHERAPY: THE QUINTESSENTIAL
PLACEBO
ST JOHN’S WORT
PHYSICAL EXERCISE
PSYCHOTHERAPY WITHOUT
PSYCHOTHERAPISTS
SOCIAL CHANGE
Epilogue
Notes
Bibliography
Index
Copyright Page
Table of Contents
Title Page
Dedication
Epigraph
Brand Names
Acknowledgements
Preface
Chapter 1 - Listening to Prozac,
but Hearing Placebo
ARE ALL DRUGS CREATED EQUAL?
DOUBLE-BLIND OR DOUBLE-TALK
ANTIDEPRESSANTS AS ACTIVE PLACEBOS
Chapter 2 - The ‘Dirty Little
Secret’
THE VANISHING DRUG EFFECT
DEPRESSION SEVERITY AND
ANTIDEPRESSANT EFFICACY
A LITTLE GOES A LONG WAY
SECRETS AND REVELATIONS
WHY WERE THE DRUGS APPROVED?
VOODOO SCIENCE
THE ASSAY SASHAY
Chapter 3 - Countering the Critics
‘ANTIDEPRESSANTS WORK IN CLINICAL
PRACTICE’
CLINICAL PRACTICE VERSUS CLINICAL
TRIALS: THE STAR*D TRIAL
CLINICAL TRIALS ARE FLAWED
SUBSEQUENT TRIALS SHOW DIFFERENT
RESULTS
OIL AND WATER OR GUNS AND KNIVES?
Chapter 4 - The Myth of the
Chemical Imbalance
HOW THE BRAIN WORKS
INVENTION OF THE
CHEMICAL-IMBALANCE THEORY
THE EMPIRICAL BASIS OF THE
CHEMICAL-IMBALANCE THEORY
DEPRESSION, DISEASE AND THE BRAIN
Chapter 5 - The Placebo Effect and
the Power of Belief
THE DISCOVERY OF THE PLACEBO
EFFECT
THE POWER OF PLACEBO
DEPRESSION AS A NOCEBO EFFECT
Chapter 6 - How Placebos Work
THE THERAPEUTIC RELATIONSHIP
FEELING GOOD
THE SPECIFICS OF ‘NON-SPECIFIC’
EFFECTS
HARNESSING THE PLACEBO EFFECT IN
CLINICAL PRACTICE
Chapter 7 - Beyond Antidepressants
WARNING: DO NOT DISCONTINUE
ANTIDEPRESSANTS WITHOUT CONSULTATION
PRESCRIBING PLACEBOS
PLACEBOS WITHOUT DECEPTION
PSYCHOTHERAPY: THE QUINTESSENTIAL
PLACEBO
ST JOHN’S WORT
PHYSICAL EXERCISE
PSYCHOTHERAPY WITHOUT
PSYCHOTHERAPISTS
SOCIAL CHANGE
Epilogue
Notes
Bibliography
Index
Copyright Page
For Leo, Alice, and the
grandchildren yet to come
‘Brahms is the best
antidepressant.’
Peter Sproston, 2008
|
Generic |
American |
British |
|
Fluoxetine |
Prozac |
Prozac |
|
Paroxetine |
Paxil |
Seroxat |
|
Sertraline |
Zoloft |
Lustral |
|
Venlafaxine |
Effexor |
Effexor |
|
Nefazodone |
Serzone |
Dutonin |
|
Citalopram |
Celexa |
Cipramil |
The information in this book is not a substitute for professional
advice on specific emotional issues. Please consult your GP before changing,
stopping or starting any medical treatment, specifically antidepressant
medication. So far as the author is aware the information given is correct and
up to date as at 3 September 2009. The author and publishers disclaim, as far
as the law allows, any liability arising directly or indirectly from the use,
or misuse, of the information contained in this book.
Special thanks are due
to Giuliana Mazzoni, David Bassine, Alan Scoboria and Steven Jay Lynn, who
carefully read and provided very helpful feedback on a number of chapters.
Giuliana, in particular, helped me set the tone of the early chapters. I also
thank Joanna Moncrieff, who gently critiqued a rather poorly done first draft
of Chapter 4. I hope she likes this version better.
Dan Hind was my
first editor at Random House. He approached me with the idea of doing this book
after attending a debate in which I participated. His feedback at various
stages was exceptionally helpful, as was his confidence and encouragement. He
left Random House before the project was finished, but continued to help me
with it even after leaving. He was replaced as my editor by Kay Peddle, who was
left in the lurch and whom I thank immensely for her substantial help on the
final leg of the journey. Mandy Greenfield has been an eagle-eyed copy-editor,
and I thank her for catching my oversights.
Thanks are also due
to numerous colleagues and friends who provided helpful comments and
information beyond that which I had found in books and journal articles. These
include David Antonuccio, David Burns, David Goldberg, David Healy, Steven
Hollon, Ted Kaptchuck, Peter Lewinsohn, John and Madge Manfred, Helen Mayberg,
Lee Park, Forrest Scogin, Harriet Vickery, Tor Wager and Nelda Wray.
Finally, I thank
the wonderful scientists with whom I have collaborated on the research leading
to this book: Guy Sapirstein, Thomas Moore, Alan Scoboria, Blair Johnson, Brett
Deacon, Tania Huedo-Medina, Joanna Moncrieff, Corrado Barbui, Andrea Cipriani,
Sarah Nicholls and David Antonuccio. Research is a team effort, and these
colleagues have made wonderful teams.
Like most people, I
used to think that antidepressants worked. As a clinical psychologist, I
referred depressed psychotherapy clients to psychiatric colleagues for the
prescription of medication, believing that it might help. Sometimes the
antidepressant seemed to work; sometimes it did not. When it did work, I
assumed it was the active ingredient in the antidepressant that was helping my
clients cope with their psychological condition.
According to drug
companies, more than 80 per cent of depressed patients can be treated
successfully by antidepressants. Claims like this made these medications one of
the most widely prescribed class of prescription drugs in the world, with
global sales that make it a $19-billion-a-year industry.1 Newspaper and magazine articles
heralded antidepressants as miracle drugs that had changed the lives of
millions of people. Depression, we were told, is an illness - a disease of the
brain that can be cured by medication. I was not so sure that depression was
really an illness, but I did believe that the drugs worked and that they could
be a helpful adjunct to psychotherapy for very severely depressed clients. That
is why I referred these clients to psychiatrists who could prescribe
antidepressants that the clients could take while continuing in psychotherapy
to work on the psychological issues that had made them depressed.
But was it really
the drug they were taking that made my clients feel better? Perhaps I should
have suspected that the improvement they reported might not have been a drug
effect. People obtain considerable benefits from many medications, but they
also can experience symptom improvement just by knowing they are being treated.
This is called the placebo effect. As a researcher at the University of
Connecticut, I had been studying placebo effects for many years. I was well
aware of the power of belief to alleviate depression, and I understood that
this was an important part of any treatment, be it psychological or
pharmacological. But I also believed that antidepressant drugs added something
substantial over and beyond the placebo effect. As I wrote in my first book, ‘comparisons
of anti-depressive medication with placebo pills indicate that the former has a
greater effect . . . the existing data suggest a pharmacologically specific
effect of imipramine on depression’. As a researcher, I trusted the data as it
had been presented in the published literature. I believed that antidepressants
like imipramine were highly effective drugs, and I referred to this as ‘the
established superiority of imipramine over placebo treatment’.2
When I began the
research that I describe in this book, I was not particularly interested in
investigating the effects of antidepressants. But I was definitely interested
in investigating placebo effects wherever I could find them, and it seemed to
me that depression was a perfect place to look. Why did I expect to find a
large placebo effect in the treatment of depression? If you ask depressed
people to tell you what the most depressing thing in their lives is, many
answer that it is their depression. Clinical depression is a debilitating
condition. People with severe depression feel unbearably sad and anxious, at
times to the point of considering suicide as a way to relieve the burden. They
may be racked with feelings of worthlessness and guilt. Many suffer from
insomnia, whereas others sleep too much and find it difficult to get out of bed
in the morning. Some have difficulty concentrating and have lost interest in
all of the activities that previously brought pleasure and meaning into their
lives. Worst of all, they feel hopeless about ever recovering from this
terrible state, and this sense of hopelessness may lead them to feel that life
is not worth living. In short, depression is depressing. John Teasdale, a
leading researcher on depression at Oxford and Cambridge universities, labelled
this phenomenon ‘depression about depression’ and claimed that effective
treatments for depression work - at least in part - by altering the sense of
hopelessness that comes from being depressed about one’s own depression.3
Whereas
hopelessness is a central feature of depression, hope lies at the core of the
placebo effect. Placebos instil hope in patients by promising them relief from
their distress. Genuine medical treatments also instil hope, and this is the
placebo component of their effectiveness. When the promise of relief instils
hope, it counters a fundamental attribute of depression. Indeed, it is
difficult to imagine any treatment successfully treating depression without
reducing the sense of hopelessness that depressed people feel. Conversely, any
treatment that reduces hopelessness must also assuage depression. So a
convincing placebo ought to relieve depression.
It was with that in
mind that one of my postgraduate students, Guy Sapirstein, and I set out to
investigate the placebo effect in depression - an investigation that I describe
in the first chapter of this book, and that produced the first of a series of
surprises that transformed my views about antidepressants and their role in the
treatment of depression.4 In this book I invite you to share
this journey in which I moved from acceptance to dissent, and finally to a
thorough rejection of the conventional view of antidepressants.
The drug companies
claimed - and still maintain - that the effectiveness of antidepressants has
been proven in published clinical trials showing that the drugs are
substantially better than placebos (dummy pills with no active ingredients at
all). But the data that Sapirstein and I examined told a very different story.
Although many depressed patients improve when given medication, so do many who
are given a placebo, and the difference between the drug response and the
placebo response is not all that great. What the published studies really
indicate is that most of the improvement shown by depressed people when they
take antidepressants is due to the placebo effect.
Our finding that
most of the effects of antidepressants could be explained as a placebo effect
was only the first of a number of surprises that changed my views about
antidepressants. Following up on this research, I learned that the published
clinical trials we had analysed were not the only studies assessing the effectiveness
of antidepressants. I discovered that approximately 40 per cent of the clinical
trials conducted had been withheld from publication by the drug companies that
had sponsored them. By and large, these were studies that had failed to show a
significant benefit from taking the actual drug. When we analysed all of the
data - those that had been published and those that had been suppressed - my
colleagues and I were led to the inescapable conclusion that antidepressants
are little more than active placebos, drugs with very little specific
therapeutic benefit, but with serious side effects. I describe these analyses -
and the reaction to them - in Chapters 3 and 4.
How can this be?
Before a new drug is put on the market, it is subjected to rigorous testing. The
drug companies sponsor expensive clinical trials, in which some patients are
given medication and others are given placebos. The drug is considered
effective only if patients given the real drug improve significantly more than
patients given the placebos. Reports of these trials are then sent out to
medical journals, where they are subjected to rigorous peer review before they
are published. They are also sent to regulatory agencies, like the Food and
Drug Administration (FDA) in the US, the Medicines and Healthcare products
Regulatory Agency (MHRA) in the UK and the European Medicine Agency (EMEA) in
the EU. These regulatory agencies carefully review the data on safety and
effectiveness, before deciding whether to approve the drugs for marketing. So
there must be substantial evidence backing the effectiveness of any medication
that has reached the market.
And yet I remain
convinced that antidepressant drugs are not effective treatments and that the
idea of depression as a chemical imbalance in the brain is a myth. When I began
to write this book, my claim was more modest. I believed that the clinical
effectiveness of antidepressants had not been proven for most of the millions
of patients to whom they are prescribed, but I also acknowledged that they might
be beneficial to at least a subset of depressed patients. During the process of
putting all of the data together, those that I had analysed over the years and
newer data that have just recently seen the light of day, I realized that the
situation was even worse than I thought. The belief that antidepressants can
cure depression chemically is simply wrong.
In this book I will
share with you the process by which I came to this conclusion and the
scientific evidence on which it is based. This includes evidence that was known
to the pharmaceutical companies and to regulatory agencies, but that was
intentionally withheld from prescribing physicians, their patients and even
from the National Institute for Health and Clinical Excellence (NICE) when it
was drawing up treatment guidelines for the National Health Service (NHS) in
the UK.
My colleagues and I
obtained some of these hidden data by using the Freedom of Information Act in
the US. We analysed the data and submitted the results for peer review to
medical and psychological journals, where they were then published.5 Our analyses have become the focus
of a national and international debate, in which many doctors have changed
their prescribing habits and others have reacted with anger and incredulity. My
intention in this book is to present the data in a plain and straightforward
way, so that you will be able to decide for yourself whether my conclusions
about antidepressants are justified.
The conventional
view of depression is that it is caused by a chemical imbalance in the brain.
The basis for this idea was the belief that antidepressant drugs were effective
treatments. Our analyses showing that most - if not all - of the effects of
these medications are really placebo effects challenges this widespread view of
depression. In Chapter 4 I examine the chemical-imbalance theory. You may be
surprised to learn that it is actually a rather controversial theory and that
there is not much scientific evidence to support it. While writing this chapter
I came to an even stronger conclusion. It is not just that there is not much
supportive evidence; rather, there is a ton of data indicating that the
chemical-imbalance theory is simply wrong.
The chemical effect
of antidepressant drugs may be small or even non-existent, but these
medications do produce a powerful placebo effect. In Chapters 5 and 6 I examine
the placebo effect itself. I look at the myriad of effects that placebos have
been shown to have and explore the theories of how these effects are produced.
I explain how placebos are able to produce substantial relief from depression,
almost as much as that produced by medication, and the implications that this
has for the treatment of depression.
Finally, in Chapter
7, I describe some of the alternatives to medication for the treatment of
depression and assess the evidence for their effectiveness. One of my aims is
to provide essential scientifically grounded information for making informed
choices between the various treatment options that are available.
Much of what I
write in this book will seem controversial, but it is all thoroughly grounded
on scientific evidence - evidence that I describe in detail in this book.
Furthermore, as controversial as my conclusions seem, there has been a growing
acceptance of them. NICE has acknowledged the failure of antidepressant
treatment to provide clinically meaningful benefits to most depressed patients;
the UK government has instituted plans for providing alternative treatments; and
neuroscientists have noted the inability of the chemical-imbalance theory to
explain depression.6 We seem to be on
the cusp of a revolution in the way we understand and treat depression.
Learning the facts
behind the myths about antidepressants has been, for me, a journey of
discovery. It was a journey filled with shocks and surprises - surprises about
how drugs are tested and how they are approved, what doctors are told and what
is kept hidden from them, what regulatory agencies know and what they don’t
want you to know, and the myth of depression as a brain disease. I would like
to share that journey with you. Perhaps you will find it as surprising and
shocking as I did. It is my hope that making this information public will
foster changes in the way new drugs are tested and approved in the future, in
the public availability of the data and in the treatment of depression.
Listening to Prozac,
but Hearing Placebo
In 1995 Guy Sapirstein
and I set out to assess the placebo effect in the treatment of depression.
Instead of doing a brand-new study, we decided to pool the results of previous
studies in which placebos had been used to treat depression and analyse them
together. What we did is called a meta-analysis, and it is a common technique
for making sense of the data when a large number of studies have been done to
answer a particular question. It was once considered somewhat controversial,
but meta-analyses are now common features in all of the leading medical
journals. Indeed, it is hard to see how one could interpret the results of
large numbers of studies without the aid of a meta-analysis.
In doing our
meta-analysis, it was not enough to find studies in which depressed patients
had been given placebos. We also needed to find studies in which depression had
been tracked in patients who were not given any treatment at all. This was to
make sure that any effect we found was really due to the administration of the
placebo. To better understand the reason for this, imagine that you are
investigating a new remedy for colds. If the patients are given the new
medicine, they get better. If they are given placebos, they also get better.
Seeing these data, you might be tempted to think that the improvement was a
placebo effect. But people recover from colds even if you give them nothing at
all. So when the patients in our imaginary study took a dummy pill and their
colds got better, the improvement may have had nothing to do with the placebo
effect. It might simply have been due to the passage of time and the fact that
colds are shortlasting illnesses.
Spontaneous
improvement is not limited to colds. It can also happen when people are
depressed. Because people sometimes recover from bouts of depression with no treatment
at all, seeing that a person has become less depressed after taking a placebo
does not mean that the person has experienced a placebo effect. The improvement
could have been due to any of a number of other factors. For example, people
can get better because of positive changes in life circumstances, such as
finding a job after a period of unemployment or meeting a new romantic partner.
Improvement can also be facilitated by the loving support of friends and
family. Sometimes a good friend can function as a surrogate therapist. In fact,
a very influential book on psychotherapy bore the title Psychotherapy:
The Purchase of Friendship.1 The author did not claim that psychotherapy was
merely friendship, but the title does make the point that it can be very
therapeutic to have a friend who is empathic and knows how to listen.
The point is that
without comparing the effect of placebos against rates of spontaneous recovery,
it is impossible to assess the placebo effect. Just as we have to control for
the placebo effect to evaluate the effect of a drug, so too we have to control
for the passage of time when assessing the placebo effect. The drug effect is
the difference between what happens when people are given the active drug and
what happens when they are given the placebo. Analogously, the placebo effect
is the difference between what happens when people are given placebos and what
happens when they are not treated at all.
It is rare for a
study to focus on the placebo effect - or on the effect of the simple passage
of time, for that matter. So where were we to find our placebo data and
no-treatment data? We found our placebo data in clinical studies of
antidepressants, and our no-treatment data in clinical studies of
psychotherapy. It is common to have no-treatment or wait-list control groups in
studies of the effects of psychotherapy. These groups consist of patients who
are not given any treatment at all during the course of the study, although
they may be placed on a wait list and given treatment after the research is
concluded.
For the purpose of
our research, Sapirstein and I were not particularly interested in the effects
of the antidepressants or psychotherapy. What we were interested in was the
placebo effect. But since we had the treatment data to hand, we looked at them
as well. And, as it turned out, it was the comparison of drug and placebo that
proved to be the most interesting part of our study.
All told, we
analysed 38 clinical trials involving more than 3,000 depressed patients. We
looked at the average improvement during the course of the study in each of the
four types of groups: drug, placebo, psychotherapy and no-treatment. I am going
to use a graph here (Figure 1.1,
overleaf) to show what the data tell us. Although the text will have a couple
more such charts, I am going to keep them to a minimum. But this is one that I
think we need, to make the point clearly. What the graph shows is that there
was substantial improvement in both the drug and psychotherapy groups. People
got better when given either form of treatment, and the difference between the
two was not significant. People also got better when given placebos, and here
too the improvement was remarkably large, although not as great as the
improvement following drugs or psychotherapy. In contrast, the patients who had
not been given any treatment at all showed relatively little improvement.
The first thing to
notice in this graph is the difference in improvement between patients given
placebos and patients not given any treatment at all. This difference shows
that most of the improvement in the placebo groups was produced by the fact
that they had been given placebos. The reduction in depression that people
experienced was not just caused by the passage of time, the natural course of
depression or any of the other factors that might produce an improvement in
untreated patients. It was a placebo effect, and it was powerful.
Figure 1.1. Average improvement on drug, psychotherapy, placebo and no treatment.2
‘Improvement’ refers to the reduction of symptomson scales used to measure
depression. The numbers are called ‘effect sizes’. They are commonly used when
the results of different studies are pooled together. Typically, effect sizes
of 0.5 are consideredmoderate, whereas effect sizes of 0.8 are considered
large. So the graph shows that antidepressants, psychotherapy and placebos
produce large changes in the symptoms of depression, but there was only a
relatively small average improvement in people who were not given any treatment
at all.
One thing to learn
from these data is that doing nothing is not the best way to respond to
depression. People should not just wait to recover spontaneously from clinical
depression, nor should they be expected just to snap out of it. There may be
some improvement that is associated with the simple passage of time, but compared
to doing nothing at all, treatment - even if it is just placebo treatment -
provides substantial benefit.
Sapirstein and I
were not surprised to find that there was a powerful placebo effect in the
treatment of depression. Actually, we were quite pleased. That was our
hypothesis and our reason for doing the study. What did surprise us, however,
was how small the difference was between the response to the drug and the
response to the placebo. That difference is the drug effect. Although the drug
effect in the published clinical trials that we had analysed was statistically
significant, it was much smaller than we had anticipated. Much of the
therapeutic response to the drug was due to the placebo effect. The relatively
small size of the drug effect was the first of a series of surprises that the
anti-depressant data had in store for us.
One way to
understand the size of the drug effect is to think about it as only a part of
the improvement that patients experience when taking medication. Part of the improvement
might be spontaneous - that is, it might have occurred without any treatment at
all - and part may be a placebo effect. What is left over after you subtract
spontaneous improvement and the placebo effect is the drug effect. You can see
in Figure 1.1
that improvement in patients who had been given a placebo was about 75 per cent
of the response to the real medication. That means that only 25 per cent of the
benefit of antidepressant treatment was really due to the chemical effect of
the drug. It also means that 50 per cent of the improvement was a placebo
effect. In other words, the placebo effect was twice as large as the drug
effect.
The drug effect
seemed rather small to us, considering that these medications had been heralded
as a revolution in the treatment of depression - blockbuster drugs that have
been prescribed to hundreds of millions of patients, with annual sales
totalling billions of pounds.3 Sapirstein and I must have done something wrong in
either collecting or analysing the data. But what? We spent months trying to
figure it out.
ARE ALL DRUGS CREATED
EQUAL? DOUBLE-BLIND OR DOUBLE-TALK
One thing that occurred
to us, when considering how surprisingly small the drug effect was in the
clinical trials we had analysed, was that a number of different medications had
been assessed in those studies. Perhaps some of them were effective, whereas
others were not. If this were the case, we had underestimated the benefits of
effective drugs by lumping them together with ineffective medications. So
before we sent our paper out for review, we went back to the data and examined
the types of drugs that had been administered in each of the clinical trials in
our meta-analysis.
We found that some
of these trials had assessed tricyclic antidepressants, an older type of
medication that was the most commonly used antidepressant in the 1960s and
1970s. In other trials, the focus was on selective serotonin reuptake
inhibitors (SSRIs) like Prozac (fluoxetine), the first of the ‘new-generation’
drugs that replaced tricyclics as the top-selling type of antidepressant. And
there were other types of antidepressants investigated in these trials as well.
When we reanalysed the data, examining the drug effect and the placebo effect
for each type of medication separately, we found that the diversity of drugs
had not affected the outcome of our analysis. In fact, the data were remarkably
consistent - much more so than is usually the case when one analyses different
groups of data. Not only did all of these medications produce the same degree
of improvement in depression, but also, in each case, only 25 per cent of the
improvement was due to the effect of the drug. The rest could be explained by
the passage of time and the placebo effect.
The lack of
difference we found between one class of antidepressants and another is now a
rather frequent finding in antidepressant research.4 The newer antidepressants (SSRIs,
for example) are no more effective than the older medications. Their advantage
is that their side effects are less troubling, so that patients are more likely
to stay on them rather than discontinue treatment. Still, the consistency of
the size of the drug effect was surprising. It was not just that the
percentages were close; they were virtually identical. They ranged from 24 to
26 per cent. At the time I thought, ‘What a nice coincidence! It will look
great in a PowerPoint slide when I am invited to speak on this topic.’ But
since then I have been struck by similar instances in which the consistency of
the data is remarkable, and it is part of what has transformed me from a
doubter to a disbeliever. I will note similar consistencies as we encounter
them in this book.
The consistency of
the effects of different types of antidepressants meant that we had not
underestimated the antidepressant drug effect by lumping together the effects
of more effective and less effective drugs. But our re-examination of the data
in our metaanalysis held another surprise for us. Some of the medications we
had analysed were not antidepressants at all, even though they had been
evaluated for their effects on depression. One was a barbiturate - a depressant
that had been used as a sleeping aid, before being replaced by less dangerous
medications. Another was a benzodiazepine - a sedative that has largely
replaced the more dangerous barbiturates. Yet another was a synthetic thyroid
hormone that had been given to depressed patients who did not have a thyroid
disorder. Although none of these drugs are considered antidepressants, their
effects on depression were every bit as great as those of antidepressants and
significantly better than placebos. Joanna Moncrieff, a psychiatrist at
University College London, has since listed other drugs that have been shown to
be as effective as medications for depression.5 These include antipsychotic drugs, stimulants and
herbal remedies. Opiates are also better than placebos, but I have not seen
them compared to antidepressants.
If sedatives,
barbiturates, antipsychotic drugs, stimulants, opiates and thyroid medications
all outperform inert placebos in the treatment of depression, does this mean
that any active drug can function as an antidepressant? Apparently not. In
September 1998 the pharmaceutical company Merck announced the discovery of a
novel antidepressant with a completely different mode of action than other
medications for depression. This new drug, which they later marketed under the
trade name Emend for the prevention of nausea and vomiting due to chemotherapy,
seemed to show considerable promise as an antidepressant in early clinical
trials. Four months later the company announced its decision to pull the plug
on the drug as a treatment for depression. The reason? It could not find a
significant benefit for the active drug over placebos in subsequent clinical
trials. This was unfortunate for a number of reasons. One is that the
announcement caused a 5 per cent drop in the value of the company’s stock.
Another is that the drug had an important advantage over current
antidepressants - it produced substantially fewer side effects. The relative
lack of side effects had been one reason for the enthusiasm about Merck’s new
antidepressant. However, it may also have been the reason for its subsequent
failure in controlled clinical trials. It seems that easily noticeable side
effects are needed to show antidepressant benefit for an active drug compared
to a placebo.6
At first,
Sapirstein and I found the equivalence between antidepressants and other drugs
puzzling, to say the least. Why should drugs that are not antidepressants be as
effective as antidepressants in treating depression? To answer this question,
we asked another. What do all these diverse drugs have in common that they do
not share with inert placebos? What do SSRIs have in common with the older tricyclic
antidepressants, with other less common antidepressants, and even with
tranquillizers, depressants and thyroid medication? The only common factor that
we were able to note was that they all produce easily noticeable side effects -
the one thing that was lacking in Merck’s new treatment for depression.
Placebos can also produce side effects, but they do so to a much lesser extent
than active medication. Clinical trials show that whereas the therapeutic
benefits of antidepressants are relatively small when compared to placebos, the
difference in side effects is substantial.7
Why are side
effects important? Imagine that you have been recruited for a clinical trial of
an antidepressant medication. As part of the required informed-consent
procedure, you are told that you may be given a placebo instead of the active
medication, but because this is a double-blind trial, you will not be told
which you are getting until the study is over. You are told that it may take
weeks before the therapeutic effects of the drug are apparent, and also that
the drug has been reported to produce side effects in some patients.
Furthermore, as required by the informed-consent procedures that need to be
followed in clinical trials, you are also told exactly what those side effects
are (for example, a dry mouth, drowsiness, diarrhoea, nausea, forgetfulness)
and that these are most likely to occur soon after treatment has begun - before
the therapeutic effects are felt.8
Now if I were a
patient in one of these trials, I would wonder to which condition I had been
assigned. Had I been put in the active-drug group or in the placebo group? Hmm,
my mouth is getting dry, and I’m beginning to feel a little nauseous. Normally,
I might feel distressed by these symptoms, but I have been informed that these
are side effects of the active drug. So instead of feeling distressed, I am
elated. My dry mouth and nauseous stomach tell me that I have been given the
active drug, rather than the placebo. I’m starting to feel better already.
Figuring out
whether you have been given the drug or the placebo in a clinical trial is
referred to as ‘breaking blind’. Clinical trials are supposed to be
double-blind. This means that neither the patient nor the doctor is supposed to
know whether the patient has been given the active drug or the placebo. In
fact, these trials are not really double-blind. Many of the patients break
blind, and so do the physicians who are treating them. Both the patients and
their doctors come to realize which condition they are in, before being told at
the end of the trial. We know this from antidepressant studies in which
patients and doctors are asked to say whether they have been given drug or
placebo. If they were only guessing, they should be right about half the time,
but in fact they are much more accurate than that. In the largest study of this
type, 80 per cent of patients accurately identified whether they were on drug
or placebo, and in 87 per cent of the cases their doctors also guessed
correctly. With the number of patients assessed in this study, the odds of 80
per cent guessing correctly just by chance is less than one in a million. This
means that most patients and most doctors broke blind. For patients, this was
especially true if they were in the real drug condition: 89 per cent of
patients given the real antidepressants correctly figured out that they were in
the drug group. In contrast, only 59 per cent of patients in the placebo group
guessed correctly.9
ANTIDEPRESSANTS AS ACTIVE
PLACEBOS
The breaking of blind
by patients in clinical trials may be the key to understanding why all types of
different drugs in our metaanalysis, even those that were not antidepressants,
had the same effect on depression. When patients are kept blind, they do not
know whether they have been given the drug or the placebo. Hence, their
expectation of getting better is tempered by their knowledge that they might
have been given a placebo. But when they break blind, their expectations
change. If they know they have been given the active drug, rather than the
placebo, they become much more confident of improving. Conversely, if they
realize that they are in the placebo group, their expectancy of improvement
declines.
As we shall see in
Chapter 6, expectations of improvement are a central factor in the placebo
effect. People expect to get better when given a treatment, and in many
conditions that expectation can produce the improvement they expect as a sort
of self-fulfilling prophecy. In other words, patients who break blind in
clinical trials might improve more on the active drug than on the placebo,
simply because they know they are getting a real drug rather than a sugar pill.
If they believe they are on the active drug, they have a greater expectation of
improvement, and because of these enhanced expectations they actually do
improve more. On the other hand, if they realize they have been given a placebo,
they expect - and therefore experience - less improvement.
This is not just
speculation. It is backed by evidence. Some antidepressant trials are conducted
without placebo groups. These are called comparator trials, because they
compare one antidepressant to another. In comparator trials, all patients are
given an active drug, and they know that there is no chance at all of getting a
placebo. A group of researchers led by Joel Sneed at Columbia University in New
York compared the response of patients in comparator trials to that of patients
in placebo-controlled trials. The researchers found that patients in the
comparator trials were significantly more likely to improve. Specifically, 60
per cent of patients responded to antidepressants in the comparator trials, but
only 46 per cent were rated as improved in the placebo-controlled trials.10 This difference resulted from
patients knowing that they were definitely getting an active drug versus
knowing that they might be getting a placebo, as that was the only difference
between the two types of trials that were compared. Because it was produced by
what the patients believed about the drug, rather than by the drug itself, it
can be considered a placebo effect.
To summarize the
argument to this point, we found a relatively small difference between the
response to antidepressant drugs and the response to placebos. In other words,
the drug effect was rather small. We also found that the small but significant difference
between active drugs and placebos was not limited to antidepressants. Other
active drugs also reduced depression more than placebos did. The one thing that
all of these drugs had in common was that they produced side effects, and side
effects have been associated with figuring out whether one has been given an
active drug or a placebo in a clinical trial. Finally, we have seen that
knowing that one is getting an active drug boosts the effectiveness of the
drug, and knowing that one might have been given a placebo decreases its
effectiveness. Putting all of this together leads to the conclusion that the
relatively small difference between drugs and placebos might not be a real drug
effect at all. Instead, it might be an enhanced placebo effect, produced by the
fact that some patients have broken blind and have come to realize whether they
were given drug or placebo. If this is the case, then there is no real
antidepressant drug effect at all. Rather than comparing placebo to drug, we
have been comparing ‘regular’ placebos to ‘extra-strength’ placebos.
When Sapirstein and
I published our analysis, we could not prove that the difference between active
drug and placebo in antidepressant trials was due to an enhanced placebo
effect. Given the data that we had, this was only a hypothesis, but it was a
hypothesis based on substantial circumstantial evidence. Besides the data I
summarized in the last paragraph, there are two additional kinds of evidence
that support the enhanced placebo effect hypothesis. One of these is that there
is an exceptionally high correlation between improvement and the experience of
SSRI side effects.11 One might
expect to find a negative association between side effects and improvement.
Side effects of SSRIs include sexual dysfunction, insomnia, short-term weight
loss, long-term weight gain, diarrhoea, nausea, drowsiness, skin reactions,
nervousness, anorexia, dry mouth and sweating.12 One would think that experiences like this would
make people feel more depressed. Indeed, some of these side effects could also
be interpreted as symptoms of depression. But in fact the relationship is in
the opposite direction. The more side effects a person experiences when taking
Prozac, the more he or she improves on the drug. I can think of only one reason
why insomnia, diarrhoea and nausea might be linked to improvement, and that is
that they lead patients to conclude that they have been given the active drug,
rather than the placebo.
The association
between side effects and improvement is so strong as to be almost perfect.
Correlations can range from zero to one. The correlation between side effects
and improvement when taking Prozac is .96, which is just about as high as a
correlation can get.13 It is
exceptionally rare to find correlations this high in research. My colleague
John Kihlstrom at the University of California at Berkeley calls data like this
‘Faustian’ - by which he means that researchers would sell their souls to
obtain them.14 A high
correlation between two things does not mean that one has caused the other. Hat
sizes and shoe sizes are highly correlated, but big feet do not cause swollen
heads. Similarly, the correlation between side effects and improvement does not
prove that side effects produce the improvement. Still, it fits the enhanced
placebo hypothesis perfectly, and it is hard to think of another explanation
for it.
While writing this
book, I was invited to speak about my antidepressant research by Corrado Barbui
and Andrea Cipriani, psychiatrists at the University of Verona who had
conducted studies with results similar to mine, but who still believed that
antidepressants had a chemical effect.15 After my talk, we argued a bit
about my contention that the small differences between antidepressant drugs and
placebos might be due to the presence of side effects and the consequent
breaking of blind among patients who had been given the real drug rather than
the placebo. ‘If you are right about that,’ said these two gentlemen of Verona,
‘then controlling for side effects statistically ought to eliminate the drug
effect completely.’ I agreed, and we decided to test this hypothesis using
their collection of all the published and unpublished clinical trials that
GlaxoSmithKline had conducted on their SSRI, Seroxat. The results of that
analysis showed that once you adjust for drug-placebo differences in side
effects, differences in rates of improvement are no longer statistically
significant.16
Another kind of
evidence supporting the active placebo hypothesis comes from studies comparing
antidepressants to what are called ‘active placebos’. An active placebo is a
real drug that produces side effects, but that should not have any therapeutic
benefits for the condition being treated. It is used to prevent patients in
clinical trials from breaking blind - that is, from guessing the condition to
which they have been assigned on the basis of side effects. If the experience
of side effects leads patients to conclude that they are in the drug group,
rather than the placebo group, then the use of active placebos should keep them
in the dark.
What would happen
if active placebos were used in clinical trials, rather than inactive placebos?
Would one still get the relatively small but significant difference between
drug and placebo? We already have the beginning of an answer to this question.
Active placebos have been compared to antidepressants in nine clinical trials.17 In these trials, the drug atropine
was used as an active placebo. Atropine is an active medication. It is used in
the treatment of gastric dysfunctions such as irritable bowel syndrome,
diarrhoea and peptic ulcers. It can also be used to treat motion sickness,
bed-wetting and symptoms of Parkinson’s disease, but it is not an
antidepressant. Its side effects include a dry mouth, insomnia, headaches and
drowsiness, which have also been reported as side effects of antidepressants.
It has significantly fewer side effects than the antidepressants to which it
was compared in these trials, but should still help prevent patients from
breaking blind and realizing that they have been given a placebo, at least to
some degree.
Most of the
published clinical trials comparing antidepressants to inert placebos - that
is, placebos that do not produce side effects - show significant differences
between the active drug and the placebo. When an active placebo is used, most
clinical trials do not show a significant benefit for antidepressants. Of the
nine clinical trials in which an antidepressant was compared to atropine, a
significant difference between drug and placebo was found in only two.
Furthermore, in the two studies that asked raters to guess which patients had
been given antidepressants and which had been given the active placebo, the
raters were able to guess what medication had been given at better-than-chance
levels. Despite this, in the vast majority (78 per cent) of the clinical trials
in which active placebos were used, no significant differences were found
between the drug and the placebo. So comparisons with inactive placebos are
much more likely to show drug-placebo differences than comparisons with active
placebos. This suggests that at least part of the difference that has been found
between antidepressant and placebo may be due to the experience of more side
effects on the active drug than on the placebo.
Let’s summarize the
arguments for the active placebo hypothesis.
1. Antidepressants
produce significantly more side effects than inert placebos.
2. Most patients in
clinical trials are able to figure out whether they have been assigned to the
drug group or the placebo group before being told.
3. There are
relatively small but significant differences between active drugs and inert placebos,
and these differences are independent of the type of active drug that is used.
Indeed, the active drug need not even be an antidepressant.
4. Although a drug
need not be an antidepressant to be more effective than a placebo, it does seem
to need sufficient side effects that patients can figure out that they have not
been given a placebo.
5. When
antidepressants are compared to active placebos, differences in outcome are
substantially harder to find.
6. The more side
effects that depressed patients experience on the active drug, the more they
improve.
7. When you control
for differences in side effects, drug-placebo differences in improvement are
not statistically significant.
Taken together,
these data strongly support the idea that side effects lead clinical-trial
patients to realize they have been given the active drug, and that this
realization leads them to improve more than patients in the placebo groups. It
may not be conclusive proof, but it is strong evidence.
In this chapter we have
looked at the results of published clinical trials of antidepressant
medication. The published studies showed a significant, but surprisingly small,
effect of antidepressants over placebos. But as I noted at the beginning of the
chapter, those data represented only the beginning. As I later discovered,
there were also studies that had been withheld from publication. These
unpublished studies were clinical trials that did not show a significant
benefit for drugs over placebo medication - trials that the drug companies
withheld from public scrutiny. In the next chapter I describe the process by
which I learned about the hidden clinical trials and how not only the drug
companies, but also regulatory agencies, kept the data from the public.
The ‘Dirty Little
Secret’
When we wrote up our
meta-analysis for publication, Sapirstein and I were cautious in our
interpretation of the data. Despite our concerns about patients breaking blind
and realizing whether they were in the drug group or the placebo group, we
concluded that our results showed ‘a considerable benefit of medication over
placebo’. Nevertheless, the article reporting our analysis of the published
literature proved to be highly controversial - controversial enough for the
editors of the journal to insert a warning label at the beginning, much like
the warning label that you find on packs of cigarettes or, more recently, on
patient information leaflets for antidepressants. They wrote:
The article that
follows is a controversial one. It reaches a controversial conclusion - that
much of the therapeutic benefit of antidepressant medications actually derives
from placebo responding. The article reaches this conclusion by utilizing a
controversial statistical approach - meta-analysis. And it employs
meta-analysis controversially - by meta-analysing studies that are very
heterogeneous in subject selection criteria, treatments employed, and
statistical methods used. Nonetheless, we have chosen to publish the article.
We have done so because a number of the colleagues who originally reviewed the
manuscript believed it had considerable merit, even while they recognized the
clearly contentious conclusions it reached and the clearly arguable statistical
methods it employed. The article that follows is a controversial one. It
reaches a controversial conclusion - that much of the therapeutic benefit of
antidepressant medications actually derives from placebo responding.1
In the decade that has passed since our article
was published, the dust has settled around the issue of meta-analysis. It is no
longer considered a controversial procedure. Meta-analyses of clinical trials
are now routinely published in all of the top medical journals, and the
National Institute for Health and Clinical Excellence (NICE), which publishes
the treatment guidelines that are used by the NHS, crafts recommendations on
the basis of meta-analyses that it conducts. Nevertheless, the editors were
right about our article being controversial. Although some scholars in the
field were persuaded by our analyses, others were sceptical, to put it mildly.2 The sceptics knew that
antidepressants worked - if we had found otherwise, we must have done something
wrong. Certainly there were other clinical trials of antidepressants beyond
those that we had included in our analyses. Surely an analysis of those studies
would point to a different conclusion.
There were indeed
clinical trials of antidepressants that we had not included in our
meta-analysis, and there was also a meta-analysis of those other trials that
had used some of the same methods we had used. It showed the same results that
we had reported. The difference between drug and placebo in published trials of
antidepressants was modest at best.3 Still, the controversy continued.
In the midst of
this dispute, I received a letter from Thomas J. Moore, a senior fellow in
health policy at the George Washington University School of Public Health and
Health Services. Noting the continuing controversy over our article, Moore
proposed that I replicate our study with a different and more complete data
set. He suggested that I use the US Freedom of Information Act to obtain the
data that the drug companies had sent to the Food and Drug Administration (FDA)
in the process of getting their drugs approved for marketing.
The FDA is the
regulatory body that licenses medications in the US. The data submitted to it
are the data that are submitted to regulatory agencies around the world -
including the Medicines and Healthcare products Regulatory Agency (MHRA), which
approves drugs for marketing in the UK, and the European Medicine Agency
(EMEA), which licenses medications for the EU. So these were the data upon
which the antidepressants that are on the market today were approved for
doctors to prescribe. If there was anything wrong with those data, then
arguably the drugs should not have been approved in the first place.
There are a number
of advantages of analysing the FDA reports. One is that they include
unpublished as well as published studies. Before approving medications, the FDA
requires that the drug companies send them information on all of the trials
that the company has conducted, regardless of whether or not those trials have
been published. This is important because many clinical trials - especially
those that have not been successful - are not published. A report by
authorities at the Medical Products Agency (MPA) in Sweden suggests that as
many as 40 per cent of clinical trials of antidepressants are not published.4 In general, there is a tendency for
successful studies to be published and for unsuccessful studies either not to
be submitted for publication or to be rejected. This tendency is called
‘publication bias’, and it creates serious problems when one is reviewing the
published literature. Because of publication bias, reviewers are likely to
overestimate the effect of the drug they are reviewing. By gaining access to
statistical summaries of the complete data set in possession of the FDA, my
colleagues and I were able to avoid this publication bias.
A second advantage
of using the FDA reports is that the agency carefully scrutinized the data that
the drug companies had sent them. They examined the design of each of the
studies and appraised the statistical procedures that were used to analyse the
results. They asked the companies to provide more information and conduct
additional data analyses where they deemed these to be needed. Most
importantly, they excluded from consideration inadequate and poorly controlled
trials. This enabled us to cope easily with one of the vexing problems of
meta-analyses - that of assuring that all of the various studies included in
the analysis were up to par. This part of our job had been done for us by a
team of medical and statistical experts with the authority to gain information
to which we had no access.
Finally, all of the
trials in the FDA data set included the same measure of depression, a
physician-rated scale called the Hamilton Rating Scale for Depression (HRSD).
The Hamilton scale is completed by doctors based on interviews and observations
of patients. The doctor rates the patient’s mood, thoughts about suicide, sleep
disturbances and other symptoms of depression. For example, one point is given
if the patient feels that life is not worth living, and four points are scored
if the person has made a serious suicide attempt. The result is a numerical
score that can range from 0 to 51.
The virtues and
shortcomings of the Hamilton scale can be debated, but it is a widely used
scale with known clinical properties. The FDA uses it as its primary measure of
drug effectiveness, the American Psychiatric Association (APA) has developed
categories of severity of depression based on it, and NICE has used it to
establish cut-offs for establishing clinical significance. Having Hamilton
scores for the trials meant that we could interpret the meaning of the results
in clinical as well as statistical terms. In other words, we could examine the
effects of the drugs in terms of how meaningful they are in people’s lives.
Moore’s idea of
analysing the data that had been sent to the FDA seemed brilliant, and I
proposed that we work on it together. So we began. Moore wrote to the FDA
invoking the Freedom of Information Act and requested the medical and
statistical reviews of every placebo-controlled clinical trial for the
treatment of depression by what, at that time, were the six most widely used
‘new-generation’ antidepressant drugs: Prozac, Seroxat (Paxil in the US),
Lustral (Zoloft), Effexor, Dutonin (Serzone) and Cipramil (Celexa). Except for
Dutonin, which was withdrawn from the market after it was linked to cases of
liver failure, these are still among the most widely prescribed antidepressants
in the world.
Obtaining the FDA
files turned out to be pretty easy, and with the data from their reports in
hand, I asked two postgraduate students, Alan Scoboria and Sarah Nicholls, to
work with me on the analysis. Together we calculated the degree to which people
improved on each of the active drugs and how well they improved on placebos.
Our first stumbling block was the discovery that there were missing data, even
in the FDA medical and statistical reviews. We had data from all of the
clinical trials for Prozac, Effexor and Dutonin, but not from some of the
studies of Seroxat, Lustral and Cipramil. We knew of the existence of these
clinical trials, because they were mentioned in the FDA documents. We also knew
that they were ‘adequate and well-controlled’ trials, because they were
described as such in the FDA reviews. Finally, we knew that they were negative
trials - that is, they had not shown a significant difference between drug and
placebo. This information was also included in the FDA files. What were missing
were the actual numbers. For these particular clinical trials, we did not have
the exact degree to which depression scores decreased after patients were given
drug or placebo. Still, as Sapirstein and I had already shown and others have
since confirmed, there is not much difference in the effectiveness of one
antidepressant compared to another,5 and we did have the complete data
for Prozac, Effexor and Dutonin. Eventually, we were able to obtain the missing
Seroxat data as well. As part of the settlement of a lawsuit against them by
the State of New York, the manufacturer of Seroxat, GlaxoSmithKline,
established a website on which they provide summaries of all their clinical
trials. Using the information on this website, we later filled in the gaps in
the FDA data set and redid our analysis. The results were the same either way.
And even without the data from their worst trials, Lustral and Cipramil fared
no better.
Analysing the data
we had obtained from the FDA - data that included unpublished as well as
published studies - we found even less of a drug effect than in our analysis of
the published literature.6 Our analyses showed that 82 per
cent of the response to medication had also been produced by a simple inert
placebo. As conventionally interpreted, this means that less than 20 per cent
of the response to antidepressant medication is a drug effect.
To put this into
perspective, you might consider some calculations that my colleague Tom Moore
has performed on some other data that he obtained from the FDA. These showed
that about 50 per cent of the effects of a pain medication can also be produced
by placebos, whereas the placebo effect in drugs used to treat blood-sugar
levels is nil. In contrast, most of the improvement shown in drug-company
trials of antidepressants was due to the placebo response. In fact, most of the
clinical trials submitted by the drug companies failed to show any significant
benefit of their drugs at all. More important, the average difference between
improvement in the drug groups and improvement in the placebo groups was only
1.8 points on the Hamilton scale. The Hamilton is a 51-point scale, so a
difference of less than two points is very small indeed. For example, one can
get a six-point reduction in Hamilton scores merely by sleeping better, even if
there is no other change in the person’s depressive symptoms.
Having differences
in Hamilton scores was particularly important because it meant that we could
evaluate the clinical significance of the drug effect, as well as its
statistical significance. When researchers report that a difference is
significant, what they usually mean is that the difference is significant statistically. Statistical significance refers to whether
an effect - the difference between a drug and a placebo, for example - is real,
or whether it has just occurred by chance. It tells you how likely you are to
get the same results if you do the same study over again. But it does not tell
you how large or important the effect is. Whether a difference is statistically
significant depends on a number of factors, including the number of people that
were included in the study. The larger the study, the easier it is to find
statistically significant differences. If the study is large enough, even very
tiny differences will be statistically significant. Conversely, the smaller the
study, the harder it is to find differences that are statistically significant.
With very small studies, even relatively large effects might not be significant
statistically. It is like a seesaw. When the size of the study goes up, the
criterion for statistical significance goes down; and when the size of the
study goes down, the criterion for statistical significance goes up.
To evaluate the
importance of the difference of an effect, you have to look at the clinical significance of the findings. Unlike statistical
significance, clinical significance refers to the size of the effect. It
addresses whether it is likely to make a meaningful difference in anyone’s
life. An example might help clarify this. Imagine that a study has been
conducted on 500,000 people and has found that smiling increases life
expectancy. This seems very impressive, but on reading further you discover
that it increases life expectancy by only ten seconds. With 500,000 subjects, the
effect is likely to be statistically significant, but it is not clinically
meaningful.
So how can we judge
the clinical significance of the 1.8-point difference between improvement on
antidepressants and improvement on placebos? One way is to look at the Hamilton
scale and see how a difference of that size could be obtained. There are two
common versions of the Hamilton scale: a 17-item version and a 21-item version.
Fortunately, we do not have to be concerned about differences between these two
versions, because only the first 17 items on the 21-item scale are generally
scored. So as far as scores are concerned, the 17-item version and the 21-item
version are identical.
The Hamilton scale
is based on an interview with a doctor. The doctor completes the scale after
the interview, indicating scores for such symptoms as depressed mood, feelings
of guilt, thoughts of suicide, insomnia, and so forth. Total scores can range
from 0 to 51. A two-point difference can be obtained by no longer waking during
the night, or by no longer waking early in the
morning, or by being less fidgety during the
interview, or by eating better. Any one of these
changes can make a two-point difference in a person’s depression score, even if
there are no changes at all in the person’s depressed mood, feelings of guilt,
suicidal thoughts, anxiety, agitation or any of the other symptoms of
depression.
In my opinion - and
in the opinion of just about everyone in the field to whom I have spoken - a
two-point difference in depression scores on the Hamilton scale is not
clinically meaningful. But we need not rely on my opinion. NICE has established
a criterion for assessing the clinical significance of drug-placebo differences
on the Hamilton depression scale.7 According to NICE, the difference
between drug and placebo has to be at least three points to be considered
clinically significant. So the 1.8-point average difference in improvement that
we found in the drug-company-sponsored trials of their products is quite far
from being clinically significant.
DEPRESSION SEVERITY AND
ANTIDEPRESSANT EFFICACY
As an invited speaker
at various medical schools and hospitals, I have often been asked how severely
depressed the patients in the drug-company clinical trials had been. Maybe
antidepressants are no better than placebos for mildly depressed patients, it
was suggested, but perhaps they work well for people who are severely
depressed. In other words, the small average effect that we found might be
misleading. It might hide a substantial effect for severely depressed patients
that is masked by no effect at all for mildly depressed people. Indeed, the
NICE guidelines concluded that there is some evidence of a clinically
significant effect of the drugs in severely depressed patients, but not in
those who are only mildly or moderately depressed.8
NICE’s conclusions were based on the published data, however, and my colleagues
and I had the unpublished data as well. So we reanalysed the FDA data to see
whether severity made a difference. To help with this project, I enlisted the
aid of two experts on the theory and practice of meta-analysis, Professor Blair
Johnson and his associate Dr Tania Huedo-Medina at the University of Connecticut,
as well as that of Dr Brett Deacon, a researcher at the University of Wyoming,
who had identified the journal articles corresponding to those trials that had
been published.
We examined the
data in a number of ways. One was to use the classification system established
by the APA to categorize levels of depression. The APA system, which was also
adopted by NICE, divides scores on the Hamilton depression scale into the
following five categories:
• No depression (0-7)
• Mild depression
(8-13)
• Moderate depression
(14-18)
• Severe depression
(19-22)
• Very severe
depression (23 and above).
In examining
baseline depression scores (that is, measures of how depressed the patients
were before the clinical trial began), the first thing we noticed was that all
but one of the trials had been conducted with patients whose scores put them in
the ‘very severe’ category of depression. The single exception was a clinical
trial of Prozac conducted with moderately depressed patients. In other words,
our findings of a clinically insignificant difference between drug and placebo
was based primarily on data from those patients who are the most severely
depressed according to the APA and NICE classification scheme.
There was no drug
effect at all for the moderately depressed patients. They got considerably
better when given antidepressants - in fact, mildly and moderately depressed
people are the ones most likely to become completely free of depression when
given treatment - but they showed just as much improvement when given placebos.
Among the very severely depressed patients, there was a statistically
significant difference between drug and placebo, but it was pretty much the
same as the difference we had found when we had analysed the trials without
regard for initial severity of depression. Removing the data for moderately
depressed patients did not have much of an effect on the outcome of our
analysis. The difference between drug and placebo was still less than two
points on the Hamilton scale, well below NICE’s three-point criterion for
clinical significance. So the failure to find a clinically significant
drug-placebo difference was not because the patients were only mildly depressed
to begin with. The drug effect was small even for severely depressed patients.
Still, there was a
relationship between severity and the antidepressant drug effect. Figure 2.1 shows that relationship. It indicates the
amount of improvement that was shown at each level of depression severity. Now
this is a rather complicated figure, so let me walk you through it. The
triangles represent the drug response on each of the clinical trials; the
circles indicate the placebo response. The size of the triangle or circle
reflects the number of subjects in the trial. The larger the shape, the larger
the trial. This is important because data from larger trials are more reliable
than data from smaller trials. So when doing a metaanalysis, more weight is
given to large trials than to small trials.
Figure 2.1. The response to drug and placebo at different levels of initial
severity of depression.9
The most important
things to look at in Figure 2.1 are the solid horizontal line, representing
the average drug response, and the dashed diagonal line, representing the
average placebo response. The difference between them is the drug effect. That
difference gets greater and greater as baseline severity increases, until it
finally reaches clinical significance (the shaded area) for the most extremely
depressed patients - those with Hamilton scale scores of about 28 or more at
the beginning of the study they were in. The average drug-placebo difference in
this small group of relatively small studies was just over four points on the
Hamilton scale. A four-point difference is clinically significant, according to
NICE, but it is still rather small. Differences in sleep patterns, for example,
can produce a six-point difference in depression scores, without any other
differences in symptoms of depression. Still, this relationship seems to be
reliable. The worse the depression, the greater the drug effect.
If you look at the
figure again, you will see that there is something a bit strange about it. The
response to the drug does not become greater as depression increases. Instead,
the placebo response gets smaller, and that is what makes the drug-placebo
difference larger. Now this seems very curious. Why is there less of a placebo
response among extremely depressed patients, without much change in the drug
response? I can think of two factors that might account for this. First, these
patients tend to have been chronically depressed. They are much more likely to
have been on antidepressant medication before, and they know what it feels
like. Second, physicians are likely to prescribe higher doses to patients who
are more severely depressed. As I show later in this chapter, the dose-response
studies that have been done tell us that this does not make much difference in
the effect of the antidepressant. Low doses of SSRIs are just as effective as
higher doses. But unlike the therapeutic effects, the side effects of SSRIs are dose-dependent. The higher the dose of the medication,
the more side effects you get. Putting these two factors together suggests that
more extremely depressed patients are particularly likely to recognize whether
they have been put on placebo or on the real drug. When they don’t experience
the side effects they are used to, even on high doses of the new medication,
they may conclude that they have been placed in the placebo group, and this
recognition may dampen the placebo effect. If this is the case, then even the
relatively small but clinically significant drug effect seen in extremely
depressed patients may be a placebo effect in disguise.
Now I have to admit
that my speculation about the severity effect being due to breaking blind, and
guessing correctly whether or not one has been given the real drug, is just
conjecture. There may be other explanations. I have not been able to think of
any, nor has anyone suggested to me another plausible explanation. Still, I
consider my proposed explanation to be no more than a hypothesis, which might
very well turn out to have been mistaken. But it might also be correct. And if
it is, then there may not be a real drug effect, even amongst the most severely
depressed patients.
Prior to submitting our
analysis of the published data to a journal, Sapirstein and I were concerned
that we might have underestimated the drug effect by lumping together effective
drugs with ineffective drugs - a concern that proved to be unfounded, as there
turned out not to be any meaningful differences between one type of drug and
another, even when looking at drugs that are not antidepressants. My colleagues
and I had an analogous concern about the data we had received from the FDA.
This time it was not differences in type of drug that concerned us - all of
them were drugs that were supposed to inhibit the reuptake of the
neurotransmitter serotonin - but rather differences in prescribed doses.
There are two ways
in which clinical trials can be conducted. One method is to allow physicians to
adjust the dose of the drug for each individual patient, just as they would in
normal clinical practice. An inadequate response to treatment might lead the
doctor to increase the dose. Concerns about side effects might lead to a lower
dose. This is an excellent clinical-trial practice, in that it mimics what
would happen when the drug is placed on the market. But it leaves an important
question unanswered: what is an effective dose of the medication being tested?
To answer that
question, a different type of clinical trial is used. In dose-response trials,
patients are randomly assigned to receive low, moderate or high doses of the
drug - or no drug at all in the placebo condition. Our concern was that
patients given low doses of the antidepressant might not have responded because
the dose was too low. By including these patients in our analysis, we might
have underestimated the drug effect.
To check whether
this might have biased our results, we compared the effect of treatment with
the lowest dose of the drug to that of treatment with the highest dose. This
led to the next of my many surprises. Putting the data from all of the
dose-response trials together, we found that there was no difference between
the effect of a high dose of antidepressants and the effect of a low dose. The
average improvement on the Hamilton scale was 9.97 points on the highest dose
of the drugs and 9.57 on the lowest dose.
Looking at the
trials individually, we found 40 statistical comparisons between specific doses
of the same drug. These yielded only one significant finding: low doses of
Prozac were more effective than high doses. When you do a large number of
statistical comparisons, you expect to get some spurious findings due to
chance, and that is probably what the one test showing that a lower dose is
better than a higher dose was - a chance finding. By and large, there is no
relationship between how much of an antidepressant people take and how much
they improve.
Some drugs produce
effects at relatively small doses, following which it does not matter how much
more you administer. A small dose of cyanide, for example, will leave you just
as dead as a large dose. But most drug effects are dose-dependent. A small
glass of wine at dinner has much less of an effect than four pints of lager
afterwards. Even placebos have dose-related therapeutic effects. A Dutch
researcher, Ton de Craen, and his colleagues found that ulcers healed at a
significantly greater rate when patients were treated four times a day rather
than twice a day, despite the fact that the treatment in both cases was a
placebo.10 But unlike
alcohol or placebos, the therapeutic effects of antidepressants are not
dose-dependent - at least not when the patients are unaware of whether they are
getting a high dose or a low dose. Although higher doses of antidepressants can
produce more side effects,11 they do not
produce greater reductions in depression. The difficulty of finding
dose-related therapeutic effects of antidepressants is yet another reason for
suspecting that those effects may be independent of their chemical action.
The equivalence of
high and low doses of antidepressants is well known, yet doctors often increase
the dose of the antidepressant when their patients do not improve. Why do they
do this? The official Summary of Product Characteristics for Prozac provides a
clue. It notes that ‘in the fixed dose studies of patients with major
depression there is a flat dose response curve, providing no suggestion of
advantage in terms of efficacy for using higher than the recommended doses’.
Nevertheless, despite the absence of evidence that higher doses produce better
effects, the very same document advises physicians as follows:
The recommended dose
is 20mg daily. Dosage should be reviewed and adjusted if necessary, within 3 to
4 weeks of initiation of therapy and thereafter as judged clinically
appropriate. Although there may be an increased potential for undesirable
effects at higher doses, in some patients, with insufficient response to 20mg,
the dose may be increased gradually up to a maximum of 60mg. Dosage adjustments
should be made carefully on an individual patient basis, to maintain the
patients at the lowest effective dose.
So when increasing the dose of antidepressants,
doctors are merely following the manufacturer’s advice, as reported in the
Summary of Product Characteristics.
If the dose
response curve is flat and higher doses produce an ‘increased potential for
undesirable effects’, why does the Summary of Product Characteristics advise
doctors to triple the dose if patients do not respond well enough to a lower
dose? The key to understanding this contradiction is our old and trusted
friend, clinical experience. The company notes that despite the negative data,
‘it is clinical experience that uptitrating [increasing the dosage] might be
beneficial for some patients’.
A study reported by
Otto Benkert and his colleagues at the Department of Psychiatry at the
University of Mainz shows how this works.12 Depressed patients who failed to respond to
antidepressant medication were given an increased dose of the drug, following
which 72 per cent of them improved significantly by showing at least a 50 per
cent reduction in symptoms of depression. The catch was that the dose had only
been increased for half of the subjects. The others only thought the dose had
been increased; in fact it had not. Yet the response rate was the same 72 per
cent in both groups. So a patient whose dose of the drug is increased may
indeed show more improvement, but this effect may be due to the patient’s
knowledge that the dose has been increased, rather than to the chemical effect
of the medication. In other words, doctors are advised to increase the dose
(and the likelihood of troubling side effects) as a means of strengthening the
placebo effect.
Our first published
report of the FDA data was accompanied by nine expert commentaries, some of
them by researchers who had conducted clinical trials of antidepressant
medication. Although there were vast differences in interpretation, this time
there were no doubts about the accuracy of our analysis. Some commentators argued
that our analysis had actually overestimated the real
effect of antidepressants. Others argued that the clinical trials sponsored by
the drug industry are flawed and that they may underestimate the actual benefit
of antidepressants. But all agreed that our description of the data was
accurate. As one defender of antidepressants phrased it, ‘“the data are the
data,” and it is clear that antidepressants have relatively small, specific
effects for the patients who participate in the RCTs [randomized clinical
trials] conducted by the pharmaceutical industry.’13
After my experience
with the previous meta-analysis, I was very pleasantly surprised by the
consensus about our basic findings. I was even more surprised to learn that our
findings did not come as news to those who were actively involved in
antidepressant research. Indeed, one group of researchers wrote: ‘Many have
long been unimpressed by the magnitude of the differences observed between
treatments and controls, what some of our colleagues refer to as the “dirty
little secret” in the pharmaceutical literature.’14
So we had not
discovered anything new at all. We had just uncovered a ‘dirty little secret’
that had been known all along. The companies that produce the drugs knew it,
and so did the regulatory agencies that approve them for marketing. But most of
the doctors who prescribe these medications did not know it, let alone their
patients.
Pharmaceutical
Companies Keeping Mum
How was this secret
kept? How is it that even the doctors who prescribe antidepressants did not
know how limited their effects were compared to dummy pills? Pharmaceutical
companies have used a number of devices to make their products look better than
they actually are. They have:
• Withheld negative
studies from publication
• Published positive
studies multiple times
• Published only some
of the results from multi-site studies
• Published data that
was different from what they submitted to the FDA.
The tendency to
publish only the more successful trials has been most clearly documented by
Hans Melander and his colleagues at the Medical Products Agency (MPA) in
Sweden.15 The MPA, which
is responsible for approving new medications for marketing in Sweden, is the
Swedish equivalent to the FDA in the US, the MHRA in the UK, and the EMEA in
the EU. Melander and his colleagues searched the medical literature for the
publications corresponding to the clinical trials that the drug companies had
submitted to the MPA. They found that almost all of the successful clinical
trials had been published, whereas most of the negative trials had not been
published. Solvay Pharmaceuticals, for example, reported ten trials of the SSRI
Faverin to the Swedish authorities. Only three of these studies showed a
significant benefit for the active drug; the other seven did not. All three
successful clinical trials were published as individual studies. Only one of
the seven unsuccessful studies made it into print. In 1991 Faverin was approved
for marketing in Sweden.
Earlier in this
chapter, I mentioned this problem of publication bias - the tendency for
successful studies to be published and unsuccessful studies not to be
published. The failure to publish unsuccessful trials presents a problem in
many research areas. When a study has produced non-significant results, it is
less likely to be submitted for publication; and, if it is submitted, it is
less likely to be favourably reviewed or accepted for publication. But although
publication bias affects all areas of research to some extent, it is
particularly acute when it comes to drug trials. This is because most of the
clinical trials evaluating new medications are sponsored financially by the
companies that produce and stand to profit from them. The companies own the
data that come out of the trials they sponsor, and they can choose how to
present them to the public - or to withhold them and not present them to the
public at all. With widely prescribed medications, billions of dollars are at
stake. In this case, it is not reviewers or journal editors who are impeding
publication of negative findings. Rather it is the companies themselves that
decide to withhold negative data from publication.
My contention that
the drug companies sometimes withhold publication of negative data
intentionally is not merely an opinion or deduction. It is a documented fact.16 During the 1990s, GlaxoSmithKline
conducted three clinical trials on the efficacy of paroxatine, which is sold in
the UK under the brand name Seroxat, in the treatment of major depression in
children and adolescents. One study showed mixed results, a second showed no
significant differences between drug and placebo, and the third trial suggested
that the placebo might actually be more effective than Seroxat for children
aged seven to eleven. Only one of these trials was ever published. The other
two studies remained hidden, and the public might never have known about them,
had a confidential internal company document not fallen into the hands of the Canadian Medical Association Journal.17 According to the document, the company’s ‘target’
was to ‘effectively manage the dissemination of these data in order to minimize
any potential negative commerical impact’. While acknowledging that the data
were ‘insufficiently robust’, it nevertheless proposed the publication of the
one study with mixed results. The company document noted that ‘it would be
commercially unacceptable to include a statement that efficacy had not been
demonstrated, as this would undermine the profile of paroxetine’. So when the
study was published in 2001, the article concluded that ‘paroxetine is
effective for major depression in adolescents’.18
In June 2004, Eliot
Spitzer, who was then Attorney General and later became Governor of the State
of New York, filed a lawsuit against GlaxoSmithKline, charging that the company
had ‘engaged in repeated and persistent fraud by concealing and failing to
disclose to physicians information about Paxil [the brand name for Seroxat in
the US]’.19 The case was
settled two months later, with the company agreeing to pay $2.5 million to the
State and to establish an online clinical-trial register containing summaries
of the results of all of the clinical trials they sponsored.20 This is the website through which my colleagues and
I were able to find the negative trial data that had been missing from the FDA
files. Spitzer predicted that other manufacturers of antidepressants would soon
follow suit, but by and large they did not.21
Most studies showing negative results remain unpublished, and short of making
official enquiries to government agencies, their data are unavailable to
researchers, doctors and the public at large.
Picking Cherries and
Slicing Salami
One would think that
withholding negative data and publishing only the successful trials would be
sufficient to maintain the ‘dirty little secret’. But the pharmaceutical
companies had other tricks up their sleeves. Whereas many of the negative
trials were not published at all, some of the positive trials were published
many times, a practice known as ‘salami slicing’, and this was often done in
ways that would make it difficult for reviewers to know that the studies were
based on the same data.22 In some cases, the authors were
different, and references to previous publication of the data were often
missing. Sometimes there were minor differences in the data between one
publication and another, as well as between the data as presented to regulatory
agencies and the data as published. So a reviewer trying to summarize the data
would be likely to count the positive data more than once.
Another trick was
to publish only some of the data from a clinical trial, a manoeuvre that
researchers call cherry-picking the data. Some clinical trials are conducted in
more than one location. These are called multi-centre studies. Multi-centre
studies make it easier to find sufficient patients to conduct the trial. They
also make it easier to cherry-pick the data. For example, one multi-centre
study of Prozac was presented to the FDA as showing a drug-placebo difference
of three points on the Hamilton scale. When data from this clinical trial was
published, the difference was reported as 15 points - a five-times increase in
effectiveness. How was this magical augmentation of the benefits of Prozac
accomplished? The full study was conducted on 245 patients. The published paper
reported data from only 27 of these patients. In the published version, the
data from the bulk of the patients were left out, making the drug seem much
more effective than it really was.
Drug companies also
publish ‘pooled analyses’ of the trials they have conducted. That is, they
bundle together the results of different trials and analyse the drug-placebo
difference across them. This is similar to the meta-analyses my colleagues and
I have conducted, but with one important difference. Our meta-analyses, in
common with most others reported in the scientific literature, are based on all
of the studies that we were able to find. In contrast, the drug companies pick
and choose which studies they wish to include in their pooled analyses. For
example, GlaxoSmithKline submitted 15 clinical trials of Seroxat to Swedish
regulators. In addition to being published individually - sometimes more than
once - studies with positive results were also included in six different pooled
analyses. Most of the studies with negative results were, of course, not
included in the pooled analyses.
There is yet
another way in which pooled analyses can hide negative data. Rather than not
publishing the negative data at all, the companies can bundle them together
with data from positive trials, so that the overall result is positive. By so
doing, they can truthfully claim that they have published the data from a
negative trial, while hiding the fact that those data showed no difference
between drug and placebo. The article by the Swedish regulators showed that the
data from about 20 per cent of clinical trials were not published at all. The
data from another 20 per cent of the trials were bundled together with data
from more successful trials, so that their negative results were hidden from
view. Taken together, approximately 40 per cent of the data are kept out of
sight.23 Practices like this make
antidepressant drugs seem much more effective than they actually are, and they
also make it exceptionally difficult for reviewers to establish how effective
the drugs really are.
Perhaps the best
indication of the difficulties that are posed by selective publication is
provided by the problems that NICE faced when drawing up its 2004 guidelines
for the treatment of depression. Having read our meta-analysis of the FDA data,
NICE contacted me in the hope of adding the unpublished data to their analysis
of the published data. Although they wanted to include the unpublished as well
as the published data, they did not want to include any of the data more than
once, because that would have biased the results. So they asked me whether I
could tell them which of the FDA trials had been published and what the
publications were corresponding to each. There was no easy way to do this. NICE
tried, but eventually gave up and reported in their guidelines that although
they had planned to combine their data with ours, ‘it was not possible to
determine which of the FDA data had been subsequently published’.24
For doctors,
researchers and policy setters to do their work properly, they need to have
access to full and complete information. This can be done if pharmaceutical
companies are required to do the following:
1. Register all
clinical trials before they are started.
2. Make summary data
publicly available for all completed trials and for trials that have been
stopped prior to completion.
3. Describe the
methods used in those trials at a level of detail that is at least comparable
to what is found in scientific-journal articles.
4. Include references
to prior publications and reports of data, so that they cannot be inadvertently
counted twice by reviewers.
5. Make the raw data available,
so that independent researchers and agencies can do their own analyses of them.
The first of these
requirements has already been met. In 2004 the International Committee of
Medical Journal Editors established a requirement that all clinical trials be
registered publicly before they begin enrolling patients.25 Any trial that has not been
registered will not be considered for publication, at least not by the journals
that have agreed to this policy. This is a strong enough threat to ensure
compliance. It means that the existence of the trial will be known publicly -
but not necessarily its outcome. Knowing the existence of a trial is helpful,
but not enough. The data coming out of the trial also need to be publicly
available, along with details of the methods by which the data were collected
and the publications that have resulted from it. Without this, researchers
reviewing the clinical-trial literature will not be able to make accurate
assessments of the efficacy of medications, and doctors prescribing drugs to
their patients will not have sufficient information to make informed
recommendations.
The importance of
the fifth of my proposed requirements - that of having the actual data
available, rather than just summaries - is highlighted by an experience that
NICE had when preparing their 2004 guidelines for the treatment of depression.
They would have liked to analyse the effects of age, gender and ethnicity on
treatment outcome. This is important information in drawing up treatment
guidelines, because the drugs might be more effective for some groups of
patients than for others. According to Sir David Goldberg, who chaired the
panel that wrote the 2004 guidelines for the treatment of depression, NICE
requested this information from the drug companies, but the companies refused
to release it. ‘If they had, we could have run analyses,’ he said. ‘No chance!’
If there are
subgroups of depressed patients who respond well to antidepressants, it would
be very important to know who they are, so that antidepressant prescriptions
could be targeted to them directly. However, this might not be something that
the manufacturers of these medications would be eager to find out, because if
there are some patients who respond better than average, then there must be
others who respond worse. You can see this in our analysis of the data on
severity of depression. The drug effect was a little better than average for
the most extremely depressed patients, but it was non-existent for those who
were moderately depressed. Knowing who responds to a drug and who does not is
very important, not only so that responders can be given effective medication
for their depression, but also so that the non-responders are not given drugs that
have potentially serious side effects, but produce no therapeutic benefit for
them at all.
Regulatory Agencies
Keeping Mum
In our meta-analysis,
more than half of the clinical trials submitted to the FDA showed no difference
between drug and placebo. Most reviewers of the clinical-trials literature have
not had access to unpublished studies and may not even know of their existence.
But the FDA and other regulatory agencies around the world knew of these data.
Nevertheless, their existence is not even mentioned in the product labels,
information leaflets and official Summaries of Product Characteristics (SPC) of
most antidepressants.
Why didn’t the
regulatory agencies inform the public that many clinical trials of
antidepressants failed to show a significant benefit of the drug over placebo?
In the case of the FDA, we know the reason. It was not just an oversight.
Buried in the FDA files on the SSRI Cipramil, my colleagues and I found an
internal FDA memo expressing the opinion that ‘the provision of such
information is of no practical value to either the patient or prescriber’ and
that it need not be included in the labelling for the drug. In the US,
labelling information is published in the Physicians’ Desk
Reference, a compendium of FDA-approved information to which physicians
often turn in deciding what drugs to prescribe. So the decision to exclude
information about failed clinical trials meant that most doctors prescribing
the medication would not know of them.
The author of the
FDA memo revealing the decision to hide the existence of the clinical trials
that had failed to find a difference between drug and placebo was Dr Paul
Leber, Director of the FDA Division of Neuropharmacological Drug Products. Here
is what he wrote about the labelling of Cipramil, which is referred to by its
generic name, citalopram, in the document:
One aspect of the
labeling deserves special mention. The Clinical Efficacy Trials subsection
within the Clinical Pharmacology section not only describes the clinical trials
providing evidence of citalopram’s antidepressant effects, but makes mention of
adequate and well controlled clinical studies that fail to do so. I am mindful,
based on prior discussions of the issue, that the Office Director is inclined
toward the view that the provision of such information is of no practical value
to either the patient or prescriber. I disagree. I believe it is useful for the
prescriber, patient, and 3rd party payer to know, without having to gain access
to official FDA review documents, that citalopram’s antidepressant effects were
not detected in every controlled clinical trial intended to demonstrate those
effects. I am aware that clinical studies often fail to document the efficacy
of effective drugs, but I doubt the public, or even the majority of the medical
community, are aware of this fact. I am persuaded that they not only have a
right to know, but should know. Moreover, I believe that labeling that
selectively describes positive studies and excludes mention of negative ones
can be viewed as being potentially ‘false and misleading.’26
Perhaps it is not without reason that in Italy a
patient information leaflet is sometimes called a ‘bugiardino’
- literally, ‘little liar’.
Leber’s laudable
argument that mention of negative trials be included in the labelling
information had relatively little effect. Although a brief mention of these
trials was added to the citalopram label, the FDA continued to approve
antidepressant labelling that did not disclose the existence of negative data.
In fact, it went even further. It urged the drug companies to keep the studies
hidden. According to an article in the Washington Post:
The Food and Drug
Administration has repeatedly urged antidepressant manufacturers not to disclose
to physicians and the public that some clinical trials of the medications in
children found the drugs were no better than sugar pills, according to
documents and testimony released at a congressional hearing yesterday.
Regulators suppressed the negative information on the grounds that it might
scare families and physicians away from the drugs, according to testimony by
drug company executives. For at least three medications, they said, the FDA
blocked the companies’ plans to reveal the negative studies in drug labels.27
How can we explain
such strange behaviour on the part of regulatory agencies? Perhaps part of the
answer lies in the way they are funded. Once upon a time, the FDA was funded
solely by the government. But that changed in 1992, when Bush senior signed a
bill into law allowing the FDA to charge the drug companies fees to evaluate
their new products, so that they could be approved more quickly. One of the
stipulations of that bill was that none of the funds could be used by the FDA
to monitor the safety of the medications it approved. That was relaxed to some
extent when the law was reauthorized, first under Bill Clinton in 1997 and
again under George W. Bush in 2007, but it is still the case that only a small
percentage of the fees can be used for safety monitoring.
In April 2007, when
the law approving drug-company funding of the FDA was up for renewal, it was
heavily criticised in a spirited article in the New England
Journal of Medicine.28 In that
article, Jerry Avorn, a Professor of Medicine at Harvard University, described
some of the effects that the law had on the FDA regulatory process. The law had
been conceived in response to complaints by AIDS activists about how long it
took for new drugs to be approved, and one of its provisions was the impos -
ition of strict deadlines for decisions. In the FDA’s efforts to meet those
deadlines, its Office of Drug Safety was downsized, as resources were shifted
from safety monitoring to drug approval. According to Avorn, ‘One FDA scientist
who was often criticized for being too concerned about drug-risk data was told
by his supervisor to remember that the agency’s client was the pharmaceutical
industry. “That’s odd,” the FDA scientist replied. “I thought our clients were
the people of the United States.”’29
Lest you think the
financial entanglement between the drug industry and those who regulate it is
only an American problem, let me assure you that it is not. Drug-company
funding accounts for 40 per cent of the FDA budget, but it provides more than
70 per cent of the income for the EMEA, and ever since Margaret Thatcher took
the Department of Health out of the business of regulating the drug companies,
all of the funding for the MHRA has come from the pharmaceutical industry.30 It may not be a case of the fox
guarding the hen house, but it does seem to resemble asking the thieves to feed
the guard dog. If a conflict of interest is to be avoided, it might be better
to fund regulatory agencies from general tax funds, even if the companies are
then charged fees by the government to compensate for the expense.
WHY WERE THE DRUGS
APPROVED? VOODOO SCIENCE
Although doctors and
their patients did not know about the unpublished negative trials or how small
the drug effect was, the regulatory agencies did. So how is it that these drugs
were approved for marketing in the first place? This is an obvious question,
and I am not alone in raising it. Officials from the drug regulatory agencies
of the European Union, France, the Netherlands and Sweden raised the same
question in a ‘regulatory apologia’ that they published after our 2008 meta-analysis
came out. ‘Against this background,’ they wrote, ‘one can ask why the
new-generation antidepressant medicinal products were ever approved.’31
To answer this
question, the regulators conducted their own meta-analysis of some of the data
in their files. Their results were very similar to ours. They agreed that the
average observed difference in improvement between drug and placebo is only
about two points on the Hamilton scale, and their data also showed that most of
the drug response could be explained as a placebo effect. Nevertheless, they
argued that they had shown that the drugs were better than placebos, not only
statistically, but clinically as well.
How were the
European regulators able to pull off the trick of turning a two-point
difference on the Hamilton depression scale into a clinically significant
benefit? They did so by using a different criterion for improvement than the
one we had used in our analysis of the clinical-trial data. We had analysed the
average degree of improvement in symptoms that patients given antidepressants
and placebos had experienced. This is a common measure of the drug effect, and
it was used by NICE in establishing a criterion for clinical effectiveness. In
their apologia, however, the European regulators examined response rates
instead of average improvement. A ‘response rate’ is the percentage of people
whose symptoms decreased by some specified amount. In antidepressant drug
trials, a 50 per cent reduction in symptoms is most often used as the criterion
for separating ‘responders’ from ‘non-responders,’ and this is the criterion
that the European regulators used.
Using this common
definition of response, the European regulators reported that 49 per cent of the
people in the drug groups had gotten better, compared to only 33 per cent of
patients given placebos. The difference between these two percentages is 16 per
cent. The regulators argued that these patients had benefited from having been
given the real drug instead of placebos; and that, they said, is clinically
significant.
There are two ways
of looking at these data. On one hand, they indicate that antidepressants only
help 16 per cent of the patients to whom they are prescribed. The rest of those
who get better would also have gotten better on a placebo. On the other hand,
given the popularity of antidepressants, 16 per cent represents a lot of
people, and one could well argue that a medication that can help so many people
deserves to be marketed.
Still, this does
not tell the whole story. The conclusion that 16 per cent of depressed people
benefit only from the real drug is actually an illusion based on a numerical
sleight of hand - although I suspect that the regulators were not aware of this
when writing their apologia. My colleague Joanna Moncrieff and I have shown how
the response-rate illusion works.32 People whose symptoms have
diminished by 49 per cent or less are classified as ‘non-responders’, and those
whose symptoms improved by 50 per cent or more are classified as ‘responders’.
The illusion lies in the implication that the ‘non-responders’ have not gotten
better at all. In fact, many of them have experienced substantial clinical
improvement, so much so that a very small boost - as little as one additional
point of the 51-point Hamilton depression scale - can push them over the 50 per
cent criterion, turning them into ‘responders’. These are the 16 per cent of
depressed people who get classified as ‘responders’ when given an
antidepressant and as ‘non-responders’ when given a placebo.
In other words,
even the small percentage of people who ‘respond’ only to the real
antidepressant do not get much chemical benefit from the medication. Most of their
improvement can be explained as a placebo effect. On average, the drug adds two
additional points of improvement on the Hamilton scale, beyond what these
patients would have obtained on placebo. This is enough to push them over the
arbitrary, but widely used 50 per cent criterion that separates clinical
‘responders’ from ‘non-responders’. The boost might derive from a small
specific effect that drugs have on depression, but as I noted in Chapter 1, it
could also come from the experience of side effects from the active drug, which
lead clinical-trial patients to conclude that they have been assigned to the
drug group rather than the placebo group, thereby producing an enhanced placebo
effect. But in either case the effect is small and it does not meet conventional
criteria for clinical significance.
So why were the
drugs ever approved? The real answer to this question lies in the criteria that
are used for antidepressant drug approval. The efficacy criterion used by drug
regulators requires two ‘adequate and well-controlled’ clinical trials showing
that a drug is better than a placebo. But there are some catches. The first
catch is that there is no limit to the number of studies that can be run in
order to find the two showing a statistically significant effect. Negative
trials just don’t count. The second catch is that the size of the drug-placebo
difference - its clinical significance - is not considered, although the
published ‘apologia’ suggests that this might change.
The FDA approval of
citalopram (Cipramil) provides a convenient example of how this works. Seven
placebo-controlled efficacy trials were conducted. Two showed small but
significant differences between drug and placebo. Another two trials failed to
show significant differences, but were deemed too small to count. Three other
trials that were deemed adequate and well controlled also failed to show
significant drug-placebo differences. For each of them, the leader of the FDA
new drug application team stated that ‘the reasons for the negative outcome for
this study are unknown’, and for two of them he added that ‘there was a
substantial placebo response, making it difficult to distinguish drug from
placebo’. In his summary of these three negative trials, the team leader wrote,
‘I feel there were sufficient reasons to speculate about the negative outcomes
and, therefore, not count these studies against citalopram.’33 Agreeing with this assessment, the Division
Director concluded that ‘there is clear evidence from more than one adequate
and well controlled clinical investigation that citalopram exerts an
antidepressant effect’.34 This, in my
opinion, is voodoo science. The drug companies can conduct as many trials as
they want until they find two showing significant effects. The negative trials
simply don’t count.
Even with the five
negative trials discounted, the size of the drug-placebo difference for
citalopram was small. It averaged only two points on the Hamilton scale, well
below the three-point difference that NICE uses as its criterion for clinical
significance. The FDA reviewers recognized that the difference was small. The
team leader wrote that ‘while it is difficult to judge the clinical
significance of this difference, similar findings for other SSRIs and other
recently approved antidepressants have been considered sufficient to support
the approvals of those other products’. So citalopram was approved as well.
When reading the FDA
memos on citalopram, I was struck by a curious phrase. The FDA team leader for
the new drug application wrote that the three adequate and well-controlled
negative trials were ‘not easily interpretable since there were no active
control arms’.35 An ‘active control arm’ is a group
of subjects who are given an older established drug, against which the effects
of the new drug might be evaluated. So there are ‘two-arm’ trials, in which a
drug is compared to a placebo, and ‘three-arm’ trials, in which a new drug is
compared to both a placebo and an older drug.
Why would you
include an older established drug in a clinical trial? You might suppose that
this would be to see if the new drug is better. That is what I had assumed until
I read the FDA memo, but the memo made me wonder. Why should the absence of
another drug in the study make it harder to interpret a failure to find a
difference between the new drug and a placebo?
It turns out that
there is another reason for including a second medication in a clinical trial.
You may remember that there is not much difference in effectiveness between one
drug and another in the treatment of depression (see Chapter 1). So trying to
show that the new drug works better is not likely to pay off, and given how
expensive clinical trials are and how difficult it can be to recruit subjects
for them, a drug company would not want to include an additional ‘arm’ unless
it paid off. So why include it?
Here is how it
works. Let’s say the new drug successfully outperforms placebos in the study.
That’s fine; it means that the drug works. In this case, it really does not
matter that it is not more effective than the old drug, and it does not matter
whether the old drug worked better than placebos. But what if the drug does not
work significantly better than placebos? That is what happens in about half of
the clinical trials in which antidepressants and placebos are compared. In that
case, you can look at whether the old drug did better than placebos. If it did
not, then you conclude that the study lacked ‘assay sensitivity’. An assay is
an analysis or assessment. So if a trial lacks assay sensitivity, it means that
it is not sufficiently sensitive to analyse the effectiveness of the drug, and
that therefore the study should not be counted as evidence against the new
drug. The logic is as follows: we know the old drug works, because it has
already been approved. So if this clinical trial doesn’t show it to be
effective, it must be that the trial is not ‘sensitive’ enough to detect
differences. No matter that the old drug did not work in many of the trials
that led to its approval, and there is no need to explain or even speculate as
to why the study was not sensitive enough. Assay sensitivity is just a way to stack
the deck in favour of the new drug.
The assay sashay is
like betting on coin tosses with the following rules. We toss two coins. If the
first one comes up heads, I win, and the second coin is irrelevant. If the
first one comes up tails, we have to decide whether the toss counts. To do
that, we look at the second coin. If it also comes up tails, the toss does not
count and we call it a draw. With these rules, I will win 50 per cent of the
time and it will be a draw 25 per cent of the time. You win only if both the
first coin comes up heads and the second comes up tails, which will only happen
25 per cent of the time. So the odds are heavily stacked in my favour. If you
doubt this, please get in touch. I will be happy to play you for real money.
Using these standards to judge the effectiveness of a medication is voodoo
science to the nth degree.
Our analyses of the FDA
data showed relatively little difference between the effects of antidepressants
and the effects of placebos. Indeed, the effects were so small that they did
not qualify as clinically significant. The drug companies knew how small the
effects of their medications were compared to placebos, and so did the FDA and
other regulatory agencies. The companies found various ways to make the data seem
more favourable to their products, and the FDA helped them to keep their
negative data secret. In fact, in some instances, the FDA urged the companies
to keep negative data hidden, even when the companies wanted to reveal them. My
colleagues and I hadn’t really discovered anything new. We had merely revealed
the ‘dirty little secret’. How were our revelations received? In the next
chapter I review the responses - favourable and unfavourable - that were
aroused by the publication of our analyses, and I respond to the criticism that
some defenders of antidepressant medication have levelled.
Countering the Critics
At first, I was very
surprised to find that the response to antidepressant drugs was so small when
compared to placebos. The media also found it new and revelatory - not only
once, but three times. Ten years ago the meta-analysis of the published
clinical-trial data that Guy Sapirstein and I had done was reported in
newspapers, magazines, and television documentaries around the world, as well
as in the news section of Science, one of the world’s
top scientific journals, spanning all branches of science. The first analysis
that my colleagues and I had done on the FDA data set was also covered widely
in the media. Nevertheless, I was unprepared for the reaction to our most
recent and most complete analysis. I woke up on the morning of 26 February 2008
to find that it was front-page news in The Times, The Guardian, The Independent and
the Daily Telegraph. It was reported on the BBC, ITV,
Sky News and Channels 4 and 5. It made its way into newspapers and television
and radio news programmes in the US, Spain, Portugal, Germany, Italy, South
Africa, Australia, Canada, China and many other countries. It was also reported
and debated in a number of leading medical and scientific journals. Overnight,
I seemed to have been transformed from a mild-mannered university professor
into a media superstar - or super-villain, depending on whom you asked.
In addition to
attracting media attention, the publication of the 2008 meta-analysis also had
practical effects. On 23 May 2008, a scant three months after its publication, Onmedica.com published
a survey of 490 doctors in the UK, in which it asked them what effect our
analysis would have on their prescribing practice. Almost half (44 per cent)
said that they would change their prescribing habits and consider alternative
treatments rather than SSRIs for their depressed patients.1
It is not often
that researchers find their work leading to such widespread changes of
behaviour. Still, the 44 per cent figure reveals a split opinion. Most
physicians did not intend to alter their prescribing practices. Our analysis
has provoked a vociferous and continuing debate on the effectiveness of
antidepressants and the circumstances under which they should be prescribed. In
this chapter I consider and respond to the various criticisms that have been
levelled at our data-based conclusions about the efficacy of antidepressants.
‘ANTIDEPRESSANTS WORK IN
CLINICAL PRACTICE’
Many doctors and
patients have reacted to our meta-analysis with simple disbelief. David Nutt,
head of the Psychopharmacology Unit at the University of Bristol, said,
‘Antidepressants work in clinical practice - everybody knows they work.’
Another critic wrote:
Dozens of clinical
trials plus decades of clinical practice plus millions of content patients
can’t be that wrong. Whatever the bias in whatever the study, common sense clearly
says: the sum of the parts attesting antidepressants’ efficacy blatantly
outnumbers the evidence showing the opposite. The use of these antidepressants
is now deeply rooted and well-established in medical society worldwide, it’s
safe, it works, and there’s no shadow of doubt about it.2
In a way, these
critics are right. Clinical experience does show that prescribing
antidepressant drugs works - and so did our meta-analyses. Patients given
antidepressants in the clinical trials we analysed showed substantial,
clinically meaningful improvement. But so did those given placebos, and the
difference between the drug response and the placebo response was not great.
The question is not whether antidepressants work, but why
they work. Is it because the chemical in the pill specifically targets
depression, or is it because of the placebo effect?
Physicians do not
sysematically prescribe placebos to their patients. Hence they have no way of
comparing the effects of the drugs they prescribe to placebos. When they
prescribe a treatment and it works, their natural tendency is to attribute the
cure to the treatment. But there are thousands of treatments that have worked
in clinical practice throughout history. Powdered stone worked. So did lizard’s
blood and crocodile dung, and pig’s teeth and dolphin’s genitalia and frog’s
sperm. Patients have been given just about every ingestible - though often
indigestible - substance imaginable. They have been ‘purged, puked, poisoned, punctured,
cut, cupped, blistered, bled, leached, heated, frozen, sweated, and shocked’,3 and if these treatments did not
kill them, they may have made them better.
Because of the
power of the placebo effect, almost anything that is believed in seems to work
for some types of medical problems. That is why the late Arthur K. Shapiro
described the history of medicine as largely the history of the placebo effect.4 It is also why clinical experience
alone cannot tell us whether a particular physical substance is an effective
treatment. Placebo-controlled trials are required to demonstrate drug efficacy
before drugs are approved for marketing.
The problem is that
many doctors are extremely reluctant to drop treatments that seem to work in
clinical practice, even when clinical trials show that these treatments are
really placebos. This problem is not confined to antidepressants. As we shall
see in Chapter 5, it is a problem that has slowed medical progress in other
areas as well.
CLINICAL PRACTICE VERSUS
CLINICAL TRIALS: THE STAR*D TRIAL
There are a number of
ways in which clinical practice is different from the clinical trials we
analysed, and these differences are often cited in efforts to dismiss our
findings. One difference is that the patients in the clinical trials knew they
might be given a placebo. As I described in Chapter 1, knowing that the pill
one is taking might be a placebo decreases its antidepressant effect.5 However, this knowledge also
reduces the effectiveness of a placebo. Placebos are more effective when people
are misled into believing that what they are getting is definitely a powerful
active treatment than when they are told that they might be getting a placebo.6 If knowing that one might be
getting a placebo decreases the response to both the placebo and the drug, then
the net effect of this knowledge on the drug-placebo difference should be zero.
Another difference
between clinical trials and clinical practice is that each of the patients in
the clinical trials we analysed was given only one kind of treatment. When a
patient seen in clinical practice fails to respond to a particular
antidepressant, psychiatrists often prescribe a different one. Sometimes the
second antidepressant works. When it doesn’t, a third might be prescribed and
then a fourth and a fifth, until one is found that works. The implicit logic
behind this practice is that different patients suffer from different chemical
imbalances. Some people may be depressed because they have a shortage of the
neurotransmitter serotonin in the brain; SSRIs, which are supposed to selectively
target serotonin, should work fine for them. Others might be lacking in
norepinephrine as well as serotonin and would best be served by an SNRI, a drug
that enhances the availability of both types of neurotransmitter. Still others
might have perfectly adequate serotonin levels, but might be lacking in
norepinephrine and dopamine; they would need a medication such as bupropion
that targets these two neurotransmitters. In other words, one has to find the
right drug for the right patient. We might call this the tailoring hypothesis,
as the task of the physician is to tailor the treatment to the particular
chemical imbalance that is causing each individual patient’s depression.
The fact that
patients sometimes improve when they are switched from one antidepressant to
another is often interpreted as evidence for the tailoring hypothesis. It also
leads to the claim that antidepressants are effective, despite the
clinical-trial evidence showing rather small effects. The particular
antidepressant given to patients in any one clinical trial may have been the
right drug for some of them, but the wrong drug for others. Maybe that is why
the drug effects do not seem very large when the average effect on all of the
patients is calculated. The clinically observed phenomenon of patients
recovering after being switched from one antidepressant to another suggests to
many doctors that finding the right drug for the right person might be the key
to antidepressant efficacy.
The clinical
experience that patients sometimes improve when a different medication is
prescribed has received confirmation from a very unusual and widely heralded
clinical trial. The study is called the Sequenced Treatment Alternatives to
Relieve Depression - or STAR*D - trial.7 It was designed to be more
representative of what happens in ‘real world’ clinical practice than are
typical clinical trials, and also to show the effectiveness of antidepressants
in the best of circumstances. A broader range of patients than are included in
normal clinical trials was accepted into the STAR*D study, there was no placebo
control group, and - most importantly to our present discussion - patients who
did not get better on the first drug were given a different treatment. Those
who were still depressed after being given a second medication were switched to
a third, and those not responding to the third were given a fourth.
As I noted in
Chapter 2, there are different ways to measure the outcome of a clinical trial.
One way is to examine how much better the patients have gotten - that is, the
average degree to which their symptoms have been reduced. Another common method
is to analyse how many of the patients have gotten better. Most often, a 50 per
cent reduction in symptoms is used as a criterion of what is called a ‘clinical
response’. One problem with this method is that most of the severely depressed
patients who show a clinical response are still depressed at the end of the
clinical trial - despite the fact that their depressive symptoms have been cut
in half.8 This is part of
the response-rate illusion that I talked about in Chapter 2. It makes a
treatment look more effective than it really is. The researchers who designed
the STAR*D trial used a much more stringent criterion. They examined the number
of patients who were in remission, meaning that they were no longer depressed
at the end of the trial.
Using this very
strict criterion of remission, the STAR*D researchers reported that 37 per cent
of the patients in the trial recovered from depression on the first medication
they were given. Another 19 per cent of the full group of patients recovered on
the second medication, 6 per cent on the third and 5 per cent on the fourth.
Altogether, 67 per cent of the patients recovered. However, the remission of
symptoms turned out to be only temporary for many - approximately half of the
patients who recovered relapsed within a year.
This is a rather
bleak picture of the effects of antidepressant treatment. In the best of
circumstances - which is what the trial was designed to evaluate - only one out
of three depressed patients showed a lasting recovery from depression, and
since there was no evaluation of what the recovery rate might have been with
placebo treatment, there is no way of knowing whether their recovery was
actually due to the medication they had been given.
Still, the study
did seem to show that switching from one antidepressant to another might make a
difference. But does it? To understand the real significance of the STAR*D
trial, it is helpful to consider a much older study.9
In 1957, a team of researchers at the University of Oklahoma School of Medicine
gave ipecac - a drug that is used to induce nausea and vomiting - to a group of
volunteer subjects. After verifying that ipecac did indeed elicit nausea and
vomiting in these subjects, the researchers then gave them a treatment to
prevent nausea and vomiting, followed by ipecac again. The question was: would
the treatment inhibit the nausea and vomiting that ipecac induces? As in the
STAR*D trial, they repeated this procedure with different medications, in this
case switching medications regardless of whether the previous one had worked.
They did this seven times, and on each occasion they measured the success of
the treatment at preventing nausea and vomiting.
The Oklahoma study
showed the same pattern of results as the STAR*D trial. Some treatments seemed
to be effective for some patients and other treatments seemed effective for
others. More than half of the subjects responded successfully to the first
treatment; 17 per cent did not respond to the first treatment, but did respond
to the second. The third treatment was successful for another 20 per cent who
had not responded to prior treatments, and by the time the sixth treatment was
tried, 100 per cent of the subjects had successfully responded to at least one
of them.
Like the STAR*D
trial, this study seemed to show that different people respond to different
medications and that the key might be finding the right treatment for the right
person - but there was a catch. None of the medications were real treatments
for nausea or vomiting. Instead, they were all placebos.
With the Oklahoma
study in mind, we can reconsider the meaning of the STAR*D data - and the
meaning of what happens in clinical practice when doctors switch medications.
The results of the STAR*D trial might have had nothing to do with switching
antidepressants. Instead, they might have been due to the placebo effect,
which, as the Oklahoma study had shown, can kick in at any time. They could
also have been due to other factors as well. Relief from depression may have
occurred because of changes in the patients’ lives, or simply because levels of
depression tend to fluctuate over time. Furthermore, these various
possibilities are not mutually exclusive. There may have been one reason for
the improvement that one patient experienced and another reason for another
patient’s improvement. The point is that the patients might have gotten better
even if they had been switched to a placebo, as was done in the Oklahoma trial,
or even if they had been given nothing at all. Similarly, when patients in
clinical practice get better after having been switched to a second
antidepressant, it may have nothing to do with the change in medication.
Instead, it could be the placebo effect kicking in - perhaps because the
patient knows that a different treatment is being used - or it could be due to
natural fluctuations in the course of their depression.
The idea of
tailoring treatment to the patient implies that the benefit of switching drugs
derives from different chemical imbalances that might be causing the
depression. But the data from the STAR*D trial contradicts this, even without
taking into account the results of the Oklahoma study. The first drug that was
given to all patients in the STAR*D study was an SSRI. SSRI stands for
‘selective serotonin reuptake inhibitor’, which means that the drug is supposed
to inhibit the reuptake of serotonin, but not of other neurotransmitters. If
this did not work, patients were given one of three different antidepressants.
Some of the non-responsive patients were switched to an SNRI, a drug that
blocks the reuptake of the neurotransmitter norepinephrine, in addition to
blocking serotonin. Others were given bupropion, which does not affect
serotonin at all, but instead inhibits the reuptake of norepinephrine and
dopamine. A third group of patients was simply switched to another SSRI, the
same type of drug to which they had not responded in the first place.
Switching
non-responsive patients from an SSRI to an SNRI led 25 per cent of them to get
better. Change from an SSRI to bupropion produced virtually the same remission
rate (26 per cent). But what of the patients who were not switched to a
different class of antidepressant, but instead were simply given another SSRI?
Twenty-seven per cent of these patients also got better - a remission rate that
is virtually identical to that produced by changing to a different type of
medication. In other words, the rate of improvement did not depend on the kind
of drug to which the patient had been switched. Simply changing from one SSRI
to another was as effective as changing to a completely different type of
antidepressant. Once again we have the strange ‘coincidence’ of virtually
identical effects produced by chemically different drugs. This indicates that
it is not the specific chemical action of the drug that alleviates the person’s
depression. Instead, it may simply be the idea of changing treatment.
The most common
criticism of our meta-analysis is the claim that the clinical trials we
analysed were flawed, and that better results would have been found if the
studies had been designed better. The trials were too short to show the real
effect of antidepressants, the critics said. The people recruited to
participate in them were not depressed enough, or they were too depressed. In
any case, they were not representative of the patients who are generally seen
in clinical practice.
Taken as a whole,
these seem like rather strange criticisms for proponents of antidepressants to
raise. These were the trials that were the basis upon which the drugs were
approved. If there was anything seriously wrong with these studies, then
arguably the drugs should not have been approved in the first place.
Furthermore, the studies were sponsored by the drug companies. One would expect
them to have been designed to maximize the benefit shown by the products in
which the companies had invested so much money.
In fact, studies
funded by drug companies usually show positive effects of their products and
worse results for the products of their competitors, whereas studies that have
been independently sponsored show results that are midway between these two
extremes. A team of researchers at the Beth Israel Medical Center in New York
have examined the outcome of clinical trials as a function of who had sponsored
them. They found that approximately 75 per cent of drug-company studies showed
favourable results for their own drugs, but only 25 per cent of them showed
favourable results for the product of a competing company. In studies that are
not sponsored by a drug company, the success rate is approximately 50 per cent.10 So it seems rather unlikely that
the industry-sponsored studies we evaluated would underestimate the drug
effect. Still, we should look at each of the alleged flaws of these clinical
trials and see whether they might have led to an underestimation of the
efficacy of antidepressants.
The Trials Were Too
Short
The clinical trials
from which efficacy is gauged are relatively short. Most of the trials we
analysed were only six weeks long, although some of them lasted eight weeks and
a few were only four weeks long. Perhaps this is not long enough to show the
real drug effect.
It is widely
believed that the drug effects of antidepressants take two to three weeks to
become evident, and that any improvement seen before then is likely to be a
placebo effect. Still, four to eight weeks should give plenty of time for a
drug effect to be seen. Furthermore, the belief that the therapeutic effects of
antidepressants are delayed is based on clinical experience, and a recent
meta-analysis of the clinical-trial data contradicts it.11 The analysis, conducted by
researchers at the University of Oxford, Yale University and the University of
Birmingham, showed that the largest decrease in depressive symptoms occurred by
the end of the first week of treatment. Although improvement continued for at
least six weeks - the typical length of a clinical trial - the rate of
improvement was less each week, and during the last couple of weeks of the
trials the difference between drug and placebo did not seem to increase at all.
The authors of the study commented that their evidence seemed to exclude ‘the
possibility that treatment response from antidepressant drugs is subject to a
period of delay’. So increasing the length of clinical trials beyond the usual
four to eight weeks is not likely to increase the drug effect.
Defenders of
antidepressants cite ‘relapse prevention’ or ‘discontinuation’ trials to
support their contention that the real magnitude of the drug effect requires
longer trials to become evident. Relapse-prevention trials are designed to
assess what happens when patients are taken off medication. They work like
this: patients who have responded reasonably well to the active medication are
either kept on the drug or switched to a placebo. Then relapse rates are
compared. Relapse-prevention trials generally show that switching patients to a
placebo leads them to get worse, compared to those who stay on the active drug.
Now there are a
number of problems with relapse-prevention studies. One is the fact that many
people who are taken off antidepressants experience withdrawal symptoms, which
in severe cases can last for months. Some of these withdrawal symptoms -
sadness, suicidal thoughts, crying spells, trouble concentrating, irritability,
anxiety, agitation and insomnia, for example - are also symptoms of depression.12 These withdrawal symptoms could
lead both patients and researchers to think that the patient has relapsed.
In addition to
being mistaken for a relapse, antidepressant withdrawal symptoms might induce a
real relapse. Imagine that you are a depressed patient who has been helped by
an antidepressant. As part of a relapse-prevention study, the drug is withdrawn
and you are given a placebo. Shortly thereafter you begin to feel sad,
depressed, anxious and agitated. These were all symptoms that you experienced
when you were depressed. In addition, you now begin to experience some new
symptoms that you have never felt before. You feel nauseous, dizzy, your vision
blurs and your muscles twitch. Not knowing that all of these are symptoms of
antidepressant withdrawal, you may think you have relapsed and become even
worse than you were before beginning medication. Misinterpreting withdrawal
symptoms as an indication of relapse could initiate a vicious cycle leading to
a genuine relapse.
A second problem
with relapse-prevention trials is related to research suggesting that the use
of antidepressants might make people more vulnerable to relapse. Patients who
are being treated with antidepressants show a specific vulnerability to relapse
that is not shown by recovered patients who have been treated without drugs.13 So the relapses suffered in
relapse-prevention trials may be due to a biological vulnerability that has
been induced by the medication in the first place. In the next chapter, where I
review the evidence behind the myth that depression is a disease caused by a
chemical imbalance in the brain, I also discuss in more detail the studies
indicating that antidepressants might make people more vulnerable to relapse.
Finally, one of the
concerns that I raised about clinical drug trials earlier in this book is that
differences in side effects might enable patients to figure out whether they
have been put in the drug group or the placebo group. This problem is
especially salient in relapse-prevention trials. Imagine that you have agreed
to be a subject in one of these studies. You have already been in the shorter
efficacy trial, and you have been told that you were in the active drug
condition. You have experienced the drug effect, and you have also experienced
some of the side effects produced by the active medication. Now you are told
that you may be continued on the active drug or you may be switched to a
placebo. Isn’t it likely that you would be able to detect at least some
difference if you were switched to a placebo, even if only a difference in side
effects? So much for double-blind! Rather than the discontinuation of
medication, it may be the patients’ knowledge that medication has been
discontinued that causes them to relapse in these studies.
There is a reason
for most efficacy trials being relatively short. As time goes on, patients tend
to drop out of them, either because the drug is not working well enough or
because of side effects. When too many patients have dropped out of a trial,
the study is considered to have been compromised and its validity is called
into question. So short-term trials are the norm. 14
Nevertheless, some
long-term efficacy trials have been conducted. These ‘continuation’ studies are
different from relapse-prevention or discontinuation trials in some very
important ways. Instead of just looking at patients who have responded to the
active drug, continuation trials also look at patients who responded to a
placebo. People who have gotten better on the drug are kept on the drug, and
those who have gotten better on the placebo are kept on the placebo. Because no
one is switched from drug to placebo or from placebo to drug, it is less likely
that the patients in continuation trials will figure out which they have been
given.
In 2002, the
prestigious Journal of the American Medical Association
published a six-month clinical trial comparing the SSRI Seroxat to a placebo to
St John’s wort, a herbal remedy that has been widely used to treat depression,
particularly in Germany, where it is a registered substance for the treatment
of mild to moderate depression.15 The first part of the study was a
short-term efficacy trial that lasted eight weeks. Those who got better were
asked to stay on whichever treatment they had been given for another 18 weeks,
bringing the total length of treatment to six months. This should certainly be
long enough to show a difference between drug and placebo - if there is one.
At the end of the
first eight weeks there was no significant difference between any of the
groups. Patients in all three groups had improved substantially, regardless of
whether they had been given the SSRI, the herbal remedy or the placebo. At the
end of six months there was still no difference between groups. Those who had
improved on the active drug maintained their improvement, but so did those who
had improved on the placebo. In fact, only one patient in the entire study
relapsed, and that was a subject who had been given the herbal remedy.
In case you think
that six months may not be long enough, note that similar results were shown in
a year-long industry-sponsored continuation trial comparing two different
antidepressants (Seroxat and imipramine) to placebo. In that study, patients
who had responded to either of the antidepressants or to the placebo during the
initial six-week trial were kept on their treatment for an additional year.
Patients in all three groups maintained their improvement. In fact, at the end
of the one-year period, those who had been treated by placebos were the least
depressed, although the differences between the groups were small and could
easily have been due to chance.16
These continuation
trials tell a very different story from that told by relapse-prevention trials.
They show that there is little difference between antidepressant and placebo
even when the clinical trial is extended over a longer period of time. Across
the eight continuation trials that have been published, 79 per cent of patients
on placebo and 93 per cent of patients on active medication remained well
throughout the treatment period. In these long-term studies, placebo treatment
was 95 per cent as effective as drug treatment. The authors of a meta-analysis
of these trials concluded that ‘the widely held - and probably erroneous -
belief that the placebo response in depression is short-lived appears to be
based largely on intuition and perhaps wishful thinking’.17
When drafting their
guidelines for the treatment of depression, NICE also reached the conclusion
that there is little difference between drug and placebo in long-term studies.
In addition to analysing short-term trials, they conducted a separate analysis
of published studies that had lasted longer. They concluded that ‘in trials
lasting eight weeks or longer, there is evidence suggesting . . . a
statistically significant difference favouring SSRIs over placebo on reducing
depression symptoms . . . but the size of this difference is unlikely to be of
clinical significance’.18
The two
meta-analyses of long-term efficacy trials were limited to data that had been
previously published, as are most meta-analyses. Nevertheless, the differences
between drug and placebo were clinically insignificant. We can only wonder
whether there are also some unpublished long-term trials that the
pharmaceutical industry has sponsored, and if so, what the results were. There
is one thing of which we can be fairly certain. Unpublished trials, where they
exist, do not show any better results than the published trials. We can be
certain of this because drug companies publish their successful studies, often
many times over. It is the unsuccessful trials that remain unpublished.
That fact that what
gets published are the trials with positive results was most convincingly shown
by a group of researchers at the Oregon Health and Science University, who
followed up on our initial analysis of the FDA data by comparing the
conclusions reached by the FDA with those reported by the drug companies in
journal articles. Of 38 drug-company clinical trials that the FDA viewed as
having positive results, all but one was published. In the same documents, the
FDA described 36 other trials as having negative or questionable results. Most
of these negative trials were not published at all, and of the few that were
published, most were described in the journal articles as showing positive
results - despite the fact that the FDA had concluded that they had not.19
The Subjects Were Not
Depressed Enough
One of the most
surprising criticisms of our most recent analysis of the FDA data is that the
patients in these trials were not depressed enough to show a strong drug
effect. Antidepressants are not effective for mildly depressed patients, the
critics noted, but they are for those who are severely depressed. This
criticism is surprising because the whole point of our article was to analyse
the extent to which the effects of antidepressants might depend on how severely
depressed the patients were to begin with. What we found was that all but one
of the trials involved patients who were classified as very severely depressed
- the most severe category of depression used by the American Psychiatric
Association and by NICE. So what is the basis for the concern that the patients
in the trials were not depressed enough to show a strong drug effect?
The most common
answer to this question is that the researchers fudge the data - that the
doctors who assess the patients’ levels of depression rate them as being more
depressed than they actually are, so that they will qualify to be enrolled in
the trial. It can be difficult to find enough patients for a clinical trial,
and the doctors may be paid for each patient they enrol. So they can be under
considerable pressure to qualify as many patients as they can.
Fudging the data is
a very serious charge. If it is true, then the real response to drug treatment
is even less than the clinical trials indicate (unless, of course, the
researchers also rate the patients as being more depressed at the end of the
trial - but why would they do that?). How seriously should we take the charge
that doctors falsify the clinical-trial data? One way of assessing the
likelihood that the researchers have fudged the data might be to consider who
it is that is levelling this charge. One of these sources is Dr Janet Woodcock,
Director of the FDA Center for Drug Evaluation and Research, who was quoted in
an interview with a reporter from USA Today as saying
that ‘patients may be rated more ill than they really are at the outset because
doctors are so eager to get them into drug trials.’20
Dr Woodcock went on
to say that ‘we [the FDA] make sure these drugs work before we put them on the
market’, but her charge that the doctors in clinical trials intentionally
distort the data undermines this claim. If the doctors are under pressure to
falsify the data at the beginning of a trial, would they not be under similar
pressure to falsify them at the end of the trial, so as to make the patients
look less ill after taking the antidepressant? Of course, the trials are
double-blind, so how would the evaluators know which patients should be
assigned lower scores? As we have seen, most doctors are able to figure out
which patients are in the drug group and which are in the placebo group,21 so the task of fudging the outcome
data would not be that difficult. These trials are the basis for drug approval.
If the data have been distorted in any way, then something is seriously wrong
with the drug approval process.
Fortunately, there
is a methodological feature of these clinical trials that makes the charge of
falsifying the initial data somewhat less problematic than it might otherwise
be - as long as those are the only data that were fudged. All of the trials we
analysed had what is called a placebo ‘run-in’ or ‘wash-out’ phase. The way
this works is as follows. After people are assessed for inclusion in the trial,
they are all given a placebo for a week or two. After this run-in period, the
patients are reassessed, and anyone who has improved is excluded from the
trial. The baseline severity scores that we used in our analyses were those taken
after the placebo run-in period; they were not the depression ratings that
doctors had made at the very beginning of the patients’ treatment. So these
were patients who were rated as still being very severely depressed after two
weeks of placebo treatment.
Of course, if the
doctors distorted the baseline scores upon which we had based our
classification of severity, they may also have fudged their second ratings of
the patients’ levels of depression. They may have fudged the initial data to
enrol the patients in the first place, and then a second time to keep them in
the trial after the placebo run-in period. But this makes the charge of fudging
the data even more troubling. If the data have been intentionally distorted at
least twice - first at enrolment and then again at baseline - then how can we
trust the outcome assessments that were made at the end of the trial?
The placebo run-in
period might itself distort the clinical-trial data, but not in the direction
that the critics of our meta-analyses contend. By getting rid of the patients
who show a placebo response to the medication that is being investigated, the
run-in should make the drugs look more effective than they actually are. This
is a potential flaw in clinical-trial methodology that biases the trials in
favour of the drug and against the placebo. It is also an ethically
questionable practice.22 Patients are
not told that they will definitely be put on a placebo for a while, nor are
they told this at the debriefing at the end of the study. So the placebo run-in
is a violation of the requirement for informed consent.
Sandra Lee and her
colleagues at St Boniface General Hospital in Winnipeg, Canada, analysed the
effect of including a placebo run-in period and excluding patients who get
better from the trial. Although placebo run-ins tended to produce larger drug
effects, the difference was not statistically significant. Part of the problem
was that there were relatively few studies that did not have a run-in phase.
This makes it very difficult for a difference to reach statistical
significance. The authors concluded that ‘from a scientific standpoint, there
is no reason to use the placebo run-in phase to eliminate placebo responders
because it is costly in terms of time and effort’. But they also predicted that
the practice of using placebo run-in periods will continue, because they do in
fact seem to produce larger drug effects.23
The Subjects Were Too
Depressed
While some critics have
complained that the patients in the clinical trials we assessed were not
depressed enough, others have argued that they were too depressed. An editorial
in Nature Reviews Drug Discovery, for example,
complained that ‘all but one trial analysed involved groups with mean initial
depression scores in the “very severe” range, limiting the strength of
extrapolations’. 24 Their suspicion
seems to be that antidepressants are more effective for severely depressed
patients, less so for either the mildly depressed or very severely depressed
groups, then becoming more effective again for the most extremely depressed.
This is a rather
labyrinthine possibility. It suggests that, like the serpentine body of the
Loch Ness monster, which rises and falls above and below the water in drawings
that you see of it, the effects of antidepressants might rise and fall below
and above the threshold of clinical significance, depending on how severely
depressed the person was to begin with.
In Chapter 2 I
described an analysis by European drug regulators of the antidepressant data
that the drug companies had submitted to them.25 Their analysis shows that the
concern raised by the editors of Nature Reviews Drug
Discovery was ill-founded. The regulatory agency data included trials of
severely depressed patients, as well as trials with moderately depressed and
very severely depressed patients, and since it included unpublished as well as
published trials, it was perfectly suited to answer the question of whether
severely depressed patients might be more responsive than those who are either
more or less depressed. As I described in the previous chapter, their study
showed a relatively small but statistically significant benefit for
antidepressant drugs compared to placebo, which is exactly what we had
concluded in our meta-analyses. More important to the issue at hand, the
European regulators found no evidence at all that responses to antidepressant
drugs were linked to severity of depression. Patients who were severely
depressed were no more likely to respond to antidepressants (or to placebos for
that matter) than those who were either moderately depressed or very severely
depressed.
The Patients Were Not
Representative
Many patients are
excluded from clinical trials. Critics of our meta-analysis have suggested that
antidepressants might work better for these patients than they do for those who
are studied in clinical trials. Let us see how plausible this concern is.
One of the main
reasons for excluding patients from clinical trials is to make it easier to
find differences between the drug and the placebo.26 There are two ways in which
excluding some patients from the trials can help accomplish this aim. One is to
eliminate those who are most likely to respond to a placebo. To accomplish this
goal, patients are excluded from clinical trials if they have only been
depressed for a short time, if they are only mildly depressed or if they
respond to placebo treatment during the placebo run-in phase.
The second way in
which excluding patients from clinical trials can magnify drug-placebo
differences is by getting rid of patients who are not likely to respond well
enough to the active drug. This is the reason for excluding patients who have
been depressed for a very long period of time, who have not responded to
previous treatments, who abuse alcohol or other drugs or who, besides being
depressed, also suffer from an anxiety or personality disorder or from various
medical disorders. Patients with these characteristics do not seem to respond
as well as others to drug treatment. The exclusion criteria used in clinical
trials make it difficult to know exactly how well antidepressants work in the
broader population of depressed patients in clinical practice, but if there is
a bias, it favours the drugs rather than the placebo, because the purpose of
excluding these patients is to increase drug-placebo differences so as to make
the drug effect easier to detect.
Most clinical
trials, including the ones my colleagues and I analysed, are conducted on
volunteers, many of whom are recruited for the trial by advertisements. Perhaps
these depressed people are not as responsive to antidepressants as the patients
seen in clinical practice. The STAR*D trial that I described earlier was
designed specifically to evaluate the effect of antidepressants on the kinds of
patients who are typically seen in clinical practice. None of the patients in
this trial were recruited by advertising. Instead, they were all patients who
sought treatment for depression in family practice or psychiatric out-patient
treatment facilities. Also, the usual exclusion criteria were relaxed, so that
a broader range of patients was evaluated. The trial did exclude patients who
had already tried antidepressants but had not responded to them, although this
exclusion should result in better response rates, not worse ones.
If the critics of
our analyses of the drug-company trials were right, the STAR*D trial ought to
have shown a larger drug response than that which is typically reported in
clinical trials. In fact, it did not.27
Instead, it showed remission and response rates very similar to those reported
in placebo-controlled clinical trials like the ones my colleagues and I had
analysed. This despite the fact that the STAR*D trial did not include a placebo
control group, a feature that has been shown to increase responsiveness to
antidepressant treatment.28 If anything,
the clinical trials my colleagues and I analysed showed better results than
trials with a more representative group of patients would have shown.
The Burden of Proof
Critics of our analyses
who claim that the trials are flawed implicitly assume that it is my task to
prove that antidepressant drugs do not work. But where does the burden of proof
lie? Earlier in this chapter I listed a few of the substances that have been
used medicinally over the centuries. Others include putrid meat, fly specks,
human sweat, worms, spiders, furs and feathers. These treatments seemed to work
in the past at least well enough for doctors and their patients to have had
confidence in them, and we cannot prove that they do not work, because they
have not been tested in clinical trials. So perhaps we should go back to using
them until appropriate trials prove their ineffectiveness. After all, as the
critic of our meta-analysis that I quoted at the beginning of this chapter put
it, ‘clinical practice plus millions of content patients can’t be that wrong’.29
The point is that
the practice of medicine should be based on empirical evidence, not on its
absence. I do not have to prove that antidepressants do not work. Instead, it
is the job of the drug companies to prove that they do work. If the trials were
flawed, then clinically significant differences between antidepressant and
placebo have not been established for most patients. If the trials were not
flawed, the data indicate that ‘clinically significant differences between
antidepressant and placebo have not been established for most patients’ (quoted
from the previous sentence). Either way, the objective of proving the
effectiveness of antidepressant medication has not been met.
Furthermore, it is
not enough to show that antidepressants are statistically better than placebos.
For drugs to be marketed and for patients to be exposed to their side effects
and other risks, the benefit over placebos needs to be shown to be clinically
significant. In the files I obtained from the FDA, agency officials
acknowledged the failure to show a clinically significant benefit for the drugs
they have approved, saying instead that they demonstrate ‘proof in principle’
of the effectiveness of the drugs. What proof in principle means is simply that
the drugs are statistically superior to placebos, even if the difference is
vanishingly small. In approving Cipramil (Celexa in the US), the Director of
the FDA Division of Neuropharmacological Drug Products summarized the situation
as follows:
The size of [the]
effect, and more importantly, the clinical value of that effect, is not
something that can be validly measured, at least not in the kind of experiments
conducted. Accordingly, substantial evidence in the present case, as it has in
all other evaluations of antidepressant effectiveness, speaks to proof in
principle of a product’s effectiveness.
And the Team Leader for Psychiatric Drug Products
commented, ‘While it is difficult to judge the clinical significance of this
difference, similar findings for other SSRIs and other recently approved
antidepressants have been considered sufficient to support the approvals of
those other products.’ In other words, the ‘clinical value’ of an
antidepressant drug is just not part of the FDA’s criteria for approving it.
But do the
clinical-trial data submitted to the FDA even establish proof of principle?
Recall that the rather small differences found between drug and placebo in the
trials submitted to the FDA could have been due to the breaking of blind on the
basis of perceived side effects. It may simply be evidence of an enhanced placebo
effect, rather than a true drug effect. As I noted in Chapter 1, once side
effects are taken into account, the difference between SSRI and placebo is not
even statistically significant.30
Although the FDA
does not consider the clinical value of an antidepressant when approving it,
NICE did take clinical significance into account when drafting their clinical
guidelines. More recently, European regulators, in their ‘apologia’ following
the publication of our most recent meta-analysis, acknowledged that clinical
relevance should be a consideration in drug approval, and they tried -
unsuccessfully in my opinion - to show retrospectively that the data
demonstrate clinical as well as statistical significance. This is a welcome
change, and it is one that I hope will come to be adopted as official policy.
SUBSEQUENT TRIALS SHOW
DIFFERENT RESULTS
By and large, the drug
companies reacted reasonably well to the various analyses that we conducted on
their data. Two of the companies actually hired me for brief consultations.
They were not at all surprised by our findings - they knew it all along, and
they wondered what all the fuss was about. In fact, the reason they hired me
was that the placebo effect was so strong. They were finding it difficult to
demonstrate drug effects and were hoping to find a way to identify in advance
those people who were likely to respond to placebo treatment. If they could
accomplish this, they could exclude the ‘placebo responders’ from clinical
trials, and with these people excluded it might be easier to show a drug
effect.
GlaxoSmithKline
(GSK), the manufacturer of Seroxat, seems to be the only drug company that has
commented publicly on our meta-analysis.31 We had limited ourselves to analysing the data
submitted to the FDA, which included 16 trials of Seroxat. They have conducted
more than 170 trials, they said; so the 16 trials we had analysed were just a
small proportion of the studies they had done.
As I described in
Chapter 2, following a lawsuit in which GSK was accused of hiding some of the
negative clinical-trial data, the company was required to maintain a website
that reports the results of all of its studies of Seroxat. I have examined the
studies that GSK has put on its website. Most of them do not have placebo
control groups. They are irrelevant to the argument of whether SSRIs are much
better than a placebo for the treatment of depression. But the GSK website also
reveals some placebo-controlled ‘post-marketing’ studies - that is, studies
that were conducted after the FDA had approved Paxil (as Seroxat is called in
the US). Because our analysis was limited to the FDA data set, we had not
included these later studies. Do they tell a different story?
Coincidentally,
researchers at a World Health Organization (WHO) centre, the University of
Verona in Italy and the Nagoya City University in Japan had already analysed
all of the placebo-controlled antidepressant trials on GSK’s website, and
published their results at just about the same time that we published our
analysis of the FDA data. They found 40 placebo-controlled studies of Seroxat
for the treatment of major depression, including the 16 that had been sent to
the FDA. The results of their analysis of these 40 studies were virtually
identical to the results of our analysis of the studies that had been sent to
the FDA. We had found that placebos were 82 per cent as effective as
antidepressants in treating major depression. In the later study, which
included the post-marketing studies on GSK’s website, the placebo was 83 per
cent as effective as the real drug.32
OIL AND WATER OR GUNS AND
KNIVES?
There is yet another
possibility. The general assumption is that the effect of a drug adds to the
placebo effect, so that the total improvement that patients experience is the
drug effect in addition to the placebo effect. This assumption is implicit in
the design of placebo-controlled clinical trials, in which the drug effect is
assessed as the difference between the response to the drug and the response to
the placebo. Anne Harrington, an historian of science at Harvard University and
the London School of Economics, calls it the oil-and-water hypothesis.
However, drug
effects and placebo effects may not be additive like oil and water.33 They could be independent, so that
the response would be the same even if there were no placebo effect at all.
Instead of being like oil and water, drugs and placebos may be like guns and
knives. Shooting someone will leave the victim just as dead as shooting him and
stabbing him, and the fact that stabbing a person leaves her just as dead as
shooting her doesn’t mean that shooting is ineffective. Similarly, it is
possible that the effects of antidepressants are real and that they are large,
despite the small size of the difference between drug and placebo. Maybe
depressed patients would get better when given antidepressants even if they
were given the drug without knowing it. In other words, the response to
antidepressant medication could be a true drug effect that is masked by the
placebo effect in clinical trials.
A number of studies
with healthy volunteers have tested whether various drug and placebo effects
are additive. These studies use an experimental method called the ‘balanced
placebo design’.34 Figure 3.1 shows how this type of study is done. Half
of the subjects in the study (those in groups A and B in the figure) are told
that they have been assigned to the drug group. The others (groups C and D) are
told that they are in the placebo group. Sometimes this information is true;
sometimes it is not. The subjects in group A have been given a drug and know
that they have been given the drug. Those in group B think they have been given
the real drug, but have actually received a placebo. In group C subjects have
been given a drug, but think they have just taken a placebo. Group D is a
control group that shows what happens when people are given nothing at all, not
even a placebo.
Figure 3.1 The balanced placebo experimental design
The balanced
placebo design makes it possible to assess whether or not drug and placebo
effects are additive like oil and water, or whether the placebo merely masks
effects that are really being produced by the drug. If drug and placebo effects
are additive, subjects who are knowingly getting the real drug (those in group
A) ought to improve more than those who are either getting a placebo (group B)
or getting the drug without knowing it (group C). On the other hand, if there
is a real drug effect that is being obscured by the placebo effect - that is,
if the two effects are not additive - then people given the drug without
knowing it (group C) ought to do better than those who do not get drug or
placebo (group D), even if drug and placebo effects (groups B and C) are
equivalent.
Studies using
methods like the balanced placebo design indicate that some drug effects are
additive and some are not. For example, drug effects and placebo effects add
together to produce a stronger combined effect when assessing the effects of
caffeine on alertness or the effects of morphine on pain.35 But not all drug and placebo
effects add together in this way. Sometimes, some rather strange interactions
are found. For example, the tenseness or jitteriness that some people feel when
they drink too much coffee only happens when people consume caffeine and know
that they are consuming caffeine (group A in the figure). Caffeinated coffee
does not make people jittery when they think the coffee is decaffeinated (group
C), and placebo caffeine does not make them jittery either (group B).
There is some
indirect evidence suggesting that the antidepressant drug effect - if there is
one - and the placebo effect are additive. As I described in Chapter 1,
patients in clinical trials in which there is no placebo condition improve
significantly more than patients in placebo-controlled trials. In the
placebo-controlled trials, patients are told that they might be given a placebo,
and this knowledge diminishes the effect of taking the drug.36
Still, the pure drug effect of antidepressants has not been assessed in a
balanced placebo study, and it is possible that a test of this sort would
reveal a larger effect than that shown in typical clinical trials.
Given that
possibility, you might think that the drug companies would be eager to try a
study of this sort. In fact, they are not. I have been campaigning for a direct
test of the additivity hypothesis for years,37 but the drug companies do not seem
to be inclined to sponsor a trial that could accomplish this goal, or if they
have, the results have not been published. Although the results of such a test
might vindicate antidepressants and show that they work independently of the
placebo effect, they could also confirm that antidepressants are little more
than active placebos. Why take the chance?
In the process of
writing this book and responding to the various concerns raised by critics of
our meta-analysis, I have come across data of which I had not previously been
aware - some of which had not been published at the time my colleagues and I
wrote up our meta-analysis for publication. These data indicate that we were
overcautious in our interpretation of the data we had received from the FDA.
Until now, I have
argued that the therapeutic effects of antidepressants are small, that
clinically meaningful benefits may be limited to a
small subset of patients, and that the effects of the drugs may
not be due to their specific chemical composition - that instead of being
active therapeutic agents, antidepressants may instead be active placebos. The
process of addressing the objections of my critics has steadily driven me to a
set of much more far-reaching conclusions. I have always had my doubts about
the commonly held view that depression is a brain disease - a chemical
imbalance that is reversed by antidepressant medication. Now, considering all
of the data together, I have come to believe that the chemical-imbalance theory
is completely implausible.
In the next chapter
I examine the data behind the chemical-imbalance theory. Others have argued
that these data provide only weak support for this conventional view.38 I go a step further. I do not
think the data are weak at all. They are in fact rather strong. But rather than
supporting the chemical-imbalance theory of depression, they contradict it. It
now seems beyond question that the traditional account of depression as a
chemical imbalance in the brain is simply wrong.
The Myth of the
Chemical Imbalance
Depression, we are told
over and over again, is a brain disease, a chemical imbalance that can be
adjusted by antidepressant medication. In an informational brochure issued to
inform the public about depression, the US National Institute for Mental Health
tells people that ‘depressive illnesses are disorders of the brain’ and adds
that ‘important neurotransmitters - chemicals that brain cells use to
communicate - appear to be out of balance’. This view is so widespread that it
was even proffered by the editors of PLoS [Public
Library of Science] Medicine in their summary that
accompanied our article. ‘Depression,’ they wrote, ‘is a serious medical
illness caused by imbalances in the brain chemicals that regulate mood’, and
they went on to say that antidepressants are supposed to work by correcting
these imbalances.
The editors wrote
their comment on chemical imbalances as if it were an established fact, and
this is also how it is presented by drug companies. Actually it is not.
Instead, even its proponents have to admit that it is a controversial
hypothesis that has not yet been proven.1 Not only is the chemical-imbalance
hypothesis unproven, but I will argue that it is about as close as a theory
gets in science to being disproven by the evidence.
To understand the
chemical-imbalance theory, it will be helpful to first review some basic
aspects of how the brain functions. The human brain contains about 100 billion
nerve cells called neurons. Each neuron is like an electrical wire with many
branches. When a neuron fires, electrical impulses travel along its length from
one end to the other. When an impulse reaches the end of a branch, it may
stimulate the next neuron, influencing whether or not it fires.
Neurons do not
actually touch each other. Rather, there are fluid-filled gaps, called
‘synapses’, between the end of one neuron and the beginning of another. The
brain’s electrical impulses are not strong enough to span these gaps. So how
can a neuron’s electrical impulse influence the firing of a neighbouring nerve
cell? It does so by means of chemicals called ‘neurotransmitters’, which are
manufactured by neurons and convey information across the gaps between them
(that is, the synapses). Serotonin is one of the neurotransmitters through
which one neuron influences the firing of another. Others include
norepinephrine and dopamine. There are many other kinds of neurotransmitters,
but these three - and especially serotonin - have been hypothesized to be
involved in depression.
After
neurotransmitter molecules have influenced the firing of a receiving neuron
(more technically called a postsynaptic neuron), some of them are destroyed by
enzymes in the synaptic cleft (the synapse), some are reabsorbed by the sending
presynaptic neuron in a process that is called ‘reuptake’, and the rest remain
in the space between the two neurons. The chemical-imbalance hypothesis is that
there is not enough serotonin, norepinephrine and/or dopamine in the synapses
of the brain. This is more specifically termed the monoamine theory of
depression, because both serotonin and norepinephrine belong to the class of
neurotransmitters called monoamines.
INVENTION OF THE
CHEMICAL-IMBALANCE THEORY
The 1950s gave rise to
the Korean War, the Cuban revolution, the Hungarian revolution, the hydrogen
bomb, beatniks - and antidepressants. Two different types of antidepressants
were developed during this decade, and in both cases the discovery of apparent
antidepressant effects was serendipitous. The story of how antidepressants were
discovered - or perhaps ‘invented’ might be a better word - and how they led to
the development of the chemical-imbalance theory is rather convoluted.2 But it is worth examining, as there
are important lessons to be learned from it. From the beginning, the
chemical-imbalance theory was based on weak and contradictory evidence, and
data contradicting it were simply ignored. This is a pattern that was to be
repeated. A half-century of research has produced data indicating that the
chemical-imbalance theory must be wrong. Yet it remains the most popular
explanation of depression, and most of the data contradicting it continues to
be ignored.
The first
antidepressant was a drug called iproniazid that had been produced in 1951 from
leftover German rocket fuel by the pharmaceutical company, Hoffmann-La Roche,
and was being used for the treatment of tuberculosis. As is true of most
medications, clinical trials of iproniazid revealed various side effects, but
not all of these effects were negative. Some patients reported an increased
sense of vitality and well-being. At first, this was merely considered a side
effect and was ignored, but it was not long before clinicians in France and the
United States began trying iproniazid as a treatment for depression.
In 1957, Nathan
Kline, Harry Loomer and John Saunders, at the Rockland State Hospital in
Orangeburg, New York, reported the first influential assessment of iproniazid
as a ‘psychic energizer’ on non-tubercular psychiatric patients, some of whom were
suffering from depression. According to their report, about two-thirds of
patients showed a ‘measurable response’ to the drug. This is about the same
response rate that is reported for clinical trials of antidepressants today,
and as we have seen, most if not all of that response can be attributed to the
placebo effect. But the study conducted by Kline and his colleagues did not
include a placebo control group - placebo-controlled clinical trials had not
yet become fashionable - and the antidepressant effect was assumed to be a
biological response to the drug. In less than one year, more than 400,000
depressed patients had been treated with iproniazid, and the first
antidepressant had been born.3
One year after
Kline and his colleagues reported the effect of iproniazid on psychiatric
patients, a Swiss psychiatrist named Roland Kuhn published an article in the American Journal of Psychiatry on the antidepressant
effects of the tricyclic drug imipramine. Like iproniazid, the discovery of
imipramine as an antidepressant was accidental. Kuhn was studying the effect of
imipramine on psychosis, not depression, but three of his patients who had been
diagnosed with psychotic depression showed marked improvement, and Kuhn went on
to try imipramine on other depressed patients.4 He reported that a high percentage
of his patients recovered completely, usually within two to three days of being
given the drug.5 This is quite
remarkable, given the subsequent widespread belief that it takes weeks for
antidepressants to take effect.
It is important to
note that claims for the effectiveness of iproniazid and imipramine were not
based on placebo-controlled clinical trials. Instead, they were based on
clinical impressions.6 In ‘discovering’
the antidepressant effects of imipramine, Kuhn did not even use precise
measurement, rating scales or statistics. His claim was that precise
measurement led to stagnation rather than progress in medicine, and he
preferred to rely on his extensive medical experience and ‘artistic
imagination’ instead.7
Despite the
weakness of the data, the idea that iproniazid and imipramine were effective
antidepressants came to be widely accepted. This is not really surprising, in
the context of the times. In the 1950s and 1960s, the power of the placebo
effect was just beginning to be recognized, and placebo-controlled clinical
trials were rare. New treatments were often accepted on the basis of clinical
experience and the testimony of experts in the field.
Iproniazid and
imipramine seemed to work as antidepressants, but how did they achieve their
effects? It would be another decade before the chemical-imbalance theory was
launched. In 1965, Joseph Schildkraut at the National Institute of Mental
Health in Washington, DC, published a groundbreaking paper in which he argued
that depression was caused by a deficiency of the neurotransmitter
norepinephrine in the gaps between neurons in the brain.8 Two years later Alec Coppen, a
physician at West Park Hospital in Surrey, published another version of the
chemical-imbalance theory. His version differed from Schildkraut’s in that it
put most of the blame on a different neurotransmitter, emphasizing serotonin
rather than norepinephrine as the neurotransmitter that was lacking.9
What was the
scientific basis for these chemical-imbalance theories? As I noted above,
norepinephrine and serotonin are now known to be neurotransmitters - chemicals
that transmit nerve impulses from one neuron to another. But in the 1950s
knowledge of neurotransmission was sketchy at best. The presence of
norepinephrine in the nervous system was not demonstrated until 1954, and
evidence that dopamine functions as a neurotransmitter was not reported until
1958. As late as 1960 the idea that neurotransmission is largely chemical in
nature, though advocated by a group of largely British scientists, was not yet
widely accepted.10
Against this
backdrop, researchers reported evidence that iproniazid, the antitubercular
drug that was to become the first antidepressant, might increase norepinephrine
and serotonin levels in the brain. How did it have this effect? Recall that
some of the neurotransmitter molecules released by a neuron are destroyed by
enzymes in the synaptic cleft between the sending presynaptic neuron and the
receiving postsynaptic neuron. When the neurotransmitter is a monoamine - like
norepinephrine and serotonin - this process is called monoamine oxidase (MAO).
As early as 1952 researchers at the Northwestern University Medical School in
Chicago reported that iproniazid inhibited the oxidation of monoamines.11 This meant that iproniazid was a
monoamine oxidase inhibitor - an MAOI, as this type of antidepressant is
commonly called.
Here then is the
logic behind the first version of the chemical-imbalance theory. Iproniazid is
a monamine oxidase inhibitor - it inhibits the oxidation of norepinephrine and
serotonin in the synapses, thereby leaving more of these neurotransmitters
available in the brain. When depressed people take iproniazid, they get better.
Therefore insufficient norepinephrine and/or serotonin causes depression.12
There was a problem
with this first version of the biochemical theory of depression. Iproniazid was
not the only drug that had been reported to be effective as an antidepressant.
Imipramine, the drug that had been tested by the Swiss psychiatrist Roland
Kuhn, seemed to have similar effects. But imipramine is not an MAOI; it does
not inhibit the destruction of neurotransmitters in the synapse. So if
antidepressants worked by inhibiting monoamine oxidase, why was imipramine
effective? How could its apparent effectiveness be reconciled with the
chemical-imbalance theory?
The answer is that
there are two ways in which neurotransmitter levels might be increased. One is
to inhibit their destruction after they have been released into the synaptic
gap. That is how MAOIs are supposed to work. Recall, however, that after a
neurotransmitter is released, some of its molecules are reabsorbed by the
presynaptic neuron that released them in a process that is called ‘reuptake’.
Blocking this reuptake process should also increase the level of neurotransmitters
in the brain. In 1961, Julius Axelrod, who later received the Nobel Prize in
Medicine for his work on the release and reuptake of neurotransmitters,
reported that imipramine, as well as a few other drugs, inhibited the reuptake
of norepinephrine in cats. Two years later he reported that these drugs also
inhibited the reuptake of serotonin.13
Axelrod’s discovery
provided an answer to the question of why imipramine might alleviate depression,
even if it did not inhibit the destruction of neurotransmitters in the brain.
With the problem of imipramine solved, the chemical-imbalance theory seemed to
work. Two different types of drugs relieve depression, the theory went, and
although they work in different ways, the net result is the same. One drug
blocks the destruction of norepinephrine and serotonin. The other inhibits
their reuptake. In either case, the result should be more of these
neurotransmitters available in the brain.
But that was only
one half of the logic behind the chemical-imbalance theory. The other half came
from studies of reserpine, a drug that was extracted from Rauvolfia
serpentina or the Indian snakeroot plant, which had historically been
used to treat snakebite, hypertension, insomnia and insanity. In studies of
animals, reserpine was reported to induce sedation and to decrease brain levels
of norepinephrine, serotonin and dopamine. Clinical reports indicated that some
people became severely depressed when taking reserpine .14
Putting these two findings together, it seemed likely that reserpine made
people depressed because it decreased neurotransmitter levels.
When the reserpine
studies are added to the antidepressant studies, the logic behind the
chemical-imbalance theory begins to look compelling. Drugs like reserpine that
decrease monoamine neurotransmitters make people depressed. Drugs that increase
these neurotransmitters by one means or another relieve their depression.
Hence, depression is due to a monoamine deficiency.
THE EMPIRICAL BASIS OF
THE CHEMICAL-IMBALANCE THEORY
The monoamine
hypothesis made a good story. There is only one problem with it. It does not
really fit the data. It didn’t fit the data that were available in the 1960s
when the theory was developed, and it does not fit the data that have
accumulated since then.
The Myth of
Reserpine-Induced Depression
Part of the initial
argument for the chemical-imbalance hypothesis was that reserpine supposedly
decreases the availability of monoamines and thereby makes people depressed.
But does it? Like the articles indicating that iproniazid and imipramine
functioned as antidepressants, the conclusion that reserpine makes people
depressed was based on clinical reports, rather than controlled trials.
In 1971 these
clinical reports were carefully re-evaluated and shown to be much ado about
nothing. Only 6 per cent of the people given reserpine developed clinical
depression, even after taking the drug for long periods of time. This means
that 94 per cent of the patients did not become depressed when given reserpine.
Furthermore, of the small percentage who did become depressed, most had
suffered from depression before.15 Their new episodes of depression
may have had nothing at all to do with reserpine. They may simply have
relapsed, as do many depressed people after recovering from depression.16 So much for the claim that reserpine
causes depression.
The re-examination
of the clinical reports showing that most people who were given reserpine did
not become depressed was not published until 1971, a few years after the
chemical-imbalance theory had been popularized by Schildkraut and Coppen. But a
decade before their influential articles were written, there had been a
carefully controlled clinical trial on the effects of reserpine on mood.17 Far from confirming the belief that
it made people depressed, the study seemed to show the reverse. Rather than
making healthy people depressed, reserpine seemed to make depressed people
better. As described by Michael Shepherd, the senior author of the study, in
1956:
When we began using
reserpine at the Maudsley Hospital less than two years ago there were very few
reliable accounts of its use in the treatment of neuropsychiatric conditions
and almost no controlled clinical studies. Dr D. L. Davies and I therefore
conducted a clinical trial on a mixed group of out-patients, the majority of
whom were suffering from anxiety and depressive reactions. The patients were
given either reserpine, prescribed as Serpasil in a dose of 0.5 mg. by mouth
twice daily, or a seemingly identical placebo, for a period of six weeks. The
two substances were allotted by the hospital pharmacist who employed a random
method and alone knew the nature of the drug dispensed to each patient; the
usual crop of placebo reactions which was observed during the weekly examinations
quickly demonstrated the importance of such precautions in testing patients of
this type. At the end of the sixth week the response of each patient was
estimated by rating scales which were completed by doctors and patients. The
results demonstrated a clear-cut difference in favour of those patients treated
with reserpine.18
In other words, the drug that was supposed to
induce depression, according to the chemical-imbalance theory, actually
relieved it, when it was carefully evaluated as a possible treatment in a
placebo-controlled study.
How is it that the
chemical-imbalance theory was proposed and so widely accepted, when the only
controlled scientific study that had been done indicated that one could relieve
depression, rather than induce it, by giving patients a drug that increases
brain levels of monoamines? David Healy, in his comprehensive treatise on the
history of antidepressants, provides an answer to this question.19
The study was simply ignored, despite having been published in The Lancet, one of the world’s most prestigious medical
journals.
Shepherd’s clinical
trial of reserpine was not the only evidence that was ignored by proponents of
the chemical-imbalance theory. Arguing strongly for this theory, Schildkraut
and Coppen cited the work of Julius Axelrod, the Nobel Prize-winning scientist,
who a few years earlier had discovered that imipramine inhibited the reuptake
of norepinephrine and serotonin - the neurotransmitters that are supposed to be
the causes of depression. What Schildkraut and Coppen failed to mention when
arguing for their monoamine theory of depression was that Axelrod had found
other drugs that inhibited the reuptake of these neurotransmitters, and one of
these other drugs was reserpine - the drug that was supposed to induce
depression, according to the chemical-inbalance argument.
Schildkraut and
Coppen should have known that reserpine inhibited the reuptake of
norepinephrine and serotonin, because it was reported in the very same articles
in which the effects of imipramine had been reported. And they could not just
have overlooked this detail, because it was the first thing that was mentioned
in these articles. The summary at the beginning of the very first article on
the subject begins with the sentence, ‘Reserpine, amphetamine, imipramine, and
chlorpromazine markedly reduced the uptake of circulating H3-norepinephrine.’20
In a sense, it
seems strange that Schildkraut and Coppen omitted this critical fact, since it
might have explained Michael Shepherd’s findings that reserpine functioned as
an antidepressant when given to patients in a clinical trial. But acknowledging
that reserpine had the same effect as imipramine on the reuptake of
neurotransmitters would have demolished one of the two empirical pillars of the
theory, the supposed fact that reserpine decreased levels of norepinephrine and
serotonin and thereby caused depression.
What Happens When
Serotonin Is Reduced
When Schildkraut
introduced the monoamine theory of depression, he admitted that there was
little direct evidence for it. Instead, it was based on the supposed effectiveness
of antidepressant medication and the mistaken belief that reserpine makes
people depressed. Schildkraut acknowledged that: ‘Most of this evidence is
indirect, deriving from pharmacological studies with drugs such as reserpine,
amphetamine and the monoamine oxidase inhibitor antidepressants which produce
affective changes.’21 A half-century
has passed since his chemical-imbalance theory of depression was introduced,
and the presumed effectiveness of antidepressants remains the primary evidence
in its support. But as we have seen, the therapeutic effects of antidepressants
are largely due to the placebo effect, and this pretty much knocks the legs out
from under the biochemical theory.
During the last 50
years researchers have tried to find more direct evidence for the monoamine
theory of depression, but by and large they have failed. Instead of finding
confirmation, much of the evidence they have found is contradictory or runs
counter to the theory.22 The most telling example involves
techniques for rapidly reducing the amount of serotonin, norepinephrine or
dopamine in the brain. The reasoning behind these studies is that if a
deficiency of these neurotransmitters in the brain causes depression, then
lowering their levels ought to induce depression in people who are not
depressed. The evidence shows that it does not.
There are a few
substances that can reduce serotonin, norepinephrine and/or dopamine rapidly
and substantially, reducing them to levels thought to be lower than those of
depressed patients.23 That is what reserpine was
supposed to do and, as we have seen, it did not cause depression - despite the
early clinical impression that it did. Other substances have been used in later
studies, the most common of which are amino-acid mixtures that lack the
essential amino acids needed by the body to produce these neurotransmitters.
For example, having people drink a beverage that is rich in amino acids, but
does not contain tryptophan (the amino acid needed to produce serotonin),
lowers their serotonin levels within a couple of hours.
Neurotransmitter
depletion has been attempted in at least 90 studies and has been the subject of
a number of systematic reviews, the most recent and comprehensive of which is a
metaanalysis conducted by a research team at the University of Amsterdam.24 The hypotheses of these studies
were based on the premise that lowered monoamine levels cause depression, in
which case depletion of these neurotransmitters ought to trigger depression in
people who are not depressed. Here is what actually happens. Experimentally
lowering the level of available serotonin, or of norepinephrine and dopamine,
in healthy volunteers who have never been depressed does not affect their mood
in the slightest.
There is only one
group of research subjects in whom rapid depletion of serotonin sometimes
produces clinical depression. These are depressed patients in remission who are
currently taking SSRIs. About half of these patients relapse when serotonin is
depleted. Note that this only happens if they are still taking antidepressant
medication. If they have stopped medication, depleting serotonin may have a
small transient effect on their mood, but it does not make them depressed
again. And the relapse occurs only if the drug they are on is one that is
supposed to enhance the availability of serotonin in the brain. Lowering
serotonin levels does not cause depression in people who are currently taking a
type of antidepressant that does not affect serotonin.
It is hard to know
what to make of the finding that serotonin depletion depresses some people who are
currently taking drugs to enhance serotonin. It could be that SSRIs induce a
temporary biological vulnerability to serotonin depletion. On the other hand,
it could be a ‘nocebo’ effect, which is a negative effect induced by a placebo.
In either case, the results of decades of neurotransmitter-depletion studies
point to one inescapable conclusion: low levels of serotonin, norepinephrine or
dopamine do not cause depression. Here is how the authors of the most complete
meta-analysis of serotonin-depletion studies summarized the data: ‘Although
previously the monoamine systems were considered to be responsible for the
development of major depressive disorder (MDD), the available evidence to date
does not support a direct causal relationship with MDD. There is no simple
direct correlation of serotonin or norepinephrine levels in the brain and
mood.’25 In other words,
after a half-century of research, the chemical-imbalance hypothesis as
promulgated by the drug companies that manufacture SSRIs and other
antidepressants is not only without clear and consistent support, but has been
disproved by experimental evidence.
If the evidence for
a chemical imbalance as a cause of depression is so weak, why was the theory so
widely accepted and why do people still cling to it? Certainly the serotonin
story was a good one - everyone could grasp it. Serotonin was good; lack of
serotonin was bad. The evidence did not really fit the story, but few doctors
have the time to carefully sift through the data. They see drug-company
advertising in their professional journals, and they read the labelling
information approved by the FDA and other regulatory agencies. At medical
conferences they meet drug-company representatives, who present the company’s
interpretation of the evidence, an interpretation that is consistent with the
simple chemical-imbalance theory. The theory may be wrong, but it certainly
helps to sell antidepressant drugs, and until recently doctors have had little
reason to question it.
Too Many
Antidepressants Work Too Well
When the
chemical-imbalance theory was introduced more than 40 years ago, the main
evidence in favour of it was the contention that antidepressants, which were
thought to increase the availability of serotonin and/or other
neurotransmitters in the brain, seemed to be effective in the treatment of
depression. As Alec Coppen wrote in 1967, ‘one of the most cogent reasons for
believing that there is a biochemical basis for depression or mania is the
astonishing success of physical methods of treatment of these conditions.’26 The situation has not changed very
much since then. People still cite the supposed effectiveness of
antidepressants as fundamental support for the chemical-imbalance hypothesis.
This theory, they say, is supported by ‘the indisputable therapeutic efficacy
of these drugs’.27
Although the
therapeutic effectiveness of antidepressants seemed ‘astonishing’ 40 years ago
and still seems ‘indisputable’ to many people today, it is, in fact, an
illusion. As I have shown earlier in this book, the difference between the
effects of antidepressants and placebos is clinically insignificant, despite
clinical-trial methods that ought to enhance it. But strangely enough, it is
not the ineffectiveness of antidepressants that seals the fate of the
chemical-imbalance theory. Rather, it is their effectiveness. The problem is
that too many different types of antidepressants work too well for the theory
to make physiological sense.
Different types of
antidepressants are supposed to work by different means. SSRIs (selective
serotonin reuptake inhibitors) are supposed to increase serotonin levels. NDRIs
(norepinephrine dopamine reuptake inhibitors) are supposed to increase
norepinephrine and dopamine, rather than serotonin. These two types of
antidepressants are supposed to be ‘selective’, affecting the designated
neurotransmitters without affecting the others. The strange thing is that these
two types of antidepressants are equally effective in treating depression.
Using data reported in a recent meta-analysis that was published in The Lancet, I have calculated that 60 per cent of patients
respond to SSRIs and 59 per cent of patients respond to NDRIs.28
‘So what’s wrong
with that?’ you might ask. Maybe some people do not have enough serotonin and
others do not have enough norepinephrine or dopamine. The problem is that
besides the remarkable coincidence of the response rates being virtually
identical, we have also accounted for too many people. Adding together 60 per
cent and 59 per cent, we get 119 per cent, which is 19 per cent too much.
That may not be a
big problem. It could be that some depressed people do not have a chemical
imbalance and would respond to anything - even a placebo - whereas others get
better only when you give them the right medication. But if this were true,
then switching people to a different type of medication ought to make a
difference. I reviewed the evidence on switching from one antidepressant to
another in Chapter 3. Some people who have not responded to a particular
antidepressant do indeed get better when you switch them to another antidepressant.
The problem for the chemical-imbalance theory is that it doesn’t matter what
the other antidepressant is. In the STAR*D trial, which was designed to be
especially representative of what happens in real-world clinical practice,
switching unresponsive depressed people from one SSRI to another was exactly as
effective as switching them to an NDRI. When depressed people who did not
respond to an SSRI were given an NDRI, 26 per cent of them got better, but 27
per cent of them also got better if the drug they were switched to was just
another SSRI.29 Once again we
have the remarkable coincidence of identical effects from different drugs.
The STAR*D trial is
not alone in finding that all antidepressants are created equal. In
meta-analyses of head-to-head comparisons of different antidepressants,
statistically significant differences are occasionally found, but these tend to
be very small - smaller even than the clinically insignificant drug-placebo difference
that we have found in our meta-analyses of the FDA data set.30 If the difference between
antidepressant and placebo is small, the differences between one antidepressant
and another are virtually non-existent. As the authors of one of these analyses
concluded, ‘overall, second-generation antidepressants probably do not differ
substantially for treatment of major depressive disorder’.31
Furthermore, when small differences are found, they may be at least partly due
to the biases in the studies. As I noted in Chapter 3, studies funded by a drug
company generally report positive results for that company’s drug, and negative
results for drugs manufactured by competitors.32
The most common
interpretation of the failure to find clinically meaningful differences between
the effects of different antidepressants is that ‘choosing the agent that is
most appropriate for a given patient is difficult’.33
This presupposes that there is a right drug for a particular patient, but the
data on which this conclusion is based suggests exactly the opposite. Let us
suppose that some patients have a serotonin deficiency, others a norepinephrine
deficiency, and still others a shortage of both neurotransmitters in their
brain. It seems a rather remarkable coincidence that the number of people
suffering from all three types of imbalance would be exactly the same. But even
this level of improbability underestimates how subversive the equivalence data
are for the chemical-imbalance hypothesis. If some people suffer from a
shortage of serotonin, others from a shortage of norepinephrine, and still
others from both, then SNRIs - which are designed to increase the availability
of both neurotransmitters - should provide a clinical benefit to substantially
more people than either of the more selective treatments. But they do not. The
effects of SNRIs are not much better than the effects of SSRIs, or than drugs
like bupropion that do not affect serotonin at all.34
It is difficult to
even imagine a convincing biochemical explanation of the virtual equivalence of
different types of antidepressants. The tailoring hypothesis (the idea that the
right antidepressant has to be found for each patient’s particular chemical
imbalance) certainly does not work. There are just too many drugs that produce
response rates of 50 per cent or better in the treatment of depression, and
these are not limited to antidepressants. Other drugs that work better than
placebos in treating depression include sedatives, stimulants, opiates,
antipsychotic drugs and the herbal remedy St John’s wort.35 I don’t think anyone would argue
that there is a common chemical mechanism by which all of these very different
drugs work. There may indeed be different subtypes of depression, and it is plausible
to suppose that different treatments might be effective for these different
subtypes of the disorder. But the proportion of people having each subtype of
depression cannot add up to more than 100 per cent. Yet that is exactly what
the data seem to tell us, if we assume that the tailoring hypothesis is right.
Although the
tailoring hypothesis does not fit the data, there is another hypothesis that
works just fine. It is the idea that antidepressants are active placebos. That
is, they are active drugs, complete with chemically induced side effects, but
their therapeutic effects are based on the placebo effect rather than their
chemical composition. Their small advantage in clinical trials derives from the
production of side effects, which leads patients to realize that they have been
given the active drug, thereby increasing their expectancy for improvement.
SSREs: The Last Nail in
the Coffin
Different types of
antidepressants are supposed to affect different neurotransmitters. Some are
supposed to affect only serotonin, others are supposed to affect both serotonin
and norepinephrine, and still others are supposed to affect norepinephrine and
dopamine. But there is a relatively new antidepressant that has a completely
different mode of action. It is a most unlikely medication, and the evidence
for its effectiveness puts the last nail in the coffin of the
chemical-imbalance theory of depression.
The name of this
new antidepressant is tianeptine. It was developed in France, where it is
licensed as an antidepressant and marketed under the name Stablon. It is also
prescribed as an antidepressant in a number of other countries, sometimes under
the names Coaxil or Tatinol. Tianeptine is a selective serotonin reuptake enhancer (SSRE). Instead of increasing
the amount of serotonin in the brain - as SSRIs and SNRIs are supposed to do -
tianeptine decreases it.36 If the monoamine imbalance theory
is right, tianeptine ought to induce depression, rather than ameliorate it. But
the clinical-trial data show exactly the opposite. Tianeptine is significantly
more effective than placebos and as effective as SSRIs and tricyclic
antidepressants.37 In head-to-head
comparisons, of tianeptine with SSRIs and with the earlier tricyclic
antidepressants, all three produced virtually identical response rates. In
these studies 63 per cent of patients responded to tianeptine, compared to 62
per cent of patients who responded to SSRIs and 65 per cent who responded to
tricyclics.38
I suppose that some
ingenious minds will be able to find a way of accommodating the
chemical-balance hypothesis to these data, but I suspect that the accommodation
will require convoluted circumventions, like those used by the Flat Earth
Society in their efforts to maintain their defunct theory in the face of
photographic evidence from space. If depression can be equally affected by
drugs that increase serotonin, drugs that decrease it and drugs that do not
affect it at all, then the benefits of these drugs cannot be due to their
specific chemical activity. And if the therapeutic benefits of antidepressants
are not due to their chemical composition, then the widely proffered
chemical-imbalance theory of depression is without foundation. It is an
accident of history produced serendipitously by the placebo effect.
Theorists Leaving a
Sinking Ship
In one of the most
influential books on the philosophy of science written in the 20th century,
Thomas Kuhn described what happens when a prevailing scientific paradigm is on
the verge of being replaced by an alternative theory.39
The precursor to a paradigm change in science is the discovery of anomalies -
findings that should not be possible if reigning conceptions were correct. As
these anomalies multiply, the field is thrown into a state of crisis, from
which it emerges only when the old ideas are replaced by a new paradigm.
The biochemical
theory of depression is in a state of crisis. The data just do not fit the
theory. The neurotransmitter depletion studies that I described earlier in this
chapter show that lowering serotonin or norepinephrine levels does not make most
people depressed. When administered as antidepressants, drugs that increase,
decrease or have no effect on serotonin all relieve depression to about the
same degree. And the effect of anti-depressants, which was the basis for
proposing the chemical-imbalance theory in the first place, turns out to be
largely a placebo effect.
With all of these
data contradicting the chemical-imbalance hypothesis, researchers have been
searching for alternative biochemical explanations. Maybe depression depends on
abnormalities of the immune system, they suggest, or in a part of the brain
called the hippocampus, or in the pituitary, adrenal or thyroid glands.40 The newest fad is the theory of
neural plasticity. Neural plasticity refers to the ability of the brain to
change when people learn. As an explanation of antidepressant effects, the idea
is that depression involves problems in the way in which depressed people
process information. Antidepressant drugs - despite their very different and
sometimes conflicting mechanisms - might make it easier for people to process
information more efficiently and thereby learn from experience. How drugs might
do this, however, is a question that has ‘yet to be addressed’.41
The nice thing
about the neural-plasticity hypothesis is that it seems to explain so much. In
fact, it is a better explanation of the effects of psychotherapy than of drugs.
If recovery from depression depends on learning new ways of thinking, then
psychotherapy - and especially cognitive behavioural psychotherapy - ought to
be effective, and indeed it is, as we shall see in Chapter 7. The concept of
neural plasticity is also used to explain the therapeutic effects of
electroconvulsive shock therapy, and even of placebos, on depression. As one
proponent of the theory phrased it, ‘psychological and pharmacological
therapies, electroconvulsive shock treatment and placebo effects might all lead
to improved information processing and mood recovery through mechanisms that
initiate similar processes of plasticity’.42
The problem with
the neural-plasticity hypothesis is that it does not explain how all of these
very different treatments - including drugs that are supposed to have
biochemical effects that are directly opposite to each other - produce their
hypothesized effects on neural networks. In seeming to explain so much, the
neural-plasticity hypothesis (at least as it is used as an explanation of
antidepressant treatment) may actually explain nothing at all. And if placebos
produce changes in neural plasticity, why bother with antidepressant drugs?
DEPRESSION, DISEASE AND
THE BRAIN
As we have seen, there
is no convincing evidence that depression is due to a chemical imbalance in the
brain. The chemical-imbalance theory rode to fame on the basis of uncontrolled
case reports of improvement on some drugs and deterioration on others, while
contrary data - some of it from carefully controlled studies - were simply ignored.
Later attempts to test the theory by experimentally reducing serotonin or
norepinephrine in healthy volunteers disproved the theory completely. If the
theory were correct, lowering the levels of these neurotransmitters in the
brain ought to have induced depression. But it did not. In healthy volunteers,
it had no effect at all. Finally, we were confronted with the news of the
newest type of antidepressant - a drug that does exactly the opposite of what
conventional antidepressants are supposed to do, and yet is just as effective
as the other drugs in controlling depression. The chemical-imbalance theory is
dead in the water, and its resuscitation seems an unlikely possibility.
Let me be clear.
Depression certainly exists in the brain. All subjective states - sadness, joy,
apprehension, delight, fear and boredom - are rooted in the brain.43 Using sophisticated neuroimaging techniques,
scientists have already established some of the neural correlates of sadness
and depression, and have shown how these brain states can be altered when
depressed people get better following treatment - even if the treatment is a
placebo.44 But finding
that depression is represented in the brain does not mean that it is a disease,
let alone a disease that can be cured by chemically altering the brain.
Depression may result from a normally functioning brain, containing neural
networks that have been shaped by life events and that respond to current life
demands in a way that is experienced subjectively as sadness and despair. It
may be the events themselves that make us feel lost and hopeless, or it may be
the way in which we have learned to interpret those events. In either case, the
underlying brain mechanisms may be normal.
If the
chemical-imbalance theory is wrong, and if depression is not a brain disease,
how is it produced and how can it be prevented and treated? One way to look for
clues is to examine the process by which we were misled into the realm of
chemistry. There is a culprit hiding in the history of the chemical-imbalance
theory - a culprit that is guilty of leading doctors and patients astray over
and over again in the history of medicine. The culprit is the placebo effect,
and its darker twin, the nocebo effect. Depressed people got better when given
MAO and reuptake inhibitors as antidepressants, and this led researchers to
conclude that depression must be caused by a chemical deficiency. But much (if
not all) of that improvement turns out to be a placebo effect. So to understand
depression and how it might be treated effectively, we need to examine the
placebo effect more carefully. That is the topic of the next two chapters.
The Placebo Effect and
the Power of Belief
When our most recent -
and most definitive - meta-analysis was published, the headlines in many
newspapers blazoned that ‘antidepressants don’t work’.1 The Daily
Telegraph headline phrased it more specifically, clarifying that
antidepressants are ‘no better than dummy pills’,2
but even this headline was not entirely accurate. What our analyses actually
showed was that antidepressants work statistically
better than placebos, but that this statistical difference was not clinically meaningful. It was too small a difference to be
of much importance in the life of a severely depressed person.
When there is
little difference between a drug and a placebo, it can be due to different
reasons. One possibility is that neither the drug nor the placebo is effective.
A second possibility is that both are effective. When it comes to
antidepressants, the latter is the case. The problem is not that people do not
improve on medication. They do, and on average the degree of improvement is
clinically significant. But people also improve on placebos. This suggests that
it is not the drug that is making people better. Nor is it simply the passage
of time or the tendency for depression to lift even without treatment. Our very
first meta-analysis, in which Guy Sapirstein and I looked at the course of
depression in depressed people who had not been given any treatment at all,
showed clearly that untreated patients do not improve nearly as much as those
given either drug or placebo treatment (see Chapter 1). So rather than being
the drug or the passage of the time, it seems to be the placebo effect that
makes depressed people feel better.
How can this be?
How is it possible that a dummy pill with no active ingredients can produce
substantial improvement in a condition as serious as clinical depression? As it
turns out, placebos can be surprisingly effective, not only in the treatment of
depression, but also for various other conditions. As we shall see in this
chapter, placebos can reverse the effects of powerful medications. They can
affect the body as well as the mind. They produce side effects as well as
beneficial effects. They can make people feel sick, and they can make them feel
better. Placebo effects are part of a broader phenomenon - the power of
suggestion to change how people feel, how they behave, and even their
physiology. If placebos can produce such powerful effects, it is important to
understand them. Only by unlocking the secrets of the placebo effect can we
hope to harness its power so that it can be used in clinical practice. In this
chapter we look at the power of the placebo: its ability to produce therapeutic
change and to cause harm.
THE DISCOVERY OF THE
PLACEBO EFFECT
The word placebo is Latin for ‘I shall please’. The medical use of
the term evolved from its use in the Catholic rite of Vespers of the Office of
the Dead, in which the congregation chants the words, ‘placebo
Domino in regione vivorum’ (I shall please the Lord in the land of the
living). In medieval France, people who did not know the deceased sometimes
came to funerals with the hope of sharing in the food and drinks that were
distributed afterwards. These people came to be known as ‘placebo singers’. In
one of the Canterbury Tales, Chaucer gave the name
‘Placebo’ to a sycophantic character, and in another (The
Parson’s Tale) he wrote that ‘Flatereres been the develes chapelleyns,
that syngen evere placebo’ (flatterers are the Devil’s chaplains, always
singing Placebo).3
By the 19th century
the term ‘placebo’ had entered the medical vocabulary with the meaning ‘a
common place method or medicine’. Still there was no recognition of the placebo
effect. True to the origin of the word, placebos might please patients, but
they could not make them better. The phrase ‘placebo effect’ does not seem to
have been used prior to 1920, and the possibility that placebos might have
genuine therapeutic effects was not widely recognized until the second half of
the 20th century.4 Until then, the
placebo was considered a ‘humble humbug’ given to patients to placate them when
nothing that might cure them was available.5
Before the middle
of the 20th century clinical trials with placebo control groups were rare in
medical research. Medications were adopted primarily on the basis of clinical
experience and the testimony of experts in the field. A few placebo-controlled
studies were done in England and the US in the early part of the 20th century,
but placebos were used in these studies only as a means of controlling for the
natural history of the disease - the tendency of some conditions, like the
common cold, to improve without treatment. Patients in the control group were
given a placebo, not because of any suspicion that the placebo might have an
effect, but as a way of securing their cooperation and keeping them in the
study. This was well before the age of informed consent, and medical
researchers had no qualms about duping patients as part of a research project.
Nowadays, deceiving patients in a clinical trial is considered unethical.
Although the
routine use of placebo-controlled trials in medicine is relatively new, the
logic behind it is not. Ted Kaptchuk at Harvard University has traced the use
of placebo controls, although without the term ‘placebo’, to rites of exorcism
in the 16th century.6 The general
belief was that demons could not tolerate contact with the divine and could
therefore be detected and driven out by holy water, consecrated wafers and
prayers. To detect fraud, priests sometimes also used ‘trick trials’, in which
they used ordinary water instead of holy water, normal wafers instead of
consecrated ones, or secular Latin texts in place of prayers. If these mundane
interventions produced the same convulsions that were produced by their sacred
counterparts, the diagnosis would be fraud rather than possession.
The first
evaluation of a medical procedure using placebo controls occurred some 200
years later. The procedure was mesmerism - now more commonly called ‘hypnosis’
- as practised by the disciples of the 18th-century Viennese physician Franz
Anton Mesmer. Mesmer believed that many illnesses were caused by a bodily
imbalance of an invisible magnetic fluid that permeated the universe. Just as
antidepressants are used today to restore a presumed chemical imbalance, so
Mesmer and his followers used magnetic treatment to restore the magnetic
imbalance that they believed was the cause of their patients’ illnesses.
In the 18th century
conventional medical treatments - like bloodletting - were not subjected to
placebo-controlled trials. But mesmerism was not a conventional treatment. The
mesmerists touched their patients with magnets, massaged their bodies, had them
stand under ‘magnetized’ trees or gave them ‘magnetized’ water to drink. The
most scandalous procedure involved having a female patient sit with her knees
pressed firmly between the thighs of the mesmerist, who applied pressure to her
‘ovarium’, while stroking her body until she began to convulse. This was
referred to as ‘making passes’ and, according to later historians, many women
were so pleased by the convulsive crisis produced by this treatment that they
followed Mesmer down the hall and begged him to repeat it.7
In 1784 a Royal
Commission was established by Louis XVI to investigate mesmerism. Its members
included some of the most illustrious figures of the time: Benjamin Franklin,
who was at the time the American Ambassador to France; Antoine Lavoisier, the
founder of modern chemistry; and the infamous Joseph-Ignace Guillotin, who is
now best known for his mechanical solution to the mind-body problem. The
commissioners devised a series of experiments that included some surprisingly
sophisticated expectancy control procedures. For example, a tree in Benjamin
Franklin’s garden was ‘magnetized’ by one of Mesmer’s disciples, but the
experimental subject was intentionally brought to the wrong tree. Another
subject was told that a container of water had been ‘magnetized’; in fact it
had not. Yet another subject was misinformed that the mesmerist was
‘magnetizing’ her from behind a closed door. The success of these expectancy
manipulations led the commissioners to conclude that the effects of mesmerism
were due to imagination and belief, rather than magnetism.
Early in the 20th
century German, Austrian and Swiss researchers recognized the possibility that
apparent medication effects might be due to suggestion, and in the 1930s a few
American medical researchers came to a similar conclusion. Still, it was not until
the 1950s that the power of placebos to do more than merely provide comfort to
incurable patients became widely recognized by the medical community, and it
was this recognition that led to the adoption of the placebo-controlled
double-blind trial - which had been advocated for two decades by Harry Gold and
his colleagues at Cornell University - as the aptly named ‘gold standard’ for
assessing new medications.8
The first influential
verification of the power of placebo to produce real effects was reported in
1950 by Stewart Wolf, a physician and medical researcher at Cornell University.9 In his seminal article on the
‘pharmacology of placebos’, Wolf described a number of experimental
demonstrations of the ability of a placebo to reverse the effects of an active
medication. In each case the reversal was brought about by misinforming the
subject about the nature of the drug being administered, and in each case the
subjective changes were verified by physiological assessment. The active
medication was ipecac - a drug that induces nausea and vomiting and that was
once used for that purpose when children accidentally swallowed a toxic
substance, a practice that healthcare authorities now strongly advise against.
One of Wolf’s
subjects was a 28-year-old pregnant woman who had been vomiting continuously
for two days. Wolf told her that he was giving her a medicine that would
abolish her nausea. Instead, he gave her ipecac. Wolf reported that his
patient’s nausea subsided completely within 20 minutes of ingesting the ipecac
syrup, and did not recur until the following morning. To see what was happening
physiologically, Wolf had inserted a balloon in his patient’s stomach, allowing
him to record her gastric contractions. Before treatment she showed the
inhibition of gastric activity that generally accompanies nausea, but when her
nausea subsided, normal gastric contractions resumed. This meant that the placebo
effect was not just in his patient’s mind; it was also in her body.
Wolf then conducted
a similar experiment on a young depressed woman who had complained of recurring
episodes of nausea over the previous few months. First, he confirmed that this
patient’s complaints of nausea were accompanied by gastric inactivity. Then he
gave her ipecac and told her it would abolish her nausea. Within half an hour
Wolf observed a resumption of normal gastric activity, and the patient reported
that her nausea had gone. When the nausea returned an hour later, Wolf gave her
another dose of ipecac. This time the therapeutic effect occurred within 15
minutes. Normal gastric contractions resumed, and the patient reported no
further experiences of nausea that day.
The best known of
Wolf’s demonstrations of placebo effects on gastric function involved a patient
identified as Tom. Tom had a large gastric fistula, an abnormal duct that made
it possible to directly observe his gastric mucous membrane. Because of his
condition, Tom was the subject of more than 100 experiments on the effects of
various drugs. One of these was prostigmine, a drug that produced gastric
hyperfunction, abdominal cramps and diarrhoea. These effects were later
reproduced by inert placebos. In another experiment, Tom was observed following
13 administrations of a placebo and during 13 control trials in which no
substance was given to him. Placebo administration resulted in a 33 per cent
decrease in gastric acid secretion, as compared to an 18 per cent decrease
during control trials.10
In 1955 Henry
Beecher published an article entitled ‘The Powerful Placebo’, which, despite
its age, may be the single most influential paper on the placebo effect ever
written.11 Beecher claimed
that, averaged across 15 studies involving a variety of conditions - including
severe post-operative pain, headache, anxiety, seasickness, coughs and colds -
about one out of three patients given a placebo showed significant improvement,
a figure that has come to be enshrined as gospel. Yet as widespread as this
conventional wisdom is, it is a myth.
In fact, the
percentage of patients who respond to a placebo can vary from none at all to almost
everyone. That the response to a placebo can vary widely was first shown in a
1957 study conducted by Eugene Traut and Edwin Passarelli at an arthritis
clinic in Chicago.12 First, Traut
and Passarelli gave their patients placebo pills. Half of the patients
improved; half did not. Those showing no improvement were then given placebo
injections. Adding together those who responded to the placebo pill and those
who responded to the placebo injection, 82 per cent of the patients seemed to
benefit from placebo treatment, and continued placebo treatment was effective
for up to 30 months, which was the full duration of the study. So what is the
real rate of response to a placebo? Is it 30 per cent, as Beecher had claimed;
50 per cent, as shown by patients given placebo pills for arthritis; or 80 per
cent, as shown when the pills were supplemented by placebo injections? In fact,
the question does not have a meaningful answer. It is much like asking what percentage
of people get drunk on beer, without specifying how much beer they have
consumed.
Although Beecher’s
paper on the power of placebo was enormously influential - to the point of
changing the way new medicines are evaluated - there was a fundamental flaw in
the data upon which it was based.13
Sometimes people improve without being given any treatment at all, not even
placebo treatment. Beecher’s estimate of the rate of response to a placebo did
not take into account the natural history of the condition being treated,
spontaneous recovery or any of the other factors that can produce improvement
even in patients who have not been given a placebo. Certainly the 35 per cent
placebo response that Beecher calculated for the common cold must have been due
to the simple passage of time. Just as the effect of a drug is assumed to be
the difference between the response to the drug and the response to a placebo,
so the placebo effect is the difference between the response to the placebo and
improvement that would have occurred if the person had not taken a placebo -
and that is something Beecher simply did not evaluate.
In 2001 two Danish
researchers, Asbjørn Hróbjartsson and Peter Gøtzsche, published an influential
meta-analysis in which they estimated the difference between the effects of
getting a placebo versus doing nothing at all.14 Although they found a signifi -
cant placebo effect, especially in the treatment of pain, the overall effect
seemed very small - much smaller than would have been expected of a ‘powerful’
treatment. On the basis of these data, the researchers asked ‘Is the placebo
powerless?’ and answered their own question by concluding that there was little
evidence that placebos have powerful clinical effects.
It seemed that
Beecher was wrong after all. But was he? There are two major problems with the
Danish meta-analysis. One problem is the way in which the term ‘placebo’ was
defined. Usually, placebos are dummy pills, capsules or injections, presented
in the guise of active medications. But many of the studies that Hróbjartsson
and Gøtzsche evaluated did not include a placebo in this sense of the term.
Instead, these studies looked at the effects of leisure reading, answering
questions about hobbies, and talking about books, movies and television shows.
All of these were called placebos, and their effects were included as placebo
effects. But do they really qualify as placebos? If you were given a medication
and told by your doctor that it had been proven effective, you might have
considerable confidence in it. But imagine that instead of giving you
medication, your physician asked you about your favourite television programme
or suggested that you curl up with a nice mystery that night. How likely is it
that you would go away with the expectation of improvement that placebos are
supposed to generate, and by means of which they are presumed to produce their
effect? A meaningful evaluation of the placebo effect has to be based on a
credible placebo, one that raises expectations of improvement that are as great
as those elicited by active treatment.
An even more
fundamental shortcoming in Hróbjartsson and Gøtzsche’s analysis is the
diversity of disorders that they evaluated. These included the use of placebos
to treat the common cold, infertility, marital discord, mental retardation,
alcohol abuse, smoking, poor oral hygiene, herpes-simplex infection, fecal
soiling and ‘undiagnosed ailments’. Placebos are not panaceas. They may be very
powerful for some conditions, less effective for others, and have no effect at
all on some ailments. As we saw earlier in this book, placebos are highly
effective in the treatment of depression, in which the placebo effect (that is,
the difference between the response to the placebo and the mere passage of
time) is twice as large as the drug effect (the difference between the response
to the drug and the response to the placebo). They also have a substantial
effect on pain, especially in studies specifically designed to assess the
placebo effect.15 But placebos
are not likely to have much of an effect on infertility. Nor are they likely to
have any effect on newborn infants, who were the subjects in one of the studies
that Hróbjartsson and Gøtzsche analysed.
Imagine reading a
scientific article assessing the effectiveness of medical treatment in general,
without regard to what condition was being treated or how it was treated? The
article might conclude that medical treatments are very effective or that they
are not very effective, depending at least in part on which particular medical
treatments had been included in the review. It is just not meaningful to try
and estimate the effectiveness of medical treatment in general. Some medical
treatments are extremely effective, whereas others have much smaller effects,
and there are some medical conditions for which effective treatments have not
yet been found.
This is the basic
problem with any attempt to evaluate the overall effectiveness of placebos, as
Beecher and the Danish researchers had tried to do. There is not just one
placebo effect. Instead, the placebo effect depends on a host of factors. It
depends, for example, on the condition being treated, the way in which the
placebo is administered, the colour of the placebo, its price, whether it has a
recognized brand name and the dose that is prescribed. Studies of the placebo
effect reveal that, all else being equal, taking placebo pills four times per
day is more effective than taking them only twice a day; brand-name placebos
are more effective than placebos presented as generic drugs; placebo injections
are more effective than placebo pills; and more expensive placebos are better
than cheaper ones.16
The placebo effect
also depends on what people are told about the ‘treatment’ they are given. The
effect is smaller when patients are told that their treatment might be a
placebo, as is routinely done in clinical trials, and is larger when people are
told that their treatment has been shown to be powerful.17 Because the placebo effect can
vary so much, attempts to estimate its power in general, without specifying the
condition being treated and the conditions under which the placebo was
administered, are meaningless.
Perhaps the most
persuasive evidence that the placebo effect can be very powerful comes from
studies in which it has been found to be more effective than an active drug.
The most recent study of this sort was reported by a team of researchers led by
Peter Tyrer in the Department of Psychological Medicine at Imperial College
London. Tyrer’s group assessed the use of antipsychotic drugs as a way of
reducing aggressive behaviour in mentally retarded adults. Consistent with
clinical reports, they did indeed find a substantial drop in aggression
following treatment, but the largest decrease in aggression was not in the groups
treated with real drugs. Rather, it was in those given a placebo. The patients
given the real antipsychotic drugs showed an average decrease in aggressive
behaviour of about 60 per cent. Those given a placebo showed an 80 per cent
reduction in aggression. It seems that the effect of the real drugs was to
reduce the powerful placebo effect.18
Placebo Surgery
One of the factors that
influence the magnitude of the placebo effect is the way in which the placebo
is administered. Placebo injections, for example, are more effective than
placebo pills; and placebo acupuncture - which uses sham needles that retract
into their handles like the blade of a stage dagger, rather than piercing the
skin - is also more effective than placebo pills.19 The most powerful placebo of all
is surgery. Approximately 45 per cent of patients with Parkinson’s disease get
better when treated with sham surgery, but only 14 per cent of Parkinson’s
disease patients improve when treated with placebo pills.20
Placebo surgery? I
know it sounds like a joke, but it isn’t. Like any medical treatment, surgical
procedures elicit expectancies of improvement, and therefore part of their
effectiveness can be due to the placebo effect. For this reason, sham surgery
has been used as a placebo in some clinical trials. Placebo surgery consists of
cutting the patients open and sewing them up, without doing the actual surgical
intervention.
The first studies
using placebo surgery were done at the end of the 1950s. At that time, a
surgical procedure called mammary ligation was used to treat angina pectoris.
Angina is a chest pain that occurs when the heart muscle does not get enough
oxygen. It is a symptom of coronary artery disease, which is produced when
plaque narrows or blocks the arteries, thereby reducing the flow of oxygen-rich
blood to the heart. The theory behind mammary ligation was that if some of the
coronary arteries were blocked off completely, the blood would find alternative
routes to the heart.
Clinical experience
indicated that mammary ligation was very effective in the treatment of angina,
with success rates as high as 85 per cent.21 Still, at least part of its
effectiveness might be due to the placebo effect, the power of which had
recently been promulgated in the articles by Beecher, Wolf and Gold that I
described earlier in this chapter. This possibility led two independent teams
of medical investigators, one in Seattle and the other in Kansas City, to test
the effects of mammary ligation against placebo surgery.22 Some patients in these studies
were given the real surgical treatment. Patients in the placebo groups were
also cut open and their mammary arteries were exposed, but the arteries were
not tied off. Across these two clinical trials, 73 per cent of the patients
receiving real mammary ligation showed substantial improvement. This is not
much different from what had been reported in uncontrolled studies, and had the
researchers not included placebo surgery groups, they might have concluded that
mammary ligation was effective. But the rate of improvement with placebo
surgery was 83 per cent, which was not significantly different from the
response to the real treatment. The apparent effect of mammary ligation was
gigantic, larger than the effect of giving antidepressants to depressed
patients, but it was a placebo effect. Needless to say, mammary ligation is no
longer used as a treatment for angina.
The patients’
comments following placebo surgery is instructive. Asked whether they had
noticed any change following surgery, one patient said, ‘Yes. Practically
immediately I felt better. I felt I could take a deep breath and I have taken
about ten nitroglycerins since surgery. These pains were light and brought on
by walking. I figure I’m about 95 per cent better. I was taking five nitros a
day before surgery. In the first five weeks following, I have taken a total of
twelve.’ Another patient, responding three months after the operation, wrote,
‘I can do anything except real hard lifting. I am running farm equipment and
using maybe one nitro a week. I used to need fifteen a day. Believe I’m cured.’23
These comments are
very similar to testimonials for antidepressants that appeared in the media
shortly after my most recent meta-analysis was published. They demonstrate the
danger of relying on clinical reports of patient improvement in deciding
whether a particular treatment is effective. Placebos can yield substantial
clinical benefit that can last for months or even years.24
After these two
placebo-controlled clinical trials of mammary ligation, the use of a placebo
control condition to evaluate surgical procedures seemed to disappear, only to
make a comeback some 40 years later. In the 1990s Bruce Moseley, a surgeon at
the Veterans Affairs Medical Center in Houston, Texas, and physician for the
Houston Rockets basketball team, routinely performed arthroscopic surgery for
osteoarthritis of the knee. Two procedures were in use at the time, and there
was a debate as to which was better. One procedure involved making small
incisions in the knee and rinsing the joint. In the second procedure, the joint
was scraped as well as rinsed. Some doctors thought that scraping rough
surfaces of the joints made the operation more effective, whereas others
suspected that it might cause some damage.
Although these were
well-established operations, performed on hundreds of thousands of people each
year, Moseley wondered whether either procedure was of any real benefit, and
conceived the idea of comparing them directly. When Moseley proposed this idea
to Nelda Wray, his colleague at the VA hospital and Director of Health Services
Research at the Baylor College of Medicine, she suggested that the apparent
benefits might be due to the placebo effect. At first, Moseley was sceptical.
This was a surgical procedure, after all, not a sugar pill. But Wray convinced
him that the possibility was worth investigating. ‘The bigger and more dramatic
the patient perceives the intervention to be,’ she said, ‘the bigger the
placebo effect.’25
Wray and Moseley
then assembled a team of medical researchers and designed a clinical trial
aimed at comparing real arthroscopic surgery to placebo surgery.26 They recruited 180 patients for
the study. One-third of them were given the full rinsing and scraping
procedure. For another third of the patients, the joint was rinsed, but not
scraped. The rest were given placebo surgery. First, three incisions were made
with a scalpel so that there would be scars afterwards. Then ‘the surgeon asked
for all instruments and manipulated the knee as if arthroscopy were being
performed. Saline was splashed to simulate the sounds of lavage.’
Not only was this
placebo operation effective, but it was significantly more effective than
actual surgery, at least in the short run. Two weeks after their operations,
patients in the placebo group reported significantly less pain than those in
either of the surgery groups, and they also showed more improvement on an
objective test of walking and climbing stairs. One year after the operation,
patients in the placebo group still walked and climbed stairs significantly
better than those whose knee joints had been both rinsed and scraped, and two
years after the surgery there were no significant differences between the
groups. In other words, in the long run, rinsing the knee joint did no good at
all, and - as Moseley had expected - scraping it actually caused damage lasting
at least a year.
There are some
interesting parallels between Moseley and Wray’s study of arthroscopic surgery
and the meta-analyses that my colleagues and I reported for antidepressants.
One similarity is that the failure to find substantial differences between real
and placebo treatment was not because of a lack of response to the treatment.
Patients given real surgery in Moseley and Wray’s study reported having much
less pain than they had before treatment, just as patients given
antidepressants report being less depressed. But in both cases, patients also
showed substantial improvement after placebo treatment. One patient in the
sham-surgery group described the outcome as follows: ‘The surgery was two years
ago and the knee never has bothered me since. It’s just like my other knee now.
I give a whole lot of credit to Dr Moseley. Whenever I see him on the TV during
a basketball game, I call the wife in and say, “Hey, there’s the doctor that
fixed my knee!”’27
Another parallel
between Moseley and Wray’s study of sham surgery and the study in which my
colleagues and I reported our analysis of the FDA antidepressant data is the
reactions that they evoked. If real arthroscopic knee surgery is no better than
placebo surgery, one would think that the procedure would be abandoned, just as
mammary ligation was discarded as a surgical procedure after its effects were
found to be no better than those of placebo surgery. Instead, many orthopaedic
surgeons tried to discredit Moseley and Wray’s clinical trial, just as
defenders of antidepressants have tried to discredit our meta-analyses of
antidepressant drugs. An editorial in the journal that published the Moseley
and Wray study, for example, opined that arthroscopic surgery might benefit
some patients but not others.28 In a spirited and compelling reply
to the editorial, the authors of the study responded that ‘if someone questions
whether arthroscopic surgery would be efficacious in a specific subpopulation
of patients, then the ethical way to proceed would be to test the hypothesis by
conducting a placebo-controlled trial in that specific subgroup’.29 I agree completely, and the same
can be said for those who hypothesize that antidepressants might be clinically
effective for some subgroups of patients. If antidepressants are effective for
some groups of patients, ‘the ethical way to proceed would be to test the
hypothesis by conducting a placebo-controlled trial in that specific subgroup’.
More recently, new
data have confirmed the findings reported by Moseley and Wray. The new study
showed that surgery added nothing to the effects of physical and medical
therapy alone.30 This article
was also accompanied by an editorial offering a defence of arthroscopic
surgery.31 The editorial
acknowledged that the new study provided ‘strong support for the conclusion of
Moseley et al. that arthroscopic surgery is not effective therapy for advanced
osteoarthritis of the knee’, but added that perhaps it is useful for patients
whose osteoarthritis is accompanied by some other knee condition. It’s déjà vu
all over again!
Is placebo surgery
ethical? Should doctors be allowed to administer anaesthesia and make surgical
incisions, but then not do any therapeutic intervention? Isn’t the first rule
of medicine to do no harm? It is true that informed consent is now required in
clinical trials. This means that patients are told that they might not get the
real surgery, and they can decide whether or not to participate. But is that
enough? Is it acceptable to expose patients to the risks of sham surgery, even
if they agree to participate?
This is surely an
ethical dilemma, but there is also another way to look at this issue. The
question can be rephrased as follows: is it ethical to perform a surgical
procedure on patients without first testing it against placebo surgery? Suppose
that the placebo-controlled studies of mammary ligation had never been done at
all. We would never have learned that the benefits of this surgical procedure
are due to the placebo effect, and we would still be performing this
ineffective procedure today. Over the years it would have been performed on
hundreds of thousands of patients, without the patients or their physicians
ever knowing that the surgery was really a placebo. So the choice is between
giving sham surgery to a relatively small number of patients, after informing
them of the risks and letting them decide whether to participate, or exposing
large numbers of patients to the risks of ineffective surgery, with neither
them nor their doctors knowing that the surgical procedure is, in fact, merely
a placebo. Which of these alternatives do you consider ethically preferable?
Mind and Brain
One of the factors that
determine the effectiveness of a placebo is the nature of the condition being
treated. Conditions that have a strong psychological component - such as pain,
anxiety and depression - are particularly prone to placebo influence, whereas
conditions like bone fractures, diabetes and infertility are less likely to be
affected by placebo treatment. But this does not mean that placebo effects are
‘all in the mind’. Placebos affect physiology as well as psychology.
The most common
physiological effects of placebos are those that are associated with changes in
subjective experience. When placebo stimulants make people feel energized and
alert, for example, they also increase their blood pressure and heart rate, and
when placebo tranquillizers relax people, they decrease their blood pressure
and heart rate.32 Similarly, when
Stewart Wolf gave ipecac to patients and told them it would ease their nausea,
their reports of no longer feeling nauseous were accompanied by a resumption of
normal gastric activity.
Many people seem
particularly impressed by the physiological effects of placebos. They see them
as evidence that the mind can affect the body. But the physiological placebo
effects I have described are not all that surprising. Instead, they are exactly
what we should expect, given what we know about the relation between mind and
body. Strictly speaking, they are not really instances of mind affecting body.
Rather, they are instances of body affecting body.33
What do I mean by
this seemingly strange assertion? As far as we know, there is a physical
substrate to all of our subjective experiences. In particular, experience seems
to be linked to our brains. When the brain is injured, subjective experience is
also changed, and the changes in experience are specific to the location of the
tissue damage. Conversely, our subjective experiences are accompanied by
changes in brain activity, and the particular areas of the brain in which these
changes occur depend on the nature of the experience. With the advent of modern
methods of imaging the brain, neuroscientists have located specific brain areas
that are involved in vision, pain perception, speech, the voluntary control of
movements and a vast myriad of other cognitive functions that were in the past
attributed to the mind. Just as water is H2O, so the mind
seems to be the brain.34
If what we
experience is associated with something that happens in the brain, and if
placebos change subjective experience, then we ought to be able to find changes
in brain activity that are produced by placebos - and in fact this is precisely
what has been found. A team of researchers led by Helen Mayberg, a neurologist
at Emory University and the University of Toronto, have used a technique called
positron emission topography (PET) to study changes in brain activity
associated with the experience of depression.35
In the first of
these studies, the researchers identified the areas of the brain that are
associated with normal sadness. They asked volunteer subjects to think about
some very sad personal experiences - and about some emotionally neutral
experiences - while their brains were being imaged in a PET scanner. When
thinking about the sad experiences, the volunteers reported feeling intense
sadness, and many of them became tearful. The PET scans showed the changes in
brain activity that accompanied these sad feelings. They demonstrated increased
blood flow in the limbic system - a part of the brain that is involved in the
control of emotion - and decreased blood flow in parts of the brain that are
involved in the control of attention.
In their next
study, Mayberg and her colleagues scanned the brains of depressed patients who
had responded positively to treatment for depression in a clinical trial of
Prozac. The patients were scanned twice, once before the treatment had begun
and once again after six weeks of treatment. About half of the patients responded
positively to the treatment by showing at least a 50 per cent reduction in
their symptoms; the other half did not improve that much and were classified as
non-responders. For the responders, but not for the non-responders, treatment
of depression produced changes in brain activation in exactly the same areas in
which normal sadness had produced changes, but in the opposite direction. In
other words, successful treatment decreased brain activity in areas where
sadness produces increased activity, and it increased brain activity in areas
where sadness decreases it.
At first blush, you
might be tempted to interpret this as evidence for a specific
neurophysiological effect of Prozac on depression. But there was a catch. Only
half of the successfully treated patients had been given Prozac. The rest had
recovered on a placebo, and the changes in brain activity that the researchers
had found were ‘independent of whether the substance administered was active
fluoxetine or placebo’.36 In other words, when placebos are
successful in lowering depression, they also produce changes in brain
activation, and for the most part these are the same changes produced by the
real drugs.
Mayberg’s studies
seem to suggest two conclusions. First, one would be tempted to conclude that
it is the placebo effect, rather than the chemical effect of medication, that
had changed the brain activity of the patients who had been given Prozac.
Second, one might interpret the observed changes in brain activity as
indications of how placebos reduce depression. In fact, neither of these
conclusions is justified. The physiological changes are exactly what would be
expected of any effective treatment for depression,
no matter how the treatment works. They are changes in patterns of brain
activity that correspond to sadness and depression. When depression is
overcome, these changes in brain activation are reversed, no matter how the
improvement in depression is brought about, whether by drugs, placebos or some
other form of treatment.
Each of these
treatments might also produce physiological alterations that are specific to
the treatment.37 Antidepressants
are active drugs, and like other active drugs they certainly have physiological
effects. Psychotherapy is a learning experience, and learning changes the
brain.38 So it, too, has
specific neurological effects. Nevertheless, recovery from depression has its
own neural substrate, and this can be seen when people improve on placebos, as
well as when other treatments have produced the improvement.
Depression is not
the only clinical condition in which placebo effects have been linked to changes
in the brain. Changes in brain activity have also been shown in neuroimaging
studies of placebo analgesics, the most influential of which was reported by a
team of researchers led by Tor Wager, a neuroscientist at Columbia University
who, at the time he conducted these studies, was a postgraduate student at the
University of Michigan.39
Wager’s interest in
the connection between mind and body stemmed from childhood. He had developed a
severe skin rash, and his mother - who was a Christian Scientist who believed
that illnesses were products of the mind - prayed and prayed for its cure, but
to no avail. Finally a friend said to her, ‘Enough praying; take the kid to a
doctor.’ The doctor applied an ointment to the skin and the rash was cured.
From that point on, the family took a more traditional approach to medical
treatment.
With that story as
part of his family lore, Wager grew up sceptical of claims about the healing
power of the mind, but he also developed a keen interest in the kinds of
health-related outcomes that might be affected by belief. That interest
eventually led him to conduct scientific investigations of the placebo effect,
studies that have given him an international reputation.
Wager’s first step
was to see if giving people a placebo would lead them to report less pain.
Despite what he had read about the placebo effect, he was not convinced that it
would. To find out, he and his colleagues induced pain in healthy volunteers
with electric shocks. Sometimes the investigators put a placebo cream, which
they described to subjects as ‘a highly effective pain-relieving medication’,
on the subjects’ arms before shocking them. Sometimes they shocked them without
the cream. In either case, the subjects had to rate how much pain they felt.
The volunteers in
Wager’s study reported feeling less pain when the placebo cream had been
applied than when it had not. In other words, they showed a placebo effect. But
had they really felt less pain, or was this just something they were saying to
be cooperative? To answer this question, Wager ran two more studies. They were
much like the first, but this time the experimenters induced pain - with and
without placebo treatment - while imaging the subjects’ brains in an fMRI
(functional magnetic resonance imaging) scanner.
When the placebo
cream had not been applied, the researchers found activation in areas of the
brain that they identified as the ‘pain matrix’. But when the same pain stimuli
were administered with the placebo cream, activation in these pain-responsive
regions of the brain was reduced, and the more pain relief the subjects
reported, the greater the reduction of activation in the pain matrix. This told
Wager that people actually do experience less pain when given placebo
analgesics, and this change in experience is accompanied by changes in brain
activity.
Brain and Body
The physiological
effects that we have reviewed so far - be they changes in heart rate, blood
pressure or brain activation - are exactly what one would expect, given that
any change in experience should be associated with a corresponding change in
physiology. But other placebo-induced physiological effects have been reported
in the literature, and some of these are more difficult to understand. These
include physiological effects of placebo treatment on asthma and eczema. If we
are right in assuming that the mind is the brain, then they are really examples
of the brain affecting other parts of the body, but exactly how it does so in each
instance remains unclear.
The placebo effect
in asthma is one of the most well-studied and robust placebo effects on
physiological function. The wheezing that sufferers of asthma experience is
accompanied by a constriction of the bronchial airways that makes it difficult
for them to breathe. Asthma medications dilate the bronchial tubes, making it
easier to breathe, but a large number of studies have shown that placebos can
also affect bronchial dilation. In fact, about two-thirds of the response to real
asthma medication is also produced by placebo treatment, leaving about
one-third of the effect as a true drug effect.40
One of the most
convincing demonstrations of the effect of placebos on asthma was conducted by
a research team led by Thomas Luparello, a psychiatrist at the State University
of New York.41 Luparello’s
team asked 40 asthmatic patients to inhale what they presented as irritants or
allergens previously identified by the subjects as triggers for their asthmatic
attacks. In fact, the substance they inhaled was an inert saline solution -
simple table salt dissolved in water. Nineteen of the 40 asthmatic patients
reacted with a significant increase in airway resistance, and 12 of them
developed full-blown bronchospasm attacks. These asthma attacks were then
reversed by the administration of a placebo presented as an asthma medication.
In a subsequent
study, Luparello and his colleagues gave two different drugs to asthmatic
patients.42 One of the
drugs was a bronchodilator, a medication that dilates the airways and makes it
easier to breathe. The other was a bronchoconstrictor, a drug that constricts
the bronchial tubes and makes breathing more difficult. Sometimes the subjects
were told the truth about what they were inhaling. Sometimes they were misled -
they were told they were inhaling a bronchodilator when in fact they were
inhaling a bronchoconstrictor, or vice versa. After each inhalation, the
researchers measured changes in airway resistance. Not surprisingly, they found
a significant effect for the type of drug the patient inhaled. The
bronchodilator dilated the bronchial tubes and the bronchoconstrictor
constricted them. But what the subjects were told also made a difference. When
the suggestion about the effect of the drug was in conflict with the real drug
effect, the response to the drug was cut in half.
In 1962, Yujiro
Ikemi, founder of the Japanese Society of Psychosomatic Medicine, and his
colleague Shunji Nakagawa published a remarkable study showing that suggestion
could both induce and inhibit contact dermatitis.43 Contact dermatitis is a skin
condition produced by chemical substances to which people have become
sensitized. One of these substances is an oil called urushiol, which is found
in various plants, including poison ivy in the United States and lacquer trees
in Japan. Some people are very sensitive to urushiol; others much less so.
Ikemi and Nakagawa found 13 boys who reported being hypersensitive to lacquer
leaves. They touched one of each boys’ arms with leaves from a harmless tree,
telling them that the leaves were from a lacquer tree. On the other arm the
students were touched with the poisonous lacquer leaves, which they were told
were from a harmless chestnut tree. All 13 boys displayed a skin reaction to
the harmless leaves (the placebo) and in 11 of these boys the reaction was
described as ‘marked’. Only two of the boys reacted to the actual poisonous
leaves.
Perhaps the most
provocative report of placebo power is a case in which placebo treatment
appeared to have profound effects on the course of cancer.44
Mr Wright’, as he was called in the report of his case, had tumours the size of
oranges in his neck, armpits, groin, chest and abdomen. The prognosis was that
he had less than two weeks to live. Having read about a new experimental drug
that was to be tested at the hospital, Mr Wright persuaded his physician to
include him in the clinical trial. Three days later the tumours had ‘melted
like snow balls on a hot stove, and in only these few days, they were half their
original size’. Within ten days practically all signs of the disease had
vanished.
About two months
later reports began appearing in the press indicating that the experimental
drug had been proven ineffective. After reading these reports, Mr Wright lost faith
in the treatment that seemed to have benefited him so greatly and relapsed to
his pre-treatment condition. At this point, his physician managed to persuade
him that the negative results were due to a deterioration of the drug and that
a new, refined, double-strength product was due to arrive shortly. A couple of
days later, treatment with an inert placebo was begun.
The effects of
placebo treatment were even more dramatic than those obtained with the
experimental drug. Once again the tumour masses ‘melted away’ and Mr Wright
remained symptom-free for two more months. Then he read an announcement by the
American Medical Association concluding that the drug he thought he was getting
was ‘worthless’. He died a few days later.
As provocative as
it is, we have to be careful in drawing conclusions from Mr Wright’s case
history. At best, it is a tantalizing teaser. It is, after all, based on only
one patient, and it is most likely that the changes in Mr Wright’s condition
were not due to his belief in the medication. There is evidence that some
cancers may spontaneously go into remission,45 and this might be the best
explanation of reported changes in Mr Wright’s cancer. The timing of the
changes in his condition - the fact that remission occurred when he thought he
was taking an effective medication and that he relapsed when he learned that
the medication was ineffective - might just have been coincidental. As
convinced as I am by the data that there is a powerful placebo effect on some
conditions, I remain sceptical of claims of remarkable cures of physical
illnesses. As Carl Sagan said, ‘Extraordinary claims require extraordinary
evidence’. With respect to seemingly miraculous cures of serious physical conditions,
even ordinary evidence is largely missing. Nevertheless, Mr Wright’s story
seems compelling enough to suggest that controlled research on the ability to
affect cancer psychologically might be warranted.
The Nocebo Effect
We usually think of
placebo effects as being beneficial. Placebos reduce depression, anxiety and
pain, improve the symptoms of Parkinson’s disease and open up the constricted
airways of people suffering from asthma. But placebos can have negative as well
as positive effects, a phenomenon that is called the nocebo effect. We have
already encountered some of these. Just as placebo inhalants can open airways,
they can also constrict them. It all depends on what the person is told about
the substance they are inhaling. In the Japanese study on contact dermatitis,
being touched with placebo leaves produced skin reactions. In the case report
of Mr Wright’s placebo treatment for cancer, although the patient went into
remission when he thought he was getting effective treatment, he relapsed when
he became convinced that the treatment was ineffective. All of these are
examples of the nocebo effect.
One of the most
fascinating examples of the nocebo effect comes from a study of the effect of
placebos on insomnia.46 Two researchers
at Yale University advertised for students suffering from insomnia to
participate in a study that was supposedly investigating the effect of bodily
activity on the content of their dreams. Some of the subjects were given
placebo pills to take before going to sleep; others were in a control group and
were not given any pills. Students on the pills were given different
information about what the pills contained. Half of them were told that the
pill would arouse them; the other half were told that it would relax them. The
results were surprising. Insomniac students given the ‘arousing’ pills fell
asleep sooner, and those given the ‘relaxing’ pills took longer to fall asleep.
How did the
researchers explain these strange findings? Actually, they had predicted the
results in advance. Their idea was that when people have trouble falling
asleep, they may see the cause of their difficulty as being a personal
inadequacy. This attribution about why they cannot sleep makes the person
emotionally aroused, thereby making it even harder to fall asleep. When given
‘arousing’ pills, however, people may make a different interpretation about the
meaning of their arousal. Now it isn’t an indication of a personal
characteristic, but rather a condition produced by the drug. This leads them to
worry less about their sleeplessness and therefore to fall asleep more easily.
On the other hand, when people given ‘relaxing’ pills find themselves having
difficulty settling down, the fact that they have taken a pill might intensify
their negative attributions. ‘Look how badly off I am,’ they might think. ‘I’ve
taken a tranquillizer and I still can’t sleep. I must
really be in bad shape.’ Thoughts like this would, of course, make it even more
difficult to get to sleep.
Sometimes nocebo
effects spread like infectious diseases and affect large numbers of people.
Technically, this is called mass psychogenic illness, but it is more commonly
known as mass hysteria. Mass hysteria has been recognized for centuries, but a
relatively recent case that was reported in the New England
Journal of Medicine a few years ago provides a nice illustration of the
phenomenon.47 On 12 November
1998 a high-school teacher in the state of Tennessee noted a smell like that of
petrol in the classroom, following which she reported experiencing a headache,
nausea, shortness of breath and dizziness. When some of her students reported
similar symptoms, the class was evacuated, the school was closed and 100
students, staff and family members were taken to the emergency room of the
local hospital, where more than one-third were kept overnight.
The school remained
closed for two days, during which it was examined carefully by the fire department,
the gas company and state officials of the Occupational Safety and Health
Administration (OSHA), but no evidence of any toxic compounds was found.
Meanwhile, the number of students and staff experiencing symptoms increased,
and the variety of symptoms they reported expanded to include tightness of the
chest, difficulty breathing, sore throat, burning eyes, coughing, abdominal
pain, watery eyes, vomiting, sneezing and diarrhoea, but no blood or urine
abnormalities were detected. Only three factors predicted whether a student
developed symptoms. Students were more likely to have symptoms if they were
female, if they had seen someone else showing symptoms and if they knew someone
who had developed symptoms. The investigators concluded that the case was
typical of mass hysteria.
Inspired by the
Tennessee school incident, William Lorber, Giuliana Mazzoni and I have studied
psychogenic illness in the laboratory.48 We asked a group of university
students to inhale a substance that we described to them as a suspected
environmental toxin. In fact, what we gave them to inhale was plain ambient
air. We told them that the substance had been reported to evoke a number of
physical symptoms, particularly headaches, nausea, drowsiness and itchy skin.
Then we had them report their experience of these and other symptoms over the
course of an hour. During that time the students reported an increase in all of
the symptoms. The increase was much larger for the four symptoms that we had
identified as having been reported previously, and their reports of itchy skin
and drowsiness were accompanied by scratching and yawning. We carried out this
study in the state of Connecticut in New England, where polluted air might indeed
contain toxic substances, but we also included a control group. The students in
the control group were not asked to inhale from the placebo inhaler, but of
course they were breathing the same air. They did not report an increase in
physical symptoms.
Throughout this
book I have stressed the importance of side effects in clinical trials of
antidepressants. They can tip patients off to the fact that they have been
given the real drug rather than a placebo, leading them to both expect and
experience greater improvement than patients who have been given placebos.
Sometimes placebos also produce side effects, especially those that the
patients expect. This was first demonstrated in a study of headaches as a side
effect of lumbar puncture, a clinical procedure used to administer anaesthetics
or to extract spinal fluid for diagnostic purposes. The researchers performed
lumbar punctures on two groups of patients, but only warned one of them that
headaches were a possible side effect. Approximately half of the subjects who
were forewarned subsequently reported headaches, as compared to only one of the
control subjects, suggesting that this commonly reported consequence of lumbar
puncture may be a nocebo effect.49
A similar result
was reported in a multi-centre clinical trial of aspirin as a treatment for
angina. Two of the three institutions participating in the study listed gastric
irritation in their list of possible side effects; the third centre did not.
The results of the study showed that significantly more patients reported
gastrointestinal symptoms in the institutions that had listed gastric
irritation on the informed-consent from than in the centre that had made no
mention of this possibility.50 The results of these studies
present doctors with an ethical dilemma. On one hand, we have the requirement
for informed consent, according to which we should warn people in advance of
the possible side effects they might experience. On the other hand, warning
them may produce side effects that would not otherwise have occurred. So what
should we do? I really do not have a solution to this dilemma, but it is
certainly a problem that deserves - but has not as yet received - careful
consideration.
In a particularly
dramatic case of placebo-induced side effects, doctors at a hospital in
Jackson, Mississippi, treated a young man who came into the emergency room,
said to the receptionist, ‘Help me, I took all my pills’ and then collapsed to
the floor, dropping an empty prescription container. His blood pressure was
abnormally low, and he was treated with intravenous fluids, which brought it
back to within a normal range. The prescription bottle bore a label indicating that
the medication was part of a clinical trial of antidepressants. Further
investigation revealed that he had been assigned to the placebo group. He had
overdosed on a placebo.51
Even more dramatic
are reports of death by placebo, although they remain controversial. In 1942,
Walter Bradford Cannon, a distinguished physiologist and chair of the
Department of Physiology at the Harvard Medical School, wrote an article
entitled ‘“Voodoo” Death’, in which he recounted numerous instances in which
people in tribal societies were reported to have died after having been cursed
or having violated strict taboos.52 Cannon offered
the explanation that voodoo death, if real, might be caused by intense fear.
The victims literally died of fright. I cannot say I am convinced that voodoo
death occurs. I am sceptical about its reality, primarily because the evidence
for it is anecdotal, but Cannon’s physiological explanation of how the fear of
death might cause a person to die remains valid. Writing on the 60th
anniversary of the article’s publication, Esther Sternberg, Director of the
Integrative Neural Immune Program at the National Institute of Mental Health in
the US, concluded that it was remarkably accurate and had withstood the test of
time.53
Does the production
of side effects by placebo undermine my argument that the perception of these
effects can lead patients to realize that they have been given the real drug,
thereby producing an enhanced placebo effect? Not really. Although placebos can
induce side effects, antidepressants produce signifi - cantly more of them. In
one clinical trial, for example, 19 per cent of the patients given a placebo
reported adverse events, but 46 per cent reported side effects on an
antidepressant, and as I mentioned in Chapter 1, once you adjust for
drug-placebo differences in side effects, the difference in therapeutic
benefits is no longer significant, not even statistically.54 Some of the adverse events that
patients report may not be side effects at all. They might have occurred even
if the person had not been treated. That is why they are often called ‘adverse
events’ rather than ‘side effects’. But the difference in adverse events
between drug groups and placebo groups is most certainly an indication of
drug-induced side effects, and can easily explain the small drug-placebo
difference in improvement.
As I will discuss in
greater detail in the next chapter, placebo and nocebo effects are part of a
broader phenomenon - the tendency for people to experience what they expect to
experience.55 Is it possible
that negative expectancies can make people depressed? If so, it would help
explain the powerful effect of placebos in the treatment of depression, and it
would also point the way to understanding how to optimize treatment in clinical
settings.
In 1976, Aaron
Beck, a psychiatrist at the University of Pennsylvania, proposed a cognitive
theory of emotions and emotional disorders - a theory that was to become the
foundation for cognitive behavioural therapy for depression. According to Beck,
fear is produced by the anticipation of harm, joy by the expectancy of positive
events, and sadness by the sense that something important has for ever been
lost. As a consequence, overcoming fear and depression requires changing the
beliefs that have produced them.
The American
President Franklin Delano Roosevelt once said that ‘there is nothing to fear
but fear itself’. It was a wise conclusion, especially from the standpoint of
clinical psychology. Fear is indeed frightening. So much so that phobias -
irrational fears of situations that are not dangerous - can be generated and
maintained by the simple belief that one will experience intense fear. The
panic and anxiety that are aroused in these disorders can be a simple, but intense,
fear of fear.56
Just as fear is a
frightening experience, depression is depressing. It is a terrible state of
affairs, and many depressed people feel that they are trapped in it for ever.
There may be other circumstances behind their depression, but depression about
depression is certainly an important component.57 Bringing their depression to an end requires
instilling a sense of hope - a belief that their depression will not last for
ever. For people who are depressed about depression, this change in expectation
may be an essential component of effective treatment. If depression is a nocebo
effect, then its treatment requires a positive placebo effect.
The evidence I have
reviewed in this chapter indicates that placebos work for a wide variety of
conditions. They can produce both positive and negative effects. They affect
the body as well as the mind. They can be as strong as potent medications, and
their effects can be lasting. We have also seen that placebos can produce
negative effects. Furthermore, the nocebo effect may be an important factor in
clinical depression - at least for some depressed people. For this reason,
understanding the placebo effect is essential to understanding how to treat
depression effectively. How do inert substances produce both therapeutic and
detrimental effects? Chapter 6 provides an answer to this question.
How Placebos Work
If we are to harness
the placebo effect and make use of it in clinical practice, we first have to
understand how it works. A number of factors have been proposed as explanations
of the placebo effect. These include the relationship between doctors and
patients, the patient’s beliefs and expectations, the production of opiates in
the brain, and a phenomenon called classical conditioning, in which people come
to associate pills and injections with therapeutic effects, just as Pavlov’s
dogs came to associate the sound of a bell with the presentation of food. In
this chapter we look at how all of these processes combine to produce placebo
effects, and we consider their implications for the treatment of depression.
You might find some
of this material tough going, and if you are willing to take my word for the
significance of these factors, you could just skip over these parts. But I
thought it important to document my claims about how placebos work. Just as I
have documented my claim that most of the antidepressant drug response is a
placebo effect and that the remainder is in all likelihood an enhanced placebo
effect, so here, too, I present the details of the research upon which my
conclusions about the way placebos work are based.
What happens when you
go to your primary-care physician? Do you feel that he is engaged with you?
Does she make frequent eye contact? Does he ask enough questions, and does she
seem to listen when you answer them? Or does he seem impatient and rushed,
spending more time looking at a laptop computer than at you? The way in which a
clinician interacts with her patients can affect the outcome of treatment - and
not just of treatment for mental-health problems, but treatment for physical
conditions as well.1
Perhaps you have
experienced the sense of well-being that a good ‘therapeutic relationship’
engenders. I know that I have. I had a doctor in New Jersey who had the most
wonderful bedside manner. Dr Doubek - I called her Marnie - looked me in the
eye when I spoke. She listened, she nodded, she showed concern. She did not
seem the least bit hurried or rushed. And I do not know if she is aware of
this, but at least once during each visit she touched me briefly on the arm
while talking to me. I felt cared for, understood.
I trusted Marnie
when I was her patient, and I still do. Two years after leaving New Jersey and
moving to England, my wife and I wondered about the meaning of some medical
test results we had obtained. We phoned Marnie to help us understand them, and
even on the phone, with people who had not been her patients for more than two
years, Marnie was forthcoming, patient and helpful. I only wish I could
videotape the way in which she conducts her clinical sessions and have the DVD
shown to all medical-school students.
I can’t call
Marnie’s style of interacting with patients a placebo effect, because as far as
I know none of the treatments she gave me were placebos. But it did make me
feel better, and some of the research I describe in this chapter indicates that
it can also promote wellness. For want of a better term, I will call this the
‘Marnie effect’. The Marnie effect is the enhancement of treatment outcome that
is produced by enhancing the therapeutic relationship.
The relationship between
the medical practitioner and the patient is, without any doubt, an important
component of the placebo effect. Recently I was able to verify that hypothesis
scientifically as part of a research team led by Ted Kaptchuk, an Associate
Professor of Medicine at the Harvard University Medical School.2 Kaptchuk is the most unusual
associate professor at Harvard - or at any other university, for that matter.
Not only does he not have a PhD or MD, but he does not even have a master’s
degree. Instead, after graduating from Columbia University with a bachelor’s
degree, he went to Macao, where he obtained an OMD - a Doctor of Oriental
Medicine degree.
Kaptchuk returned
from China a proponent of acupuncture and wrote The Web That
Has No Weaver, the classic explanation of Chinese medicine for Western
readers.3 But over time he
came to wonder whether the effects of acupuncture might be at least partly due
to the placebo effect. To answer that question, he taught himself how to design
research studies, and he did so well enough to obtain funding from the National
Institutes of Health and publish more than 100 articles in leading medical
journals. No wonder Harvard saw fit to hire and promote him, despite his rather
unusual academic credentials.
Like real
medicines, placebos show a dose-response relationship. The more you take, the
greater the effect. Taking placebo pills four times a day provides greater
relief from ulcers than taking only two a day,4 and people who take their heart
medication as prescribed live longer than those who do not, even if what they
are taking is really a placebo that they have been given in a clinical trial.5 Kaptchuk wondered whether the
‘dose’ of the therapeutic relationship could be altered just like the dose of a
medication and, if so, whether this might affect the effectiveness of
treatment. So he designed a study to find out and invited me to be one of the
researchers.
We gave patients
suffering from irritable bowel syndrome three ‘doses’ of a therapeutic
relationship. The lowest dose was no relationship with the medical practitioner
and no treatment at all. These patients were simply assessed and put on a
waiting list, with the promise that they would receive treatment some weeks
later. Another group of patients was given placebo acupuncture (using the fake
needle that does not prick the skin, as I described in Chapter 5) with a ‘low
dose’ of the therapeutic relationship. These patients were seen by a licensed
acupuncturist who told them that because this was a scientific study, he had
been instructed not to converse with them. A third group of patients received
the ‘high-dose’ therapeutic relationship. Prior to starting the fake
acupuncture treatment, the acupuncturist interviewed these patients for 45
minutes. He was warm and friendly with them, saying things like: ‘I can understand
how difficult your condition must be for you.’ He took time to ponder the
treatment plan and instilled a positive expectation by saying, ‘I have had much
positive experience treating irritable bowel syndrome and look forward to
demonstrating that acupuncture is a valuable treatment in this trial.’
The results of this
study showed that we were right about the effects of the therapeutic
relationship. Six weeks after the beginning of treatment, patients given an
enhanced therapeutic relationship reported significantly greater symptom
reduction and better quality of life than those given the low-dose
relationship, despite the fact that the difference in treatment was limited to
the initial interview. Those in the wait-list group showed the least improvement
of all.6
Our study showed
that enhancing the therapeutic relationship boosts the placebo effect. Other
studies have shown that the same thing happens when real treatments are
delivered within the context of a caring relationship. When a doctor is warm,
friendly, reassuring and confident in the effectiveness of the treatment,
patients show greater symptom reduction and recover from illnesses more
quickly.7
How is it that the
quality of the therapeutic relationship can enhance improvement, not only in a
psychological condition like depression, but also in a physical disorder like
irritable bowel syndrome? A clue to the answer to this question lies in one of
my all-time favourite studies. You may have read E. M. Forster’s book A Room with a View or seen the film that was based on it.
As it turns out, having a room with a view not only makes a holiday more
pleasant, but can also improve your health. Roger Ulrich, a researcher at the
University of Delaware, divided patients who had just had gall-bladder surgery
into two groups.8 Patients in one
group were given rooms with windows looking out over a park-like setting with
trees and plants. The other patients were assigned rooms with views of a brick
wall. Those given the rooms with the view of trees and plants required
significantly less pain medication and were discharged from the hospital sooner
than the others. Their nurses were more likely to describe them as doing well
and being in good spirits. Patients in the rooms facing the brick wall needed
more medication, took longer to be discharged and were described as upset and
needing encouragement. In other words, feeling good psychologically makes you
feel good physically. A warm and caring therapeutic relationship feels good. It
leads the patient to feel hopeful rather than hopeless. It facilitates an
expectation for improvement and that may, at least in part, explain its ability
to facilitate healing.
The ability of
emotions to affect health, for better and for worse, has been shown in other
studies as well. Negative emotions, such as those induced by stress, can worsen
physical health. They can increase blood pressure, impair the functioning of
the immune system and increase the risk of death from heart disease.9 There has been less research on the
health benefits of positive emotions, but the research that has been done
suggests that it can have curative effects. For example, people who are
generally optimistic have lower blood pressure, better immune function and
recover better from heart surgery. There is even some evidence that survival
from cancer might be affected by emotional well-being.10 So maybe Mr Wright’s response to
placebo treatment for cancer, in the case study I described in Chapter 5, was
not merely a coincidence.
THE SPECIFICS OF
‘NON-SPECIFIC’ EFFECTS
Although the
therapeutic relationship and positive emotions are clearly important, there are
many instances of the placebo effect that they cannot explain. They cannot, for
example, explain the effect of placebos in research settings in which students
or other healthy volunteers have been asked to participate in return for money
or course credit. In these studies there is no therapeutic relationship. Most
importantly, emotions cannot explain the specificity of the placebo effect.
If you look in the
medical literature, you will often see the term ‘placebo’ defined as a
‘non-specific’ treatment. What does it mean to say that a treatment is not
specific? It could mean that the treatment is effective for many different
disorders, rather than for only one particular condition. In this sense,
placebos are indeed non-specific. Besides depression, placebos have been shown
to affect anxiety, pain, ulcers, irritable bowel syndrome, Parkinson’s disease,
angina, autoimmune diseases, Alzheimer’s disease, rheumatoid arthritis, asthma,
gastric function, sexual dysfunction and skin conditions.11
We know this from the thousands of studies in which placebos have been used as
control conditions, against which the effects of medication have been
evaluated, and from studies that were specifically designed to assess the
placebo effect.
Although placebo
effects are generally referred to as non-specific, there is also a sense in
which they are very specific. The effect of the placebo is specific to the
beliefs that people have about the substance they are ingesting. Placebo
morphine, for example, reduces pain, whereas placebo antidepressants reduce
depression. Even the side effects that people report when given a placebo tend
to be the same side effects that are produced by the real drug.12
In other words, the effect of a placebo is specific to the effect that the
person expects it to have. When given placebo stimulants like decaffeinated
coffee (presented as regular coffee), people feel more alert, and their heart
rate and blood pressure may go up, but when given placebo tranquillizers, they
feel more calm and relaxed, and their heart rate and blood pressure go down.13 These opposite effects have been
produced in studies with healthy volunteers as subjects. They were conducted in
sterile laboratory settings, in which there was no therapeutic relationship at
all. Furthermore, there is no reason to think that the healthy participants in
these studies have any particular feelings about being given one or another
type of placebo. The placebo effects found in these studies cannot be explained
by the therapeutic relationship or by the positive emotional state it induces,
but they can be explained by the subjects’ beliefs and expectations about what
they have been given. Some years ago, I coined the term ‘response expectancy’
to denote the expectations that are evoked by placebos, and this has since
become an accepted factor in theories of the placebo effect.14
If placebo effects
depended completely on the therapeutic relationship and patients’ emotional
states, it would not be possible for the same person to show placebo effects
and nocebo effects at the same time. But they do. Sometimes the same person
reports both therapeutic benefits and side effects from the same placebo.15 Sometimes the more negative side
effects they have experienced, the better they feel. That can happen because
the side effects might convince them that they have been given a potent
medication. Maybe their improvement was generated by their happiness over
receiving what they believe to be an effective treatment for their condition,
but this certainly would not explain their experience of side effects.
My former student
Guy Montgomery, who is now a researcher at the Mount Sinai School of Medicine
in New York City, demonstrated experimentally that placebo pain reduction
cannot be completely explained by the patient’s emotional state - or by any
other factor that should affect a person’s whole body instead of just part of
it. He put a placebo cream on the index finger of one hand of his subjects and
nothing at all on their other hand. Then he induced pain by putting heavy
weights on the subjects’ index fingers. He measured the placebo effect as the
difference in the pain that the subjects felt in the finger on which he had put
the placebo cream and the pain they felt in the untreated finger. Sometimes he
put the weight on both fingers at the same time. At other times he tested each
hand separately. That did not make a difference. He got the same placebo effect,
regardless of whether he put the weight on both hands simultaneously or whether
he did so sequentially.16 Now, if placebo effects were
produced by inducing positive emotions, or by reducing anxiety as has also been
hypothesized,17 then he should
not have gotten a placebo effect when he put the weight on both hands at
exactly the same time. Fingers do not feel anxious or happy; people do. So any
effect on pain produced by their emotional state should have occurred in the
fingers of both hands.
When Montgomery and
I published our article, we thought we had disproven another theory of placebo
effects - the theory that placebo effects are produced by the release of
endorphins in the brain. In 1978 researchers at the University of California in
San Francisco discovered that when placebos reduce pain, they may stimulate the
release of endorphins.18 Endorphins, the existence of which
had only been discovered a few years earlier, are opioids that are produced
naturally by the brain. Just like the opiates that are derived from opium -
morphine and codeine, for example - endorphins reduce the sensation of pain.
The University of California researchers reasoned that if placebos can mimic
the effects of opiate drugs, maybe they do so by stimu - lating the release of
the brain’s endogenous opioids.
To test their
hypothesis, the researchers gave placebo morphine intravenously to a group of
patients who had just undergone dental surgery. An hour later they gave the
patients a substance called naloxone. Naloxone is an opiate antagonist, which
means that it blocks the pain-reducing effects of morphine and other opiates.
In the California study, naloxone cancelled the pain-reducing effect of the
placebo. This finding led the researchers to conclude that endorphins must have
been involved in the production of the placebo effect in their post-surgical
patients, a conclusion that has since been confirmed more directly by scanning
people’s brains during placebo treatment.19
Montgomery and I
assumed that the release of endorphins in the brain would have general global
effects throughout the entire body. It could not affect the perception of pain
in just one part of the body, without affecting the rest of the body. Others
shared our opinion, including Howard Fields at the University of California,
one of the authors of the original naloxone study. But it turned out that we
were wrong. Fabrizio Benedetti and his colleagues at the University of Turin
Medical School repeated our study. Only this time he also assessed the effects
of hidden infusions of naloxone, just as the University of California
researchers had done. The results of Benedetti’s study surprised everyone. He
found a placebo effect despite having applied the pain stimulus to treated and
untreated parts of the body simultaneously, just as Montgomery and I had found.
That in itself was not surprising, but he also found that naloxone abolished
this placebo effect completely. It seems that when expectancies of reduced pain
lead the brain to release endorphins, these endogenous opiates can act on the
specific part of the body towards which the expectancy is directed. I think it
is safe to say that no one, with the possible exception of Benedetti and his
collaborators, would have thought that possible.20 Everyone else assumed that the
pain-reducing effect of endorphins was global, affecting the person’s entire
body, rather than targeting specific locations.
Classical Conditioning
It has now been well
established that expectancies play a central role in the production of placebo
effects.21 People’s
expectations of relief are not only correlated with how much benefit they
report, but also with changes in the brain activity associated with the
therapeutic benefit. These expectancies are formed and altered in many
different ways. Our beliefs are influenced by parents, teachers, friends and
colleagues, the advertisements we see on television and in newspapers and
magazines, news programmes and documentaries, books and magazine articles. But
the most effective way to alter beliefs and expectations is through direct
experience.
The process by
which experience affects our expectations is called classical or Pavlovian
conditioning. I assume you already know about Pavlovian conditioning, but a
brief review may nevertheless be useful. Classical conditioning was discovered
at the turn of the 20th century by the Russian scientist Ivan Pavlov.22 Pavlov was a distinguished physiologist
who had been awarded a Nobel Prize in 1904, not for his work on conditioning,
which he was just beginning and which few people knew of in 1904, but for his
research on the physiology of digestion in dogs.
In 1897 one of
Pavlov’s doctoral students discovered that after stimulating dogs to salivate
by having them smell a glass of carbon bisulphide, the dogs began to salivate
when presented with a glass of plain water. Eventually this discovery changed
the direction of Pavlov’s research. He began using many different stimuli to
induce salivation, including tuning forks, musical scales, tapping on a glass
and, most famously (although much later), ringing a bell. These stimuli were
paired with food in Pavlov’s studies. The food was called an unconditioned (or
unconditional) stimulus, because it evoked salivation as a reflex, even if
there had been no conditioning at all. The bell, tuning fork or musical scale
was termed a conditioned (or conditional) stimulus, because it provoked
salivation only after it had been associated with food.
The 1897 study in
which Pavlov’s student substituted a glass of water for the carbon bisulphide
that had been used to stimulate the dogs to salivate shows the relevance of
classical conditioning to the placebo effect. The glass of water was a placebo.
Although it was inert, it looked exactly like the substance that had led the
dogs to salivate.
Here then is the
classical conditioning account of the placebo effect. People experience getting
better after having been given active medications. These medications are always
administered in some kind of vehicle - in a pill, a capsule or by injection.
Eventually the pills, capsules and injections become associated with the
effects of the drug and are able to reproduce those effects as ‘conditioned
responses’.
Some years ago a
team of Australian researchers conducted an ingenious series of studies showing
how Pavlovian conditioning could strengthen the placebo effect.23 They told the subjects in their
study that they were testing a powerful fast-acting analgesic cream, which was
actually a placebo. Then they repeatedly stimulated the subject’s arms with a
pain generator that drives positive potassium ions into the skin, causing a painful
cramping sensation. Sometimes the arm had been treated with the placebo cream;
sometimes it had not. To strengthen the placebo effect, the experimenters
surreptitiously lowered the intensity of the pain stimulus whenever the placebo
cream had been applied. Then they tested the effect of this conditioning
procedure by turning the intensity of the pain generator back up to its
original level, so that exactly the same level of stimulation would be used,
regardless of whether or not the placebo had been applied. What they found was
that this conditioning procedure increased the placebo effect substantially.
The subjects who had experienced reduced stimulation, but without knowing that
the intensity had been reduced, later reported significantly more placebo pain
reduction than a control group that had not undergone this conditioning
procedure - this despite the fact that the intensity of the pain generator had
been turned back up to full level when the effect of the conditioning procedure
was tested.
In a later study,
my colleagues and I showed that we could gain an exquisite degree of control
over experienced levels of pain by using this conditioning procedure.24 We dabbed a liquid mixture from a
medicinal bottle bearing the label ‘Trivaricaine-A’ on to one area of each
person’s arm, and we applied liquid from a bottle labelled ‘Trivaricaine-B’ to
a different part of the arm. We told people that these bottles contained
different strengths of the same topical anaesthetic and that we were testing
their efficacy. Of course, both liquids were placebos. (I had been tempted to
label our placebo ‘Prevaricaine’, but my colleagues talked me out of it.) After
the placebos had been applied and given time to take effect, we administered
pain stimulation to each of the two areas on the arm. We also stimulated a
third area of the arm, on which we had applied plain water.
During our
conditioning procedure, without the subject knowing it, we manipulated the
intensity of the pain stimulus that we applied to each area. We administered an
intensely painful stimulus to the area where we had put plain water, slightly
less intense stimulation to the Trivaricaine-B area and much lower intensity to
the Trivaricaine-A area. Then, to test the effects of this conditioning
procedure, we applied the same level of pain to all three areas. As we had
expected, subjects reported the greatest amount of pain in the control area
where we had applied plain water, less pain in the Trivaricaine-B area and even
less in the Trivaricaine-A area.
You might suspect
that the subjects in these conditioning studies might have been lying to the
experimenters - just telling us what we wanted to hear. But we now know that
this is not the case. Tor Wager used this conditioning procedure before he
scanned the brains of subjects while they were given painful stimulation with
and without the benefit of the placebo to which they had been conditioned.25 The subjects not only reported
experiencing less pain, but they also showed reduced activity in the pain
network of the brain.
Expectancy and
Conditioning
For many years there
was a debate in the scientific literature about whether placebo effects are
produced by conditioning or by expectancy. Now the answer seems as clear as
Pavlov’s bell. Both factors are involved. Specifically, conditioning is one of
the means by which expectancies are produced and altered.26 After repeatedly being given food
just after hearing a bell ring, the dog comes to expect to be fed whenever it
hears the bell. After successful treatments with active drugs, we come to
expect drugs to have positive effects. We can form expectations like this even
without direct experiences of this sort - for example, by being told of the
effectiveness of a medication - but direct experience (that is, conditioning)
is the most convincing source of information.27
Guy Montgomery and
I confirmed the role of expectancy in conditioned placebo effects in a study
that we conducted while he was working on his doctoral dissertation under my
supervision at the University of Connecticut.28 We repeated the conditioning
procedures that the Australian researchers had developed, but we added a new
twist. In addition to having subjects who did not know that we were turning
down the level of the pain stimulus during the conditioning trials, we also ran
a group in which we told people that we were turning down the stimulus
intensity. Our idea was that this group of people would have the same classical
conditioning experience, in which pain reduction would be paired with the
placebo tincture, but they would know that the reduced pain they were feeling
was not due to the placebo. We reasoned that if conditioning were an automatic
process that does not depend on people’s expectancies, then even this
‘informed’ group should show the conditioning effect by experiencing a greater
placebo effect when we turned the pain generator back up to full intensity. On
the other hand, if the effect of conditioning occurs because people come to
expect less pain when given the placebo, then the ‘informed’ group should not
benefit from the conditioning procedure.
The results of our
study clearly established that conditioning enhanced the placebo effect by
changing people’s expectations. As had the Australian researchers, we found
that conditioning increased the placebo effect for the subjects that we had
kept in the dark about our manipulation. They came to expect less pain, and
they subsequently experienced less pain. But conditioning had no effect at all
on the subjects who were told that we were lowering the intensity of the pain
stimulus. Knowing that we had lowered the stimulus intensity, they did not come
to expect less pain where the placebo had been applied, and since they did not
expect less pain, they did not experience it when the intensity was turned up
again.
Researchers at the
University of Manchester recently replicated our study and used an EEG to
record their subjects’ brain activity.29 Similar to our results, they found
that lowering the intensity of the pain stimulus enhanced the subsequent
placebo effect on self-reported pain, but only if the subjects did not know
that the stimulus intensity had been reduced during the conditioning session.
They also showed that this effect was not just because the subjects were
telling the experimenters what they wanted to hear. Instead, the reports of
reduced pain were accompanied by reductions in brain activity.
I am tempted to
conclude that the only direct effect of conditioning is to change expectancies,
and that it never has automatic effects that aren’t based on what the person
believes. But that would be going too far. Classical conditioning can be seen
in organisms as simple as the California sea slug, and I would be very
reluctant to attribute thought processes to anything with such a simple nervous
system. People have expectations, and I am convinced that dogs do as well, but
I draw the line at slugs. Consciousness most certainly evolved from simpler
unconscious processes, and Pavlovian conditioning is one of those processes. In
lower organisms the effect of conditioning on behaviour is direct. In higher
organisms, conditioning provides information that can be used to decide on a
course of behaviour.
Still, there seem
to be some vestiges of automatic conditioning effects that affect the placebo
response and are not based on expectancy. Consistent with the result of the
study I did with Guy Montgomery, Fabrizio Benedetti and his colleagues have
shown that conditioned placebo effects on conscious experiences like pain
depend on people’s expectations, but they also found a conditioning effect on
hormonal secretion that could not be blocked by preventing a change in
expectancy.30 Automatic conditioning
effects like these are the exception rather than the rule. They seem to be
limited to unconscious processes like hormone secretion. The effects of
conditioning on conscious processes like pain depend on people’s expectations.
HARNESSING THE PLACEBO
EFFECT IN CLINICAL PRACTICE
During the 1980s the
National Institute for Mental Health (NIMH) in the United States sponsored a
massive, multi-centred research programme to evaluate the effectiveness of
antidepressants and psychotherapy in the treatment of depression.31
Before beginning treatment, each patient was asked the following question:
‘What is likely to happen as a result of your treatment?’ They were asked to
respond to this question on a five-point scale, on which low expectancy for
improvement was represented by the sentence ‘I don’t expect to feel any
different’ and high expectancy was represented by ‘I expect to feel completely
better’. Patients’ answers to this question predicted their therapeutic
outcome. Those who expected to feel better improved the most, and those who did
not expect to feel better got the least benefit from treatment. Furthermore,
the effect of expectancy on treatment outcome was independent of which
treatment they had been given. Regardless of whether they had been treated with
antidepressant medication, psychotherapy or a placebo, patients who expected to
get better showed the most improvement.32
One lesson to learn
from the findings of the NIMH Treatment of Depression Collaborative Research
Program is that people who are depressed need to be convinced that the
treatment they are being offered - whatever it is - is effective and that it
offers them hope for what they may until then have considered a hopeless
situation.33 Some people
come into treatment with positive expectations, but others do not, and unless
the clinician puts effort into changing negative expectations at the outset,
treatment is not likely to be very effective. This is yet another reason for
concluding that the effects of medication on depression are placebo effects. If
the effect of these drugs were not at least partly a placebo effect, they would
work - like antibiotics and hypoglycaemics - regardless of patients’
expectations.
As I discussed in
Chapter 5, depression is partly a nocebo effect, in the sense that it can be
produced by negative expectations about oneself and the world.34 The way in which these negative
expectations develop and produce their negative effects provides some clues as
to how they can be reversed. Expectancy effects grow, feeding upon themselves.
One reason this happens is that our subjective states - our feelings, moods and
sensations - are in constant flux, changing from day to day and from moment to
moment. The effects of these fluctuations depend on how we interpret them, and
our interpretations depend on our beliefs and expectations. When we expect to
feel worse, we tend to notice random small negative changes and interpret them
as evidence that we are in fact getting worse. This interpretation makes us
actually feel worse, and it strengthens the belief that we are getting worse,
leading to a vicious cycle in which our expectations and negative emotions feed
on each other, cascading into a full-blown depressive episode. This is the
process by which relapse can occur when someone is taken off antidepressants.
Positive expectancies have the opposite effect. They can set in motion a benign
cycle, in which random fluctuations in mood and well-being are interpreted as
evidence of treatment effectiveness, thereby instilling a further sense of hope
and countering the feelings of hopelessness that are so central to clinical
depression.
In 1998 a group of
researchers at Columbia University provided evidence for this snowball effect.35 Recall that at the beginning of
most clinical trials, all patients are given placebos for a week or two in what
is called a placebo run-in period. The Columbia researchers looked at what
happened during this run-in period and found that the patients who improved
during it were the ones most likely to improve later in the trial, regardless
of whether they were then given antidepressants or placebos. In a subsequent
study, researchers at the University of California at Los Angeles (UCLA)
confirmed these results by identifying changes in regional brain activity
during the placebo run-in period that predicted improvement when patients were
given medication.36
Positive
expectations can also backfire, and clinicians need to be careful about the
beliefs they foster. The key to preventing this is to understand that
expectancies of improvement have different facets and that these different
kinds of expectancy can function independently.37 One of these facets is the amount of change the
person expects. I might expect a complete cure, or I might expect no change at
all. This is the kind of expectancy that was correlated with improvement in the
NIMH Treatment of Depression Collaborative Research Program. A second aspect of
a person’s expectancy is the confidence with which it is held. I may be
absolutely certain that I will change, or I might be very unsure. This is the
kind of expectancy we alter when we tell people in a clinical trial that we
might give them a placebo. As we have seen, lowering expectancy in this way
decreases the effect of treatment.38
But there is also a
third aspect to our expectancies for improvement, and that is the speed with
which the change is expected. I might expect change to occur almost
immediately, or I might expect it to happen gradually over time. This is the
aspect of our expectations that can have paradoxical effects. When people have
unrealistic expectations, when they expect too much change to occur too
quickly, their expectations are likely to be shattered.
There is yet one
other aspect of expectancy to which we need to attend. Patients might expect
change to occur automatically, without them having to do anything to bring it
about. This is the expectation fostered by drug treatment. One does not expect
to have to do anything but take the drug for it to have its effect.
Alternatively, one might expect to have to work actively to bring change about,
rather than to wait passively for it to occur. Data from the NIMH study showed
that when patients expected treatment to work, they also got more involved in
working with the clinician to help bring those changes about, and the more
actively involved they became with the treatment process, the more they
improved.
Here then are the
kinds of expectations that are most likely to lead to therapeutic improvement
and that should be fostered by clinicians. To maximize therapeutic outcome, it
is best to be confident in the effectiveness of treatment, to expect
substantial change, but also to expect that change to occur gradually. The
changes are likely to be subtle at first, and to increase over time. It is also
helpful to understand that change is not automatic; one has to work to bring it
about. These are the kinds of expectations that are best suited to interrupting
vicious cycles and replacing them with benign ones.
As we have seen,
expectancy is not the only factor that encourages placebo effects. There is
also the effect of the therapeutic relationship - what I have called the Marnie
effect. A caring therapeutic relationship enhances the patient’s confidence,
and in so doing also fosters positive expectations. But it can also affect
patients’ well-being in ways that are independent of expectancy. A positive
therapeutic relationship feels good, and feeling good counters depression and
may also have more general health benefits.
Is the Marnie
effect too much to ask for in primary care? Doctors are busy. They have large
caseloads. The amount of time they have available for each patient is limited,
and making more time available would cost money. Still, this might be money
well spent, given the potential benefits for health and well-being that it
could produce. In the long run it might even be cost-effective. It has the
potential to reduce the number of primary-care visits that patients need and
the number of referrals that need to be made.
Enhancing expectations
and strengthening the therapeutic relationship might enhance the outcome of
treatment. But what treatment? Antidepressants may be nothing more than active
placebos, producing side effects through chemical means and therapeutic effects
only through psychological means. In the next chapter we consider the various
options that are available for the treatment of depression. As we shall see,
some of these treatments go well beyond the Marnie effect in the treatment of
clinical depression.
Beyond Antidepressants
We are faced with a
dilemma. Millions of people suffer from depression. Many of them get better
when treated with antidepressants, whereas left untreated, they do not show
much improvement at all.1 The problem is that antidepressants
have turned out to be not much more effective than placebos.
The placebo effect
in the treatment of depression is very large, and it is likely to be even
larger in clinical practice than it is in clinical trials. In clinical trials,
people are told that they might be getting a placebo, and this knowledge diminishes
the placebo effect.2 In clinical
practice, on the other hand, people know they are getting an active medication
and, trusting their doctors, they are more confident that they will improve.
So what are we to
do? Perhaps we should continue prescribing antidepressants, even if they are
placebos, given that they are very effective placebos. As one psychiatrist put
it, ‘It matters little whether the patient responds because of a placebo effect
or the specific pharmacological actions of the drug, as long as he/she gets
better’.3 But there is a
problem with this solution. Antidepressants may be placebos, but unlike the
placebos that are used in almost all clinical trials, they are not inert.
Instead they are active drugs, and as such they produce effects that are not
placebo effects. The problem is that many of these real drug effects are
harmful side effects rather than beneficial therapeutic effects.
The side effects of
antidepressants are a serious problem. Many depressed patients find them so
intolerable that they stop taking their medication. This leads many of them to
drop out of clinical trials within a few weeks after beginning treatment, which
is why most of these trials are short, lasting only between four and eight
weeks. Drug companies have directed most of their efforts not towards finding
more effective antidepressants - differences in effectiveness between one
antidepressant and another are clinically insignificant - but towards
developing drugs that have fewer side effects and will therefore be more
tolerable. This is the advantage of SSRIs and other ‘new-generation’
antidepressants over older drugs that were used to treat depression. The new
drugs are not more effective, but they do have fewer side effects.
Although SSRIs have
fewer side effects than older antidepressants, the list of adverse events is
still substantial - substantial enough to preclude their use as ‘active
placebos’. Among the reported side effects of SSRIs, Eli Lilly (the
manufacturer of Prozac) lists the following in their official Summary of
Product Characteristics: sexual dysfunction, headaches, nausea, vomiting,
insomnia, drowsiness, diarrhoea, sweating, dry mouth, seizures, mania, anxiety,
impaired concentration, panic attacks, fatigue, twitching, tremors, dizziness,
anorexia, dyspepsia, difficulty swallowing, chills, hallucinations, confusion,
agitation, photosensitivity, urinary retention, frequent urination, blurred vision,
hair loss, pain in the joints, hypoglycaemia, rashes and serious systemic
events involving the skin, kidneys, liver or lungs. Furthermore, these are only
the more common side effects that have been associated with SSRIs. Lilly
reports other undesirable effects, such as hepatitis and haemorrhages, as
occurring ‘rarely’.
Each of these side
effects is experienced by only a minority of patients taking the drugs. About
15 per cent of patients taking SSRIs report headaches, and the same number
complain of nausea. Diarrhoea, dizziness and insomnia are reported by 10 per
cent of patients on SSRIs. But while only a minority report any particular side
effect, the number of patients who report suffering from at least one of them
is quite high, ranging from half of the patients to the vast majority of them,
depending on how these adverse events are assessed.4
The risk of
potentially serious side effects should be enough to preclude the prescription
of antidepressants for their placebo benefit, but this is not the only hazard
associated with these medications. On 19 July 2006 the FDA issued a
public-health advisory warning that, when taken in conjunction with other drugs
that can affect serotonin levels, antidepressants can induce a life-threatening
disorder called the ‘serotonin syndrome’.5
The serotonin syndrome is caused by an excess of serotonin in a person’s body.
One way of inducing
the serotonin syndrome is to take more than one antidepressant at the same
time, but it has also been associated with the concurrent use of other drugs,
including over-the-counter headache remedies and cough suppressants. Other
drugs that have been implicated in producing this potentially fatal condition
when taken together with antidepressants include analgesics, antibiotics,
herbal medications, appetite suppressants and street drugs like ecstasy,
cocaine and LSD.6 Symptoms of
serotonin syndrome include restlessness, hallucinations, loss of coordination,
a racing heart, rapid changes in blood pressure, fever, nausea, vomiting and
diarrhoea.
Suicidal thoughts
are one of the symptoms of depression. Paradoxically, one of the
best-publicized dangers of SSRIs is their potential to increase the risk of
suicide. This heightened risk is especially well established for children,
adolescents and young adults. In their most recent analysis of the data, the
FDA concluded that, when compared to placebos, SSRIs double the risk of
suicidal thoughts and behaviour in depressed patients up to the age of 24.7 There also seems to be an increased
risk for people who are older than 24, but the interpretation of these data is
still disputed.8
Not only has the
connection between SSRIs and suicide been well established, but we also have
some idea how SSRIs might produce this increased risk. The American
psychiatrist Peter Breggin has documented how SSRIs can provoke an agitated,
restless state called akathisia, which some people describe as feeling like
jumping out of their skin.9 It is often in this state that people
on SSRIs become violent and aggressive towards themselves or others.
I first learned of
the akathisia connection on 2 February 2004, at the FDA hearing that resulted
in the addition of the ‘black box’ warning to SSRI labelling information. Along
with my colleague David Antonuccio, I had been invited to testify at the
hearing about the efficacy - or lack of efficacy - of SSRIs as a treatment for
childhood depression. It was there that I first heard the heart-wrenching
stories of parents whose children had committed suicide, of a 12-year-old boy
who had murdered his grandparents with a shotgun, and of a woman who had shot
her jaw off while taking SSRIs. It was also at that hearing that I first
learned of the clinical studies in which akathisia was turned on and off by
Prozac. In one of these studies, three patients, aged 25-47 years, who had
attempted suicide while on Prozac and then been taken off of the drug, were
given Prozac again to see what would happen. All three of them developed severe
akathisia and reported feeling suicidal again. The manic feelings subsided, as
did their suicidal thoughts, when the drug was discontinued again.10
WARNING: DO NOT
DISCONTINUE ANTIDEPRESSANTS WITHOUT CONSULTATION
Understandably,
learning that the benefits of antidepressants are largely due to the placebo
effect, some depressed patients may be tempted to stop taking their medication.
With this in mind, I have asked the publishers to highlight the following
warning in bold typeface. It is akin to the black-box warning about the
increased risk of suicide that is contained in the approved labelling for
antidepressants: Antidepressant medication should not be
discontinued without first discussing it with your doctor.
The reason for this
warning is that abrupt cessation of SSRIs produces withdrawal symptoms in about
20 per cent of patients. Symptoms of withdrawal from antidepressant medication
include gastrointestinal disturbances (abdominal cramping and pain, diarrhoea,
nausea and vomiting), flu-like symptoms, headaches, sleep disturbances,
dizziness, blurred vision, numbness, electric-shock sensations, twitches and
tremors. Abrupt withdrawal can also produce symptoms of depression and anxiety,
which can occur within hours of the first missed dose of the drug.11 Withdrawal symptoms are sometimes
mistaken for a relapse, leading patients to resume antidepressant medication
and to conclude that they need it in order to remain free of depression.
Technically, this is not considered ‘addiction’, but it does seem awfully
close.
If you are
currently taking an antidepressant drug, if you are happy with its effects, and
if side effects are not causing undue problems, you might be best advised to
continue taking it. As the saying goes, ‘If it ain’t broke, don’t fix it.’ On
the other hand, if the drug is not producing sufficient benefit or if you are
troubled by the side effects, you might consider alternative approaches to
managing depression. I discuss some of these alternatives later in this
chapter.
If you do decide to
discontinue drug treatment, talk to your doctor first. It will be important to
taper your medication gradually, rather than stopping abruptly. The book Coming Off Antidepressants by Joseph Glenmullen of the
Harvard Medical School is an excellent source of information on how to
discontinue antidepressant drug treatment.
If the placebo effect
in depression is so powerful, perhaps we should just prescribe inert placebos
to depressed patients. They have been tested in thousands of clinical trials,
they are the standard against which all other medications are evaluated, and
they are safe enough to be taken by pregnant women, small children, the infirm and
the elderly. You might think I am merely being facetious in suggesting this,
but it has been recommended seriously and appears to be practised frequently.
The British Medical Journal has published surveys in
which doctors in the US and Israel were asked whether they sometimes prescribed
placebos intentionally.12 Approximately half of them
responded that they did, mostly in the form of over-the-counter analgesics and
vitamins.
The obvious problem
with prescribing placebos is the fact that it generally entails deception. When
physicians prescribe placebos, they don’t tell their patients that the
treatment is a placebo.13 Instead, the
patients are led to believe that they are receiving an active treatment. This
raises a serious ethical question. Is it ethical to deceive patients if the
deception is likely to make them better?
Two NHS physicians,
Rudiger Pittrof and Ian Rubenstein, have argued that the use of placebos can be
ethically justifiable and that it can be done without - strictly speaking -
deceiving patients. The gist of their argument is that placebos work for some
conditions (notably depression) and that this makes it possible to remain
‘within the spirit of scientific, evidence-based medicine’ when prescribing
them. In fact, they suggest that it might be unethical to withhold placebo
treatment that has been shown to be effective. Even in conditions for which
placebos are not as effective as active medications - as in the treatment of
sexual dysfunction in men, for example - the side effects and dangers of drug
interactions could be avoided by prescribing placebos, and this might make
placebo treatment preferable to many patients. Pittrof and Rubenstein recommend
giving patients a choice between a possibly more effective treatment that has a
greater likelihood of side effects and a somewhat less effective treatment
(placebo) that has fewer side effects - without, of course, telling them that
it is a placebo.
As sympathetic as I
am to Pittrof and Rubenstein’s arguments, I remain unconvinced. It may be
possible to avoid technically lying to patients when administering placebos,
but that just makes the deception implicit rather than explicit. Patients are
still led to believe that they are getting a pharmacologically active
treatment, when in fact they are not.
Perhaps it is my
background as a psychotherapist that leads me to be concerned about the
widespread practice of deceptively giving patients placebos. As a therapist, I
learned that one of the principal factors in the success of treatment is the
relationship between the doctor and the patient. Trust is one of the central
components of the therapeutic relationship, but trust has to be earned. When it
is betrayed, it is lost. So my concern is as much practical as it is ethical.
When doctors deceive their patients, they violate their patients’ trust. In the
long run they will lose it and, in so doing, they will lose one of the most
effective weapons in their clinical arsenal.
When given in the guise
of active medications, placebos can produce powerful effects, but how potent
would they be if the patients knew they were taking placebos? Is it possible to
produce a placebo effect without deception?
In 1965, Lee Park
and Lino Covi, two young psychiatrists at the Johns Hopkins University
hospital, undertook a study that was aimed at answering this question.14 Their surprising conclusion was
that placebos can be given openly, without deception, and still be effective.
Park and Covi gave placebo pills to 15 psychiatric outpatients and told them
that the pills were placebos. More specifically, they told the patients: ‘Many
people with your kind of condition have . . . been helped by what are sometimes
called “sugar pills”, and we feel that a so-called sugar pill may help you,
too. Do you know what a sugar pill is? A sugar pill is a pill with no medicine
in it at all. I think this pill will help you as it has helped so many others.
Are you willing to try this pill?’
With instructions
like these, one might expect patients to become angry or insulted, to refuse to
take the pills or at least to feel sceptical, even if reluctant to express their
scepticism. We would certainly not expect them to improve. Even the researchers
who conducted the study did not expect to find much of an effect. ‘It was to
just be a very small pilot trial to learn if patients would actually go along
with us and to see if any subjects actually benefited,’ Lee Park recalls.
The researchers
were amazed by the results. All but one of the 15 patients agreed to take the
placebo pills. But did they actually take them? To find out, Park and Covi
counted how many pills were left at the end of the first week. The pill count
indicated that all 14 who had agreed to take the placebo pills had in fact
taken them as prescribed. More impressive, all of them reported feeling better
at the end of the study.
How did the placebo
produce improvement in these patients? To find out, Park and Covi asked them
what they thought about the pills they had been given. Eight of the patients
suspected that the clinicians had lied to them and that the pills contained
active medication. Three of these patients reported side effects that may have
encouraged their suspicion. One patient concluded that the pills could not have
been placebos because they worked better than medications that she had taken
previously. Other patients were sure that the pills were in fact placebos, just
as their doctors had told them they were. These patients also got better. In
fact, one patient who was afraid of getting addicted to active medication
expressed relief at having been given a placebo and asked to be allowed to continue
taking her sugar pills after the experiment was over.
The Park and Covi
study is certainly tantalizing, and it is a shame that no one has ever followed
up on it with further research, because it is also a flawed study, and it is
difficult to draw conclusions from it. The biggest problem is that there was no
control group. The patients might have improved just as much even if they had
not been given the placebo pill. Still, the fact that most of the patients
complied with the non-deceptive placebo treatment instructions, and that some
later attributed their improvement to having taken a ‘sugar pill’, suggests
that the use of placebos need not be deceptive in order to be effective.
In 1965, when Park
and Covi’s study was published, placebos were just becoming a standard feature
of medical research, and the general public was not as aware of them as they
are now. I may be wrong, but I suspect that patients today would not be as
amenable to the idea of taking a ‘sugar pill’ as they seem to have been then.
Still, there are rationales for knowingly taking placebos that might be
effective today. As I described in Chapter 6, classical conditioning is one of
the factors behind the placebo effect. Classical conditioning is the phenomenon
in which a neutral stimulus (such as a bell, buzzer or placebo pill) comes to
evoke a reaction that had been produced by something else (food or active
medication) with which it has been associated. Most of these conditioned
responses are due to the beliefs and expectations that are produced by the
conditioning process, but some of them are also automatic.15 They can occur even without the
person’s conscious awareness. So perhaps taking a placebo pill is a smart idea
after all, even if you know it is a placebo. The pill can function as a
conditioned stimulus - as it is called in the scientific literature -
triggering a therapeutic reaction because of your previous positive experience
with active medications.
It may indeed be
possible to give people placebos openly, without deceiving them, and still
obtain good results. But there is a good argument for not doing this: we don’t
have to. There are alternatives to the prescription of either antidepressant
drugs or placebos. These alternative treatments mobilize the placebo effect,
and some of them may do much more than this, but they carry neither the
side-effect risks of active drugs nor the ethical risks of deception. I explore
these alternatives in the rest of this chapter.
PSYCHOTHERAPY: THE
QUINTESSENTIAL PLACEBO
Of all the alternatives
to antidepressant medication, psychotherapy is the most thoroughly researched.
It has been the subject of hundreds of studies, which have been summarized in
scores of meta-analyses. Indeed, there have been so many meta-analyses of the
psychotherapy outcome research that there are even systematic reviews of the
meta-analyses - that is, reviews of the reviews.16 The results of these clinical
trials, meta-analyses and reviews point to one inescapable conclusion.
Psychotherapy works for the treatment of depression, and the benefits are
substantial. In head-to-head comparisons, in which the short-term effects of
psychotherapy and antidepressants are pitted against each other, psychotherapy
works as well as medication. This is true regardless of how depressed the
person is to begin with. It works for people who are moderately depressed,
those who are severely depressed and even for patients who are very severely
depressed.
Psychotherapy looks
even better when its long-term effectiveness is assessed.17 Formerly depressed patients are
far more likely to relapse and become depressed again after treatment with
antidepressants than they are after psychotherapy. As a result, psychotherapy
is significantly more effective than medication when measured some time after
treatment has ended, and the more time that has passed since the end of
treatment, the larger the difference between drugs and psychotherapy. This
long-term advantage of psychotherapy over medication is independent of the
severity of the depression. Psychotherapy outperforms antidepressants for
severely depressed patients as much as it does for those who are mildly or
moderately depressed.18
There are a number
of different psychotherapies for depression. The most common and thoroughly
researched of these is cognitive behavioural therapy, known as CBT for short.
As implied by its name, CBT has two components, a behavioural component and a
cognitive component. The behavioural component of CBT is emphasized during the
early stages of treatment, especially for severely depressed patients. It
focuses on planning daily life activities, with special attention to activities
that have the potential to provide pleasure and a sense of mastery and
accomplishment. The cognitive component of CBT is based on the premise that
emotions are not caused by the things that happen in our lives, but rather by
the way in which we interpret those events. In other words, it focuses on the
meanings that events have for us, and it is supposed to work by changing those
meanings. It involves examining and challenging the negative thoughts that may
promote and maintain depressed feelings - thoughts like ‘I am a failure’, ‘I’m
stupid’ or ‘no one will ever love me’. Depressed patients are asked to monitor
the thoughts that spontaneously pop into their minds, and then, together with
their therapists, they examine these conclusions, evaluate them logically and
test them. The therapist and the patient work together as if they were research
collaborators. They treat the patient’s negative thoughts as hypotheses that
can be tested and revised in the light of evidence and reason.
In the past, the
cognitive and behavioural components of CBT were referred to different types of
therapy - cognitive therapy and behaviour therapy. But it soon became clear
that there were few (if any) differences between them. When treating
depression, behaviour therapists worked on producing cognitive as well as
behavioural change, and cognitive therapists used behavioural as well as
cognitive techniques.19 The distinction between behaviour
therapy and cognitive therapy for depression was based on differences in theory
rather than practice, and it has now pretty much disappeared.
Although it has
received the most attention, CBT is not the only form of psychotherapy that is
effective for depression. Other psychological treatments include interpersonal
psychotherapy, short-term psychodynamic therapy and non-directive supportive
therapy. Interpersonal psychotherapy focuses on problems that arise in
interpersonal relationships, such as marital conflict, the loss of a loved one
and social isolation.20 Short-term psychodynamic therapy
focuses on acquiring insight and understanding of unresolved conflicts arising
from the person’s childhood. It is based on Freud’s psychoanalytic theory, but
requires only months, rather than the years it takes for a full psychoanalysis.21 Non-directive supportive therapy
provides a warm, supportive atmosphere in which the depressed person can
explore life issues in the presence of a caring professional. It is based on
the premise that people have within themselves the ability to work through
their psychological issues and to grow towards fulfilment and well-being. All
that they need is a caring context in which they can feel safe enough to
explore their inner world.22
Researchers
comparing the effectiveness of these various psychotherapies have found some
significant differences.23 In general, cognitive behavioural
treatments seem to be more effective than psychodynamic therapy, and
non-directive supportive therapy seems less effective than any of the others.
For very severely depressed people, interpersonal psychotherapy and the
behavioural components of CBT seem particularly effective in the short run at
least, and the long-term effects of CBT are particularly impressive, especially
when compared to the long-term effects of antidepressants. For the most part,
the differences in effectiveness of these therapies are not very large, and
people who are depressed might well make a choice about which to seek on the
basis of how much sense the treatment makes to them.
Psychotherapy,
Medication or Both?
Psychotherapy has a
number of advantages over medication. The most obvious is that it is not a
drug, which means that it does not have the side effects or other risks that
are associated with taking drugs. A second advantage is that it can be used
safely to treat depression in children, adolescents and young adults, for whom
antidepressants increase the risk of suicide.24 A third advantage is that people
are less likely to drop out of psychotherapy prematurely than they are to stop
taking antidepressants, and this seems to be particularly true for patients
with severe to very severe levels of depression.25
The greatest
advantage of psychotherapy over medication is that it reduces the likelihood of
relapse after having got better. In 2005 a group of Dutch researchers conducted
a clinical trial in which they examined the effect of adding cognitive therapy
to ‘treatment as usual’ in a group of patients with a history of recurrent
depression.26 These are the
people who are most likely to relapse after treatment, because they are the
ones who have relapsed in the past. The researchers found that among patients
who had suffered five or more prior bouts of depression, cognitive therapy
reduced the rate of relapse from 72 per cent to 46 per cent over a two-year
period, and this benefit was independent of whether the patients took
medication during the follow-up period.
The most impressive
demonstration of the long-term benefits of psychotherapy comes from a study
conducted by a group of Italian researchers led by Giovanni Fava at the
University of Bologna.27 Over a six-year
period, they followed patients who had been successfully treated with
antidepressants and then gradually taken off them. Half of the patients were
given ten half-hour sessions of cognitive behaviour therapy (CBT). The others
were also seen by the psychiatrist for ten half-hour sessions, but they were
not given the actual therapy during these sessions. Instead, they received
‘clinical management’. During these clinical-management sessions, the
psychiatrist reviewed the patients’ current state, discussed any problems that
had arisen since the previous session and provided an opportunity for patients
to express their feelings. In other words, patients in the control group were
provided with all of the ‘non-specific’ placebo characteristics of
psychotherapy, without any of the components that are specific to CBT. There
was no attempt to help these patients schedule the activities of everyday life
or to examine or change their negative beliefs and expectations. The results of
this trial were dramatic. Six years after the ten-session treatment, 60 per
cent of the patients who had been give CBT were symptom-free, compared to only
10 per cent of those who had only received clinical management.
Why does
psychotherapy - either alone or in combination with antidepressants - have more
lasting effects than medication? If you take antidepressants and get better,
you are likely to attribute your improvement to the medication. So when you
stop taking it, you might expect to get worse again. In Chapter 5 we saw that
placebos can have negative as well as positive effects, in which case their
effects are called nocebo effects, rather than placebo effects. Getting off
medication may trigger relapse as a nocebo effect. This might not happen all at
once. Instead, the normal slumps in mood that come with the stresses and
strains of life might be interpreted as indications that depression is
returning, beginning the vicious cycle that I described in Chapter 6, in which
expectations and emotional slumps feed on each other, leading eventually to a
relapse.
When people recover
from depression via psychotherapy, their attributions about their recovery are
likely to be different than those of people who have been treated with
medication. Psychotherapy is a learning experience. Improvement is not produced
by an external substance, but by changes within the person. It is like learning
to read, write or ride a bicycle. Once you have learned, the skill stays with
you. People do not become illiterate after they graduate from school, and if
they get rusty at riding a bicycle, the skill can be reacquired with relatively
little practice. Furthermore, part of what a person might learn in therapy is
to expect downturns in mood and to interpret them as a normal part of life,
rather than as an indication of an underlying disorder. This understanding,
along with the skills that the person has learned for coping with negative
moods and situations, can help to prevent a depressive relapse.
If both drugs and
psychotherapy alleviate depression, maybe the combination of the two would work
even better. This could be true even if the effects of antidepressants are
placebo effects. As we saw in Chapter 4, taking two placebos can be more
effective than taking only one.
There does, in
fact, seem to be an advantage in combining antidepressants with psychotherapy,
even in the short run, but the extra benefit of combining both treatments seems
to be relatively small, and there is a catch. The advantage of combining
treatments depends on whether you compare the combination treatment to drugs
alone or psychotherapy alone. Combining psychotherapy and medication is better
than just taking antidepressants, but it is not better than psychotherapy
without drugs.28 In other words,
if you are in psychotherapy, there is no advantage to be gained by also taking
antidepressants. On the other hand, if you are treated with antidepressants,
you will be better off if you also get psychotherapeutic treatment. But since
the effect of psychotherapy alone is as great as the combined effect of
psychotherapy and antidepressants, why bother with the drugs?
Is Psychotherapy a
Placebo?
The central theme of
this book is that much - if not all - of the therapeutic effects of
antidepressants are due to the placebo effect. Might this not also be true of
the effect of psychotherapy on depression? Could this also be a placebo effect?
This is one of the objections that I hear quite often when I am invited to speak
about my research. Psychotherapy is no more effective than antidepressant
medication, these critics contend. So if antidepressants are merely placebos,
so too is psychotherapy.
If you look back
again at the graph in Chapter 1 (page 10) showing the results of the first
meta-analysis that I published on the treatment of depression, you can see why
people might conclude that psychotherapy - like antidepressants - is merely a
placebo. My own analysis showed that the effectiveness of psychotherapy is
about the same as that of drugs, and that although both are much better than no
treatment at all, neither is much better than placebo pills.29
In the short run,
psychotherapy is about as effective as medication, which means that it is only
slightly more effective than placebo pills. In the long run, however, CBT is
much more effective than antidepressant drugs, which means that it is also much
more effective than placebos. Still, there is a sense in which the critics are
right. There is a good reason for thinking of the effects of psychotherapy as
being similar to placebo effects, even though the research shows it to be more
effective than placebo pills.
Dan Moerman, an
anthropologist at the University of Michigan, has pointed out that the phrase
‘placebo effect’ is really an oxymoron, a contradiction in terms.30 By definition, placebos are
supposed to be inert. So how could they possibly affect anything? As a solution
to this definitional conundrum, Moerman has coined the term ‘meaning response’
to designate what up till now we have called the placebo effect. Meanings are
not inert. They can and do affect people. In fact, a fundamental premise of
Albert Ellis’s rational emotive therapy, which was the first cognitive therapy
for emotional problems, is that the way we feel does not depend on the events
that happen to us, but rather on the meaning these events have for us.
Imagine trying to
design a research study to control for the meaning effect in psychotherapy. How
could one ever do this? I suppose we might replace the meaningful words that
the psychotherapist uses with similar-sounding gibberish. Perhaps we could have
the therapist speak only in a language that the patient does not understand.
But even then, some meaning would be assigned to the treatment, as when a
priest or shaman chants in a sacred language or a doctor describes your
condition and its treatment in convoluted technical jargon.
The point is that
meaning is the essence of psychotherapy. It is through meaning that treatment
effects are supposed to be brought about. Controlling for the meaning effect in
psychotherapy is like controlling for the drug effect in the evaluation of a
medicine. It just makes no sense.
Moerman’s concept
of the meaning effect shows the futility of trying to ‘control for the placebo
effect’ in studies of psychotherapy. Nevertheless, researchers have devised a
number of procedures that are intended to do just that. Most commonly, these
are referred to as ‘attention control’ procedures. Their specific components
vary greatly. In fact, some of the interventions that have been used as
attention-control or placebo procedures have also been evaluated as bona-fide
psychotherapies. What they have in common is that they are all supposed to
control for the effects of being given attention and treatment by a clinician,
which is a component of the placebo effect in medicine. These attention-control
procedures differ in their effectiveness, but on the whole they are
significantly less effective than real psychotherapies.31 This is one reason for rejecting
arguments that dismiss psychotherapy as merely a placebo.
Like
antidepressants, a substantial part of the benefit of psychotherapy depends on
the placebo effect, or as Moerman calls it, the meaning response. At least part
of the improvement that is produced by these treatments is due to the
relationship between the therapist and the client and to the client’s
expectancy of getting better. That is a problem for antidepressant treatment.
It is a problem because drugs are supposed to work because of their chemistry,
not because of psychological factors. But it is not a problem for psychotherapy.
Psychotherapists are trained to provide a warm and caring environment in which
therapeutic change can take place. Their intention is to replace the
hopelessness of depression with a sense of hope and faith in the future.32 These tasks are part of the
essence of psychotherapy. The fact that psychotherapy can mobilize the meaning
response - and that it can do so without deception - is one of its strengths,
not one of its weaknesses. Because hopelessness is a fundamental characteristic
of depression, instilling hope is a specific treatment for it. Invoking the
meaning response is essential for the effective treatment of depression, and
the best treatments are those that can do this most effectively and that can do
so without deception.
As we have seen,
the meaning response can be very large. In the treatment of depression, it is
much larger than the drug effect. In fact, if you take away the meaning
response, there may be no drug effect left at all. So what we need is a means
of evoking this response. We want to exploit it rather than avoid it, and a
treatment that can capitalize on the meaning response without deception should
be embraced rather than rejected. What we need is a way to activate a
therapeutic meaning response in clinical practice, and to do so without
deceiving people or playing tricks on them by giving them sugar pills. That is
exactly what psychotherapy is supposed to do, and that is what it does. That is
why I call it the quintessential placebo.
The Costs of
Psychotherapy
There is yet another
advantage of psychotherapy, and it is one that is counter-intuitive.
Psychotherapy costs less than antidepressants. At first glance it might seem
impossible for this claim to be true. Certainly, a week’s worth of
antidepressants costs less than a 50-minute session of psychotherapy. Still, in
the long run, psychotherapy is cheaper. Psychotherapy is cheaper because many
patients have to remain on antidepressants if they are not to relapse and
become depressed again. In contrast, all of the psychological treatments that
have been tested and found effective in the long-term treatment of depression
are relatively brief treatments that last from 10 to 20 weeks. After that there
are no additional costs. About nine months after the beginning of treatment,
the costs of continuing antidepressant treatment catch up to the costs of brief
psychotherapy, and after that, the cumulative costs of medication continue to
rise, whereas those of psychotherapy do not.33
NICE has recognized
the importance of psychotherapy in their current guidelines on the treatment of
depression.34 They recommend
six to eight sessions of CBT or some other form of psychotherapy or counselling
for mild or moderate depression, CBT for recurrent depression, and CBT combined
with antidepressants for severe depression. The problem, of course, is
resources. When doctors prescribe psychotherapy in the UK, patients generally
have to wait from six to nine months for an NHS therapist. In some cases the
patient may have to wait up to two years, and in some areas therapy may not be
available at all. The lack of resources creates a dilemma for GPs and for their
patients who are suffering from depression. Surveys indicate that most doctors
would prescribe antidepressants less often if other treatment options were
available without long waiting lists.35
Currently, the UK
government is taking steps to make psychotherapy for depression more readily
available. On 20 January 2005 the Prime Minister’s Strategy Unit hosted a
seminar in the Cabinet Office, the focus of which was an invited paper
presented by Lord Richard Layard, entitled ‘Mental Health: Britain’s Biggest
Health Problem’.36 In his paper,
Lord Layard argued forcefully for a ten-year plan in which 10,000 new
therapists would be trained to provide CBT and other therapies that had been
shown to be effective in clinical trials. According to Layard, the programme
would not only pay for itself, but would actually generate a profit. Depression
can lead to time-off at work, physical health problems and hospitalization.
This costs society money in terms of reduced output of goods and services, and
it costs the taxpayer money in terms of benefits, services and reduced tax
revenue. The cost of short-term psychotherapy would be about £750, but the
government would save £850 per patient in reduced incapacity benefits and
higher taxes alone, not to mention the costs saved by the NHS through reduced
medication prescriptions and hospitalization.
On 12 May 2005 the
UK government launched the programme that Lord Layard had advocated by establishing
two pilot centres, one in Doncaster and the other in Newham, where CBT would be
offered as an alternative to medication to people suffering from depression.
Two years later the pilot programme was deemed a success, and the government
announced that it would be expanded with the development of ten new
‘Pathfinder’ sites.37 Large numbers of people, including
patients who had applied without being referred by a GP, had been treated in a
short time frame. Recovery rates were consistent with the clinical trials I
have reviewed in this chapter, and statutory sick pay was reduced.
If the government’s
Pathfinder programme is a success, the problem of insufficient therapists may
be solved. But what do we do in the meantime? People who are depressed cannot
wait until the year 2015 for help. Fortunately, there are some low-cost
alternatives that are available right now. These are treatment approaches that
are sometimes used in conjunction with psychotherapy, but can also be used as
stand-alone treatments. Let us take a look at them.
St John’s wort is a
yellow flowering plant that was first used medicinally by the ancient Greeks as
a diuretic and a treatment for wounds and menstrual disorders. This herbal
remedy is widely prescribed in Germany, where it has been studied extensively
in clinical trials as a treatment for depression. In most countries, including
the UK, it is available over the counter. In Ireland it is available only by
prescription. Recently, a team of German scientists led by Klaus Linde at the
University of Munich published a comprehensive review of 29 clinical trials of
St John’s wort, involving more than 5,000 depressed patients. They concluded
that it is more effective than placebos and as effective as standard
antidepressants in the treatment of major depression.
To be fair, since
conventional antidepressants are not much better than placebos, one would have
to draw the same conclusion about St John’s wort. Still, it has some advantages
over standard antidepressants. In particular, it generates far fewer side
effects. In fact, the percentage of patients reporting side effects on St
John’s wort does not seem to be significantly more than the percentage from
placebos.38 To me, this
means that the difference in effectiveness between St John’s wort and placebos,
while small, may be more genuine than the difference between conventional
anti-depressants and placebos. Recall that the effectiveness of regular
antidepressants in clinical trials is linked to the side effects they produce.
Side effects are a cue that enables patients to ‘break blind’ and realize that
they have been given the real drug. This can produce an enhanced placebo
effect, which is responsible for at least part of the difference between drug
and placebo. Because St John’s wort does not have appreciably more side effects
than placebos, patients in clinical trials of this herbal remedy are much less
likely to break blind. As a result, the benefit that it shows compared to
placebos may be more trustworthy than the equally small benefit of
antidepressant drugs.
There are, however,
some drawbacks to St John’s wort. In countries where it is sold over the
counter, there may be a lack of government oversight over its production, but
this would be easy to remedy. The most important drawback is that it affects
the way the body processes a number of other drugs, including conventional
antidepressants and birth-control pills. Like any other drug, St John’s wort
would need to be taken under consultation with a doctor who knows what other
medications the patient is taking.
The reaction to St
John’s wort by the medical profession reveals an interesting double standard.
For example, a large clinical trial sponsored by the National Institutes of
Health in the United States has been interpreted as showing that it is ‘no more
effective than placebo in treating major depression’.39 In fact, the clinical trial on which this
conclusion was based included a group of patients that was given the SSRI
Seroxat.40 Although St
John’s wort did not do significantly better than placebos in that trial,
neither did Seroxat. So if this trial shows that St John’s wort does not work,
it also shows that antidepressants don’t work. Nevertheless, it is often cited
as evidence against St John’s wort, but not against SSRIs.
I am not a great
fan of St John’s wort. For lasting control of depression, psychological
treatment produces the best results, and medication does not add much - if
anything - to it. Nevertheless, if a depressed patient wants medication, or if
available alternative treatments are not sufficiently effective, this herbal
remedy, taken under medical guidance, may be worth considering.
Physical exercise as a
treatment for clinical depression has not been studied as extensively as drugs
or psychotherapy, but there are a number of clinical trials evaluating its
effectiveness.41 In some of
these studies, exercise was compared to no treatment at all. In others, it was
compared to psychotherapy, medication or attention-control procedures intended
to control for the non-specific placebo aspects of the exercise programme. Some
of the trials also looked at the combination of physical exercise with
medication, to see if the two treatments together might be more effective than
either one alone. The results of these studies have been summarized nicely in
an official 2004 report for the NHS by Sir Liam Donaldson, the Chief Medical
Officer for England. Sir Liam concluded that ‘physical activity is effective in
the treatment of clinical depression and can be as successful as psychotherapy
or medication, particularly in the longer term’.42
The studies of
physical exercise as a treatment for depression contain a number of surprising
findings. First, exercise is more effective for moderate to severe depression
than it is for mild to moderate depression. Second, the antidepressant benefits
of exercise seem to be long-lasting, so long as the person keeps exercising
regularly. In fact, the benefits of exercise seem to increase as time goes on.
Twenty minutes of exercise three days a week seems to be enough to produce the
antidepressant effect, and the kind of exercise that is practised does not seem
to matter much. Walking and running are equally effective, and anaerobic
exercises like weight training are as effective as aerobic exercise. Finally,
epidemiological studies indicate that exercise can prevent depression as well
as ameliorate it.43
In 2000, a group of
researchers led by James Blumenthal at Duke University in North Carolina
reported the results of a particularly important clinical trial assessing
exercise as a treatment for depression.44 Equally depressed patients were
randomly divided into three groups. One group was given a four-month course of
aerobic exercise, the SSRI Lustral was prescribed to a second group, and the
third group was given both Lustral and the exercise course. After four months
of treatment there were no significant differences between the groups. Patients
in all three groups had improved significantly. In other words, exercise was as
effective as medication in lowering depression, and combining the two
treatments was no more effective than using just one of them.
But the most
interesting findings from this clinical trial were obtained six months later -
ten months after the beginning of the study. Some important differences between
the three treatment groups emerged at this follow-up assessment. By this point,
significantly more exercise patients had recovered from depression, and more
SSRI patients had relapsed. In other words, exercise was more effective than
drugs.
This advantage of
physical exercise over medication in the long run is reminiscent of comparisons
between cognitive behavioural psychotherapy and antidepressants. More people
treated with antidepressants relapse than those treated with either CBT or
physical exercise. But there is an interesting difference between the
psychotherapy data and the exercise data. Not only did the patients who had
been assigned to the exercise group fare better than those in the drug group,
but they also did better than those in the combined exercise plus medication
group. In other words, adding an SSRI to exercise training increased the risk
of getting depressed again. This was something that Blumenthal and his
colleagues had not anticipated when they designed their study. They had assumed
that if combining exercise with medication had any effect at all, it would be a
positive one, in which the two treatments together would be more effective than
either of them alone.
How can we explain
this rather strange finding that exercise alone was more helpful than exercise
combined with antidepressants? The drugs seemed to have had a harmful effect,
somehow making the exercise programme less effective. This is consistent with
comments that were made by some of the people who were in the group that
combined exercise with drugs. According to the researchers, a number of the
patients in this group ‘mentioned spontaneously that the medication seemed to
interfere with the beneficial effects of the exercise program’. But how did the
medication achieve this negative effect? One possibility is that it was a
nocebo effect. People may have volunteered for this study because it offered an
alternative to drug treatment, and, in fact, some of the participants expressed
disappointment when they were told they would be given an antidepressant drug.
Their negative feelings about the drug component of treatment may have blunted
the positive effect of the exercise programme.
There seems to be
considerable reluctance in some parts of the medical community to acknowledge
the benefits of exercise in the treatment of depression. One meta-analysis of
clinical trials showed that physical exercise was as effective as psychotherapy
or antidepressant medication and much better than no treatment. But the authors
concluded that ‘the effectiveness of exercise in reducing symptoms of
depression cannot be determined’,45 and the editors of the journal introduced the
article with an editorial comment entitled ‘effectiveness of exercise in
managing depression is not shown by meta-analysis’.46 Why not? Because there were flaws
in the way many of the studies had been designed. To be fair, there were indeed
shortcomings in the studies, but these shortcomings also characterize clinical
trials of antidepressants. 47 If clinical trials like these do
not establish the effectiveness of physical exercise as a treatment for
depression, neither do they establish the effectiveness of antidepressants.
How does physical
exercise alleviate depression? One possibility is that it increases the release
of endorphins that produce a sense of well-being, sometimes referred to as the
‘runner’s high’. Another possibility is that it is a placebo effect. But even
if it is a placebo effect, consider the differences between exercise and
antidepressants in side effects. Side effects of antidepressants include sexual
dysfunction, nausea, vomiting, insomnia, drowsiness, seizures, diarrhoea and
headaches. Side effects of physical exercise include enhanced libido, better
sleep, decreased body fat, improved muscle tone, greater life expectancy,
increased strength and endurance and improved cholesterol levels. So if both
antidepressants and exercise work by means of the placebo effect, which placebo
would you prefer?
If physical
exercise is as effective as psychotherapy, why bother with psychotherapy at
all? Why not just prescribe exercise? It is true that exercise is as effective
as psychotherapy when all forms of psychotherapy are lumped together, but when
different types of psychotherapy are compared with exercise, a somewhat
different picture emerges.48 Exercise is about as effective as
psychodynamic therapy and more effective than supportive counselling, but it is
less effective than CBT. The next step will be to assess the effectiveness of
combining CBT with physical-exercise programmes. That might turn out to be the
most effective treatment of all. One of my hopes is that a researcher reading
this book will conduct a clinical trial to find out if this hypothesis is
right.
PSYCHOTHERAPY WITHOUT
PSYCHOTHERAPISTS
Many of the benefits of
CBT can be obtained without going into therapy. There are a number of self-help
books, CDs and computer programs that have been used to treat depression and
some of these have been tested in clinical trials with positive results. I can
particularly recommend two of these books. One is Control
Your Depression, the lead author of which is Peter Lewinsohn, a
Professor of Psychology at the University of Oregon.49 Beginning in the 1970s, Lewinsohn
pioneered the use of behaviour therapy for the treatment of depression, and the
treatment procedures that he and his colleagues proposed have since become
standard components of CBT. The other book that I can recommend with confidence
is Feeling Good by the psychiatrist David Burns.50 Burns based his approach on the
cognitive-therapy programme developed by Aaron Beck at the University of
Pennsylvania. This is the type of psychotherapy that is most often meant when
the term CBT is used. Control Your Depression
emphasizes behavioural techniques like increasing pleasant activities,
improving social skills and learning to relax. Feeling Good
puts greater emphasis on changing the way people think about themselves. But
both books include both cognitive and behavioural techniques.
As a psychotherapist,
I have recommended both of these books to depressed clients, and I found them
useful adjuncts to treatment, but the real basis of my recommendation is the
research that has been published testing their effectiveness as stand-alone
treatments for depression. You might wonder whether something so simple as
reading a book could possibly cure depression, but clinical studies indicate
that it can. An analysis of these trials shows that people get less depressed
after reading these books, and a three-year follow-up indicates that the
benefits are long-lasting.51
The most prolific
researcher of bibliotherapy is Forrest Scogin, a Professor of Psychology at the
University of Alabama. One of Scogin’s studies compared the clinical
effectiveness of Feeling Good to standard CBT with a
live therapist. Although patients in both groups improved, those who had seen a
therapist had improved more than the others by the end of treatment. But the
subjects who had been given the book to read continued to improve,and within
three months they had caught up with those who had received standard CBT. One
caveat is needed, however. The patients studied in clinical trials of
bibliotherapy were only moderately depressed. We do not yet know what effect
books like Feeling Good and Control
Your Depression would have on people who are more severely depressed,
but for those who are mildly or moderately depressed, working through the
exercises in these books can be a reasonable alternative to psychotherapy.
Physicians might
wonder whether self-help treatments would be acceptable to their depressed
patients. A recent study by Alastair Dobbin, a general practitioner in
Edinburgh, suggests that they might actually prefer it.52 Dobbin let depressed patients
referred by the NHS choose between taking antidepressant medication prescribed
by their GPs and receiving a self-help self-hypnosis treatment programme
presented on CDs. Eighty-six per cent of the patients chose the self-help
self-hypnosis programme, 7 per cent chose antidepressants and the rest
expressed no preference. With so few patients in the drug condition, a
statistical comparison of the outcomes of the two treatments was not feasible,
but those getting the self-help programme did at least as well as patients in
studies of antidepressants and CBT.
In this chapter I have
stressed the good news that there are many effective treatments for combating
depression. This is necessarily true given the strength of the placebo effect.
If placebos produce improvement, then any credible bona-fide treatment will
also alleviate depression. Some of these treatments may be more effective than
placebos, but in the treatment of depression, the placebo effect is always a
major component.
That’s the good
news. Unfortunately, there is also some bad news. The bad news is that despite
the range of treatments available, many people remain depressed after treatment
and others relapse after getting better. Even CBT, which can substantially
reduce the likelihood of relapse, does not eliminate it altogether.
Depression is not
just an individual problem; it is also a social problem. The people most likely
to become depressed are poor, unemployed and undereducated.53 To some extent, this may be due to
what is called social selection or economic drift. People who are chronically
depressed might find it harder to perform well or even hold a job, and this
might lead to a downward shift in their economic status. But there are data
showing that the cause and effect can also run in the opposite direction.54 Different ethnic groups, for
example, have different rates of depression. As the authors of one of the
studies investigating this pointed out, ‘ethnic status cannot be an effect of
disorder because it is present at birth’. Another study showed that people are
more likely to become depressed if their parents were poor or less educated.
These data cannot be explained by the economic-drift hypothesis. In other
words, poverty and discrimination can cause depression.
The importance of
economic problems in depression has been shown in a study of psychotherapy for
depression conducted by two researchers in Chicago.55 They found that during the first
two sessions of treatment, more than 85 per cent of the depressed patients
spontaneously brought up issues relating to inadequate financial resources,
difficult working conditions or unemployment. They also found that the patients
did better if their therapists responded by focusing on their economic problems
as part of the treatment.
Still, dealing
effectively with depression requires more than merely treating it. Not only are
poor, unemployed, less well-educated and non-white people more likely to become
depressed, but they are also least likely to benefit from treatment by either
antidepressants or psychotherapy.56 That is why combating depression
requires more than merely providing effective treatment for those who are
already suffering from it. We also need to change the social conditions - such
as racism, unemployment, poverty, unaffordable housing and lack of adequate
education - that put people at increased risk of becoming depressed.
Using data
collected by the World Health Organization, Richard Wilkinson and Kate Pickett
have shown that countries in which there is greater economic inequality have
higher rates of mental illness. Their conclusions were based on data from rich
countries only, ranging from the more economically equal Japan and Belgium to
the less equal US and UK. So it was not the level of poverty per se that made
the difference. Rather it was the unequal distribution of income within each
country that was associated with emotional disorders and other social problems.57 These data reinforce the idea that
decreasing social inequality might also reduce the incidence of depression.
By now, I hope that I
have convinced you that much of what has passed for common wisdom about
depression and antidepressants is simply wrong. Depression is not caused by a
chemical imbalance in the brain, and it is not cured by medication. Depression
may not even be an illness at all. Often, it can be a normal reaction to
abnormal situations. Poverty, unemployment, and the loss of loved ones can make
people depressed, and these social and situational causes of depression cannot
be changed by drugs.
Depression is a
serious problem, but drugs are not the answer. In the long run, psychotherapy
is both cheaper and more effective, even for very serious levels of depression.
Physical exercise and self-help books based on CBT can also be useful, either
alone or in combination with therapy. Reducing social and economic inequality
would also reduce the incidence of depression.
‘DON’T ROCK THE BOAT’
Reporting these conclusions
and the evidence on which they are based has not always been an easy task. I
have faced some rather hostile crowds at medical schools, although more often
the reception has been open and cordial. Nevertheless, there can be negative
consequences to taking a stance that challenges powerful interests. I recall
working with a researcher at a medical school some years ago in an effort to
design a clinical study of antidepressants using the balanced placebo design
that I described in Chapter 3. Our collaboration ended when he was warned that
he should not submit a grant proposal with my name on it, if he ever wanted to
do a clinical trial on antidepressants again. I cannot blame him for this
decision, as he was funded on ‘soft money’, which means that his salary
depended on getting his research funded.
I was well
established in my career when this incident happened. Having a tenured position
in the psychology department at the University of Connecticut, I did not feel
threatened by it. In fact, I must admit to feeling a bit proud of my apparent
infamy. But young researchers with their careers at stake are also subject to
this sort of pressure. One young colleague on the staff at a medical school
wrote a paper critical of antidepressants that was published in a very
distinguished medical journal. Instead of being proud of him, his department
head told him that he should not have written the article, that he should not
become too involved with me and that he was biting the hand that feeds him.
In August 2000, David
Healy was formally offered a position at the Centre for Addiction and Mental
Health, a teaching hospital affiliated with the University of Toronto. Three
months later Healy gave an invited address at the university, during which he
noted that most of the clinical trials of Lustral and Prozac had ‘failed to
detect any treatment effect’. This claim is actually much milder than it seems
at first glance. Healy concluded that these unsuccessful trials did not
constitute evidence that the drugs were ineffective. Instead, like many of the
critics of my recent work, he saw them as ‘evidence of the inadequacy of our
assessment methods’.1 On the other hand, Healy did say
that he believed that SSRIs can lead to suicide, and in subsequent years he has
backed that claim up with persuasive evidence.2 In any case, one week after
delivering his lecture, Healy received a message withdrawing the offer of the post
at the hospital.
The most recent ‘don’t
rock the boat’ incident that I am aware of involved Jonathan Leo, Associate
Professor of Neuroanatomy at Lincoln Memorial University in Tennessee. Leo and
his colleague Jeffrey Lacasse, an assistant professor in the school of social
work at Arizona State University, had criticized an article that had been
published in the Journal of the American Medical Association
( JAMA). The study supported the use of the SSRI
Cipralex (Lexapro in the US) to prevent depression in patients who have
suffered a stroke. It also assessed the effects of problem-solving therapy, a
form of CBT, and found that it too prevented depression. But until Lacasse and
Leo’s questioning, the authors of the study had not directly compared the two forms
of treatment. When they did, they found the two to be equally effective.3
Lacasse and Leo’s
criticism, and the reply to it, were published in JAMA
in October 2008. Five months later Leo and Lacasse wrote another commentary on
the JAMA article and sent it to the British Medical Journal. They recounted the story of having
wondered about the comparison between Lexapro and problem-solving therapy and
noted the results of the comparison that had been published in response to
their questioning. They also mentioned an apparent conflict of interest
involving financial connections between Robert Robinson, the lead author of the
study, and Forest Pharmaceuticals, the US manufacturer of Lexapro. Robinson acknowledged
the conflict of interest and apologized for not having disclosed it.4
All of this is pretty
standard stuff. Researchers write articles. Other researchers criticize them,
sometimes vociferously, often in the same journal, but sometimes in other
journals. I have already lost count of the number of challenging commentaries
that my most recent meta-analysis provoked in journals other than the one in
which my article had been published. Sometimes I was alerted to them by
editors, most often not. Occasionally I was invited to reply.
What happened to
Jonathan Leo next was reported in the Wall Street Journal’s
online Health Blog. JAMA editors phoned Leo and the
Dean of his institution. According to Leo, the deputy editor of JAMA asked him, ‘Who do you think you are’, and then said,
‘You are banned from JAMA for life. You will be
sorry. Your school will be sorry. Your students will be sorry.’ The JAMA editors confirmed the calls. They said that Leo had exaggerated
their content, but the editor-in-chief of the journal is also quoted as telling
the Wall Street Journal reporter, ‘This guy is a
nobody and a nothing. He is trying to make a name for himself. He should be
spending time with his students instead of doing this.’5 The editor subsequently denied
making such a statement, claiming the journalist had misquoted her.
Nevertheless, the general response to Leo is scary stuff from one of the
world’s leading medical journals.
‘DON’T ASK, DON’T TELL’
When Bill Clinton was
campaigning for the presidency of the United States, he promised to lift the
long-standing ban on homosexuals serving in the military. But once in office,
congressional opposition was so strong that he was forced to back off. The
result was a compromise, in which gays were allowed to remain in the armed
forces, as long as they did not call attention to their sexual orientation.
This compromise came to be known as the ‘Don’t ask, don’t tell’ policy.
Sometimes, when
they run out of arguments in defence of antidepressants, people suggest that I
should have adopted a ‘Don’t ask, don’t tell’ policy. Even if the drugs don’t
work, they tell me, it is wrong to say so in public or to write about it in
medical-journal articles, like the ones my colleagues and I have published.
They argue that we shouldn’t tell patients that the drugs don’t work, even if
it is true, because it will undermine their faith in treatment.
In 2004 the FDA urged
drug companies to adopt a ‘Don’t ask, don’t tell’ policy with respect to their
clinical-trial data showing that antidepressants are not better than placebos
for depressed children. If the data were made public, they cautioned, it might
lead doctors to not prescribe antidepressants. The FDA believed that the jury
was still out on antidepressants for children. Even if the clinical trials show
negative results, an FDA spokesperson was reported to have said to a Washington Post reporter, it doesn’t mean that the drugs
are ineffective.6 The assumption
seems to have been that doctors should prescribe medications that have not been
shown to work, until it has been proven that they don’t work.
I disagree strongly
with the ‘Don’t ask, don’t tell’ policy. Without accurate knowledge, patients
and physicians cannot make informed treatment decisions, researchers will ask
the wrong questions and policymakers will implement misinformed policies. If
the antidepressant effect is largely or entirely a placebo effect, it is
important that we know this. If placebos can make people better, then
depression can be ameliorated without reliance on drugs that have potentially
serious side effects and that foster dependency.
For people who are
depressed, and especially for those who do not receive enough benefit from
medication or for whom the side effects of antidepressants are troubling, the
fact that placebos can duplicate much of the effects of antidepressants should
be taken as good news. It means that there are other ways of alleviating
depression. As we have seen, treatments like psychotherapy and physical
exercise are at least as effective as antidepressant drugs and more effective
than placebos. In particular, CBT has been shown to lower the risk of relapsing
into depression for years after treatment has ended, making it particularly
cost-effective.
For society as a
whole, knowledge of what the data on antidepressants really say should be a
clarion call. Resources need to be made available for the provision of
effective alternative treatments, and the social and economic causes of
depression need to be addressed and overcome. It is my hope that this book will
contribute to a wider recognition of the need for these changes in public
policy and attitudes.
As you may have gathered by now, I rather enjoy
telling tales and ruffling feathers. I also enjoy rocking boats, especially
when they are in need of sinking. I hope you have enjoyed the ride.
Notes/References/Referanslar
Preface
1 John P. A. Ioannidis, 2008; Jeffrey Lacasse and Jonathan Leo, 2005;
‘CNS Drug Discoveries: What the Future Holds 2008’.
2 Irving Kirsch, 1990.
3 John D. Teasdale,
1985.
4 Irving Kirsch and Guy Sapirstein, 1998.
5 Irving Kirsch, Alan Scoboria and Thomas J. Moore, 2002b; Irving
Kirsch, Thomas J. Moore et al., 2002a; Irving Kirsch, Brett J. Deacon et al.,
2008.
6 NICE, ‘Depression: Management of Depression in Primary and Secondary
Care’; CSIP, Choice and Access Programme, 2007; Eero Castrén, 2005; H. G. Ruhé,
N. S. Mason and Aart H. Schene, 2007.
1 Listening to Prozac,
but Hearing Placebo
1 William Schofield, 1964.
2 Standardized mean difference between pre-treatment and posttreatment
depression scores for each type of treatment, Irving Kirsch and Guy Sapirstein,
1998.
3 John P. A. Ioannidis, 2008.
4 John W. Williams, Jr, et al., 2000.
5 Joanna Moncrieff, 2008b.
6 Mark S. Kramer et al., 1998.
7 Michael Philipp, Ralf Kohnen and Karl O. Hiller, 1999.
8 Carl Sherman, 1998.
9 J. G. Rabkin et al., 1986.
10 Joel R. Sneed et al., 2008; Martin Enserink, 1999; Martin Keller et
al., 2006.
11 Roger P. Greenberg et al., 1994.
12 James M. Ferguson, 2001.
13 Greenberg et al., 1994.
14 John F. Kihlstrom, 1998.
15 Corrado Barbui, Toshiaki A. Furukawa and Andrea Cipriani, 2008.
16 Corrado Barbui, Andrea Cipriani and Irving Kirsch, 2009.
17 Joanna Moncrieff, S. Wessely and R. Hardy, 2005; Joanna Moncrieff,
2008b.
2 The ‘Dirty Little
Secret’
1 Peter Nathan and Martin E. P. Seligman, 1998.
2 Larry E. Beutler, 1998; Donald F. Klein, 1998.
3 Russell Joffe, Stephen Sokolov and David Streiner, 1996.
4 Hans Melander et al., 2003.
5 Irving Kirsch and Guy Sapirstein, 1998; Richard A. Hansen et al.,
2005; Gerald Gartlehner et al., 2007.
6 Irving Kirsch, Thomas J. Moore et al., 2002a; Irving Kirsch, Brett J.
Deacon et al., 2008.
7 NICE, ‘Depression: Management of Depression in Primary and Secondary
Care’.
8 Ibid.
9 Kirsch, Deacon et al., 2008.
10 Anton J. M. de Craen et al., 1999.
11 Carl Sherman, 1998.
12 Otto Benkert et al., 1997.
13 David O. Antonuccio, David D. Burns and William G. Danton, 2002; Roger
P. Greenberg, 2002; Walter A. Brown, 2002; Michael E. Thase, 2002.
14 Steven D. Hollon et al., 2002.
15 Melander et al.,
2003.
16 Wayne Kondro and Barbara Sibbald, 2004; ‘Major Pharmaceutical Firm
Concealed Drug Information’, 2004.
17 Kondro and Sibbald, 2004.
18 Martin Keller, Neal D. Ryan et al., 2001.
19 ‘Major Pharmaceutical Firm Concealed Drug Information’, 2004.
20 Gardiner Harris,
2004.
21 Alex Berenson, 2005.
22 B. J. Deacon, Kimberlee Glassner and Irving Kirsch, 2006; Melander et
al., 2003.
23 Melander et al.,
2003.
24 NICE, ‘Depression: Management of Depression in Primary and Secondary
Care’.
25 Catherine DeAngelis, Jeffrey M. Drazen et al., 2004.
26 Paul Leber, 1998.
27 Shankar Vedantam, 2004.
28 Jerry Avorn, 2007.
29 Ibid.
30 EMEA, 2008; Rob Evans and Sarah Boseley, 2004.
31 Hans Melander, Tomas Salmonson et al., 2008.
32 Irving Kirsch and Joanna Moncrieff, 2007.
33 Thomas P. Laughren, 1998.
34 Leber, 1998.
35 Laughren, 1998.
3 Countering the
Critics
1 ‘Doctors Change Prescribing Habits on Back of SSRI Study’, 2008.
2 ‘Antidepressants
Work . . . ,’ David Nutt, quoted in Martin Enserink, 2008; ‘Dozens of Clinical
Trials,’ Rachel Werner, 2008.
3 Arthur K. Shapiro and L. A. Morris, 1978.
4 Arthur K. Shapiro, 1960.
5 Joel R. Sneed et al., 2008.
6 Lene Vase, Joseph L. Riley III and Donald D. Price, 2002.
7 Madhukar H. Trivedi et al., 2006; A. John Rush et al., 2006a; A. John
Rush et al., 2006b.
8 Blair T. Johnson and Irving Kirsch, 2008.
9 S. Wolf et al.,
1957.
10 Robert E. Kelly, Jr, et al., 2006.
11 Matthew J. Taylor et al., 2006.
12 Joseph Glenmullen, 2006; Christopher H. Warner et al., 2006.
13 H. G. Ruhé, N. S. Mason and Aart H. Schene, 2007; Giovanni A. Fava,
2003.
14 Arif Khan, Nick Redding and Walter A. Brown, 2008.
15 Hypericum Depression Trial Study Group, 2002.
16 James L. Claghorn and John P. Feighner, 1993.
17 Khan, Redding, and Brown, 2008.
18 NICE, ‘Depression: Management of Depression in Primary and Secondary
Care’.
19 Erick H. Turner et al., 2008.
20 Quoted in Marilyn Elias, 2002.
21 J. G. Rabkin et al., 1986.
22 Ted J. Kaptchuk, 1998b.
23 Sandra Lee et al., 2004.
24 Editorial, ‘A Double-Edged Sword’, 2008. I should also note that Nature, which is the primary journal of the Nature
Publishing Group, responded to our meta-analysis with an excellent editorial on
6 March 2008. Citing the difficulties we had in obtaining access to complete
data, they advocated a mandatory database that would provide access to the
results of all trials clinical trials that are undertaken, not just those that
are published.
25 Hans Melander, Tomas Salmonson et al., 2008.
26 D. S. Charney et al., 2002; Michael A. Posternak et al., 2002.
27 Trivedi et al.,
2006.
28 Sneed et al., 2008.
29 Werner, 2008.
30 Corrado Barbui, Andrea Cipriani and Irving Kirsch, 2009.
31 GlaxoSmithKline,
2008.
32 Corrado Barbui, Toshiaki A. Furukawa and Andrea Cipriani, 2008.
33 Irving Kirsch, 2000.
34 G. A. Marlatt and D. J. Rohsenow, 1980.
35 I. Kirsch and M. J. Rosadino, 1993; Fabrizio Benedetti, G. Maggi et
al., 2003.
36 Sneed et al., 2008.
37 Irving Kirsch, ‘Are drug and placebo effects in depression additive?’ Biological Psychiatry, 47, 733-735, 2000.
38 Pedro L. Delgado, 2000.
4 The Myth of the
Chemical Imbalance
1 Jeffrey R. Lacasse and Jonathan Leo, 2005; P. J. Cowen, 2008.
2 David Healy, 1997; Joanna Moncrieff, 2008a.
3 Francisco López-Muñoz et al., 2007.
4 Peter Fangmann et al., 2008.
5 Roland Kuhn, 1958.
6 Healy, 1997.
7 Roland Kuhn, 1990.
8 Joseph J. Schildkraut, 1965.
9 Alec Coppen, 1967.
10 Healy, 1997.
11 López-Muñoz et al., 2007; Healy, 1997.
12 Schildkraut, 1965.
13 Julius Axelrod, L. G. Whitby and George Hertting, 1961; Julius Axelrod
and Joseph K. Inscoe, 1963.
14 Schildkraut, 1965.
15 F. K. Goodwin and W. E. Bunney, Jr, 1971.
16 A. John Rush et al., 2006a.
17 D. L. Davies and Michael Shepherd, 1955.
18 Michael Shepherd, 1956.
19 Healy, 1997.
20 Axelrod, Whitby and Hertting, 1961.
21 Schildkraut, 1965.
22 Lacasse and Leo, 2005; Joanna Moncrieff, 2008b; Eero Castrén, 2005.
23 Joseph Mendels and Alan Frazer, 1974.
24 H. G. Ruhé, N. S. Mason and Aart H. Schene, 2007.
25 Ibid. For the sake of clarity, I have altered the quotation by
spelling out some of the abbreviations.
26 Coppen, 1967.
27 G. S. Malhi, G. B. Parker and J. Greenwood, 2005.
28 Andrea Cipriani et al., 2009. The calculations are simple and
straightforward. Table 3 of The Lancet article reports
response rates for head-to-head comparisons of different antidepressants, along
with the number of subjects on which each response rate was based. I merely
extracted the response rates in all of the head-to-head comparisons of an SSRI
with an NDRI, multiplied each response rate by the number of subjects it was
based on, summed the product and divided the sum by the total number of
subjects.
29 A. John Rush et al., 2006b.
30 Gerald Gartlehner et al., 2007; Richard A. Hansen et al., 2005;
Cipriani et al., 2009.
31 Hansen et al., 2005.
32 Robert E. Kelly, Jr, et al., 2006.
33 Hansen et al., 2005.
34 Rush et al., 2006b.
35 Moncrieff, 2008b; Irving Kirsch and Guy Sapirstein, 1998; Irving
Kirsch, 2003.
36 Sheldon H. Preskorn, 2004; Milan Sarek, 2006.
37 Siegfried Kasper and Bruce S. McEwen, 2008; Antona J. Wagstaff,
Douglas Ormrod and Caroline M. Spencer, 2001; Tayfun I. Uzbay, 2008.
38 Wagstaff, Ormrod and Spencer, 2001.
39 Thomas Kuhn, 1970.
40 I. Hindmarch, 2002.
41 Castrén, 2005.
42 Ibid.
43 Michael E. Hyland, 1985.
44 Helen S. Mayberg, Mario Liotti et al., 1999; Helen S. Mayberg, J.
Arturo Silva et al., 2002.
5 The Placebo Effect
and the Power of Belief
1 Jeremy Laurance, 2008; ‘Depression Drugs Don’t Work, Says New Study’,
2008; Sarah Boseley, 2008; Fiona McRae, 2008.
2 Rebecca Smith, 2008.
3 Jeff Aronson, 1999; Geoffrey Chaucer, 2003.
4 T. C. Graves, 1920.
5 ‘The Humble Humbug’, 1954.
6 Ted J. Kaptchuk, Catherine E. Kerr and Abby Zanger, 2009.
7 Alfred Binet and Charles Féré, 1988.
8 Ted J. Kaptchuk, 1998a; Ted J. Kaptchuk 1998c.
9 S. Wolf, 1950.
10 Ibid.; F. K. Abbot, M. Mack and S. Wolf, 1952.
11 H. K. Beecher, 1955.
12 E. F. Traut and E. W. Passarelli, 1957.
13 Kaptchuk, 1998c.
14 A. Hróbjartsson and P. C. Gøtzsche, 2001; A. Hróbjartsson and P. C.
Gøtzsche, 2004.
15 Lene Vase, Joseph L. Riley III and Donald D. Price, 2002; Joel R.
Sneed et al., 2008.
16 Anton J. M. de Craen, D. E. Moerman et al., 1999; Anton J. M. de
Craen, J. G. Tijssen et al., 2000; A. Branthwaite and P. Cooper, 1981; Rebecca
L. Waber et al., 2008.
17 Vase, Riley III and Price, 2002.
18 Peter Tyrer et al., 2008.
19 De Craen, Tijssen et al., 2000; Ted J. Kaptchuk, W. B. Stason et al.,
2006.
20 Christopher G. Goetz et al., 2008.
21 Mario Battezzati, Alberto Tagliaferro and Angelo Domenko Cattaneo,
1959.
22 L. Cobb et al., 1959; E. G. Dimond, C. F. Kittle and J. E. Crockett,
1960.
23 Dimond, Kittle and Crockett, 1960.
24 Traut and Passarelli, 1957.
25 Margaret Talbot,
2000.
26 J. Bruce Moseley et al., 2002.
27 Talbot, 2000.
28 David F. Felson and Joseph Buckwalter, 2002.
29 Nelda P. Wray, J. Bruce Moseley and K. O’Malley, 2002.
30 Alexandra Kirkley et al., 2008.
31 Robert G. Marx,
2008.
32 Irving Kirsch, 1990.
33 Michael E. Hyland, 1985; Irving Kirsch and Michael E. Hyland, 1987.
34 For more complete discussions of the relation between mind and brain,
see Peter M. Churchland, 1984.
35 Helen S. Mayberg, Maria Liotti et al., 1999; Helen S. Mayberg, Steven
K. Brannon et al., 2000; Helen S. Mayberg, J. Arturo Silva et al., 2002.
36 Mayberg, Silva et al., 2002; p. 731.
37 Kimberly Goldapple et al., 2004; Andrew F. Leuchter et al., 2002.
38 Sarah-Jayne Blakemore and Uta Frith, 2005.
39 Tor D. Wager, James K. Rilling et al., 2004.
40 Samantha C. Sodergren and Michael E. Hyland, 1999.
41 T. J. Luparello, H. A. Lyons et al., 1968.
42 T. J. Luparello, N. Leist, et al., 1970.
43 Y. Ikemi and S. Nakagawa, 1962.
44 B. Klopfer, 1957.
45 Per-Henrik Zahl, Jan Mæhlen and H. Gilbert Welch, 2008.
46 Michael D. Storms and Richard E. Nisbett, 1970.
47 Timothy F. Jones et al., 2000.
48 William Lorber, Giuliana Mazzoni and Irving Kirsch, 2007.
49 A. M. Daniels and R. Sallie, 1981.
50 M. G. Myers, J. A. Calms and J. Singer, 1987.
51 Roy R. Reeves et al., 2007.
52 W. B. Cannon, 1942.
53 Esther M. Sternberg, 2002.
54 Michael Philipp, Ralf Kohnen and Karl O. Hiller, 1999; Corrado Barbui,
Andrea Cipriani and Irving Kirsch, 2009.
55 Irving Kirsch, 1985; Irving Kirsch (ed.), 1999.
56 S. Reiss and R. J. McNally, 1985; Kirsch, 1985.
57 John D. Teasdale, 1985.
6 How Placebos Work
1 Zelda Di Blasi et al., 2001; Ted J. Kaptchuk, John M. Kelley et al.,
2008.
2 Kaptchuk, Kelley et al., 2008.
3 Ted J. Kaptchuk, 1983; Ted J. Kaptchuk, 2000.
4 Anton J. M. de Craen, D. E. Moerman et al., 1999.
5 Scot H. Simpson et al., 2006.
6 Kaptchuk, Kelley et al., 2008.
7 Di Blasi et al., 2001; Kaptchuk, Kelley et al., 2008.
8 Roger S. Ulrich,
1984.
9 Margaret A. Chesney et al., 2005.
10 D. Räikkönen et al., 1999; D. M. Byrnes et al., 1998; M. F. Scheier et
al., 1999; David Spiegel and Janine Giese-Davis, 2003; H. Yang and W. Lin,
2005.
11 Irving Kirsch, 2006.
12 R. Pogge, 1963.
13 Irving Kirsch and Lynne J. Weixel, 1988; M. Frankenhaeuser et al.,
1963.
14 Irving Kirsch, 1985; Irving Kirsch (ed.), 1999; Steve Stewart-Williams
and John Podd, 2004.
15 Arthur K. Shapiro, E. Struening and E. Shapiro, 1980.
16 Guy H. Montgomery and Irving Kirsch, 1996.
17 Donald D. Price and Howard L. Fields, 1997.
18 Jon D. Levine, Newton C. Grodon and Howard L. Fields, 1978.
19 Tor D. Wager, David J. Scott and Jon-Kar Zubieta, 2007.
20 Fabrizio Benedetti, C. Arduino and M. Amanzio, 1999.
21 Kirsch, 1985; Stewart-Williams and Podd, 2004; Tor D. Wager, 2005; Tor
D. Wager, James K. Rilling et al., 2004.
22 Ivan P. Pavlov, ‘Physiology of Digestion: Nobel Lecture 12 December
1904; Ivan P. Pavlov, 1927; Robert E. Clark, 2004.
23 N. J. Voudouris, C. L. Peck and G. Coleman, 1985; N. J. Voudouris, C.
L. Peck and G. Coleman, 1989; N. J. Voudouris, C. L. Peck and G. Coleman, 1990.
24 Donald D. Price, Leonard B. Milling et al., 1999.
25 Wager, Rilling et al., 2004.
26 Robert A. Rescorla, 1988; Irving Kirsch, Steven J. Lynn et al., 2004;
Voudouris, Peck and Coleman, 1985.
27 Voudouris, Peck and Coleman, 1985.
28 Guy H. Montgomery and Irving Kirsch, 1997.
29 Alison Watson et al., 2007.
30 Fabrizio Benedetti, Antonella Pollo et al., 2003.
31 Irene Elkin, 1994.
32 Stuart M. Sotsky et al., 1991.
33 Irving Kirsch, 1990; Joel Weinberger and Andrew Eig, 1999; Björn Meyer
et al., 2002.
34 Aaron T. Beck et al., 1979; John D. Teasdale, 1985.
35 Frederic M. Quitkin et al., 1998.
36 Aimee M. Hunter et al., 2006.
37 Kirsch and Weixel, 1988.
38 Joel R. Sneed et al., 2008.
7 Beyond
Antidepressants
1 Irving Kirsch and Guy Sapirstein, 1998.
2 Joel R. Sneed et al., 2008.
3 R. Hamish McAllister-Williams, 2008.
4 Richard A. Hansen et al., 2005; Michael Philipp, Ralf Kohnen and Karl
O. Hiller, 1999; Corrado Barbui, Andrea Cipriani and Irving Kirsch, 2009.
5 FDA, 2006.
6 Bettina C. Prator, 2006.
7 Tarek A. Hammad, Thomas Laughren and Judith Racoosin, 2006.
8 Marc B. Stone and M. Lisa Jones, 2006; David Healy, 2009; Dean
Fergusson et al., 2005.
9 Peter R. Breggin, 2003/2004; Peter R. Breggin, 2006; David Healy,
Andrew Herxheimer and David B. Menkes, 2006.
10 Anthony J. Rothschild and Carol A. Locke, 1991.
11 Christopher H. Warner et al., 2006; Joseph Glenmullen, 2006.
12 Jon C. Tilburt et al., 2008; Uriel Nitzan and Pesach Lichtenberg,
2004.
13 Tilburt et al.,
2008.
14 Lee C. Park and Lino Covi, 1965.
15 Fabrizio Benedetti, Antonella Pollo, et al., 2003.
16 Andrew C. Butler et al., 2006.
17 NICE, ‘Depression: Management of Depression in Primary and Secondary
Care’; Claudi L. H. Bockting et al., 2005; Keith S. Dobson et al., 2008;
Giovanni A. Fava et al., 2004.
18 Zac E. Imel et al., 2008.
19 Peter M. Lewinsohn, David O. Antonuccio et al., 1984; Aaron T. Beck et
al., 1979.
20 Gerald L. Klerman et al., 1984.
21 H. Davanloo, 1976.
22 Carl Rogers, 1961.
23 Pim Cuijpers et al., 2008; Sona Dimidjian et al., 2006; Dobson et al.,
2008; Leslie A. Robinson, Jeffrey S. Berman and Robert A. Neimeyer, 1990.
24 Stone and Jones, 2006; Hammad, Laughren and Racoosin, 2006; FDA, 2007.
25 NICE, ‘Depression: Management of Depression in Primary and Secondary
Care’.
26 Bockting et al.,
2005.
27 Fava et al., 2004.
28 Michael A. Friedman et al., 2004; Marc B. J. Blom et al., 2007.
29 Kirsch and Sapirstein, 1998.
30 Daniel E. Moerman, 2006; Daniel E. Moerman and Wayne B. Jonas, 2002.
31 Bruce E. Wampold et al., 2002.
32 J. D. Frank, 1973.
33 Dobson et al., 2008.
34 NICE, ‘Depression: Management of Depression in Primary and Secondary
Care’.
35 Ed Halliwell, 2005.
36 Richard Layard, 2004; Richard Layard, 2006.
37 CSIP, Choice and Access Programme, 2007a; CSIP, 2007b; CSIP, 2008.
38 Philipp, Kohnen and Hiller, 1999.
39 NCAM, ‘St John’s
Wort’.
40 Hypericum Depression Trial Study Group, 2002.
41 Lynette L. Craft and Daniel M. Landers, 1998; Debbie A. Lawlor and
Stephen W. Hopker, 2001; James A. Blumenthal et al., 1999; Michael A. Babyak et
al., 2000; Nalin A. Singh, Karen M. Clements and Maria A. Fiatarone Singh,
2001.
42 Liam Donaldson,
2004.
43 William J. Strawbridge et al., 2002.
44 Blumenthal et al., 1999; Babyak et al., 2000.
45 Lawlor and Hopker, 2001.
46 Editorial, ‘Effectiveness of Exercise’, 2001.
47 M. Hotopf, G. Lewis and C. Normand, 1997.
48 M. Pinquart, P. M. Duberstein and J. M. Lyness, 2007.
49 Peter M. Lewinsohn, R. F. Munoz et al., 1978.
50 David D. Burns,
1980.
51 Robert J. Gregory et al., 2004; Mark Floyd et al., 2004; Nancy M.
Smith et al., 1997.
52 Alastair Dobbin, Margaret Maxwell and Robert Elton, 2009.
53 Christopher G. Hudson, 2005; V. Lorant et al., 2003.
54 Bruce P. Dohrenwend et al., 1992; Jeffrey G. Johnson et al., 1999.
55 Lydia Falconnier and Irene Elkin, 2008.
56 Madhukar H. Trivedi et al., 2006; R. Bruce Sloane et al., 1976.
57 Richard Wilkinson and Kate Pickett, 2009.
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