Jonah
Lehrer was also Wrong About Antipsychotics
We
spend a lot of time writing about knowledge dissemination in mental health, and
over time, have increasingly recognized the important role of science
journalists in our society. Thus, we have watched the recent rise and fall of Jonah Lehrer with great
interest. Mr. Lehrer wrote a piece for the New Yorker last year
that addressed antipsychotics. However, his well-written and entertaining piece
didn’t seem to reflect the data on how pharmaceutical companies have promoted
antipsychotics – instead, it seemed like he had jammed two narratives together
that didn’t quite fit, at best not taking all the available into account, at
worst, discarding the data that didn’t fit his story. At the time, we were a
bit puzzled, and wrote a blog post about it (see below). As it turns out, this
turns out not to be an anomaly but more a pattern of behavior, as he just
resigned his position at the New Yorker for inventing quotes in a recent book.
We
don’t mean to “pile-on”, as this is a tragic circumstance, but we noticed how
many people read Lehrer’s piece who do not read, for instance, Mad in
America.com, and feel it was a missed opportunity to inform the public of a
very interesting story – the overestimation of the efficacy and safety of the
newer antipsychotics due to enthusiastic and overwhelming promotion by
pharmaceutical companies and their associates. Unfortunately, that story
apparently didn’t fit the narrative Lehrer wanted to write.
We
badly need good science writers, especially those who do rigorous work and
consider all the available data in their stories.
Originally
posted on Mad in America on December 13, 2011:
In
a recent article in the New Yorker, titled, The Truth Wears Off, science writer Jonah Lehrer discusses an intriguing problem
in science. The problem is that scientific results which are confirmed at one
point are sometimes overturned after further testing – today’s “facts” are
tomorrow’s “fallacies.” The reason for this, as he sees it, are subtle biases
at work that taint the scientific method, so that well-done experiments
designed by well-meaning scientists are eventually shown to be problematic. To
support this line of reasoning he provides an excellent example of an experiment by John Crabbe.
Crabbe’s group attempted to do the exact same experiment in three different
labs, each in different parts of the country. One would expect that if all the
experiments were well-controlled at all three research labs, each would reach
similar results. His group did their absolute best to replicate all the
variables in each of the labs as much as possible, and in spite this, the
results varied somewhat for each lab. The natural conclusion is that
eliminating all bias in experimentation is probably impossible and that
replicability is more difficult and complex than commonly considered.
In
addition to Crabbe’s study, Lehrer also cites the clinical trials of
antipsychotics to support his view. According to Lehrer, by 2007, scientists
were scratching their heads in exasperation because several large studies began
to show that the drugs were not as efficacious as was presumed in the 1990s,
when the drugs were first introduced. In his words: “But the data presented at
the Brussels meeting made it clear that something strange was happening: the
therapeutic power of the drugs appeared to be steadily waning.” Having followed
the atypicals for the last decade, this piqued our interest. We believe that
the atypical antipsychotics are NOT an example of the type of subtle research
bias that Crabbe is writing about otherwise, but rather an example of
scientists getting closer and closer to the true efficacy of the drugs, as
various types of overt bias (and even outright fraud) are observed, noted, and
integrated into the literature. While Crabbe’s research was designed to explore
the nuances of the scientific method, the story of clinical trials of
antipsychotics does not belong in the same category. We are concerned that this
mis-categorization may be confusing, and explain our different interpretation
of the same story, below. We do not mean to single out Jonah Lehrer for
criticism- he is undoubtedly one of our best science writers,
with the challenging task of understanding and explaining multiple scientific
sub-fields to the layperson. However, we do think that it will be useful to
understand how the atypical antipsychotic story differs from the subtle biases
that complicate other kinds of research.
The
Clinical Trial Process
Lehrer
writes, “Before the effectiveness of a drug can be confirmed, it must be tested
and tested again, different scientists in different labs need to repeat the
protocols and publish their results. The test of replicability, as its known,
is the foundation of modern research.” This portrays the clinical trial
process in the best light possible; one might call it a scientific ideal that
is seldom realized in psychiatric research. Under the current regulatory
process, for a company to get their drug approved, they must submit two
positive studies to the FDA. This would seem to support the importance of
replicability, however, there is a major problem with this. Namely, that
although a company has to submit two studies to the FDA, the company can do as
many studies as they want. As Paul Leber of the FDA CNS division has said, “How do we interpret two positive results in the context of
several more studies that fail to demonstrate that effect? ….in a sense the
sponsor could just do the studies until the cows come home until he gets two of
them that are statistically significant by chance alone, walks them out and
says he has met the criteria.” To get their two positive studies,
they might have to do five.
It
is a mistake, therefore, to think of psychiatric research on patented,
for-profit drugs as an unbiased scientific endeavor. This completely misses the
primary purpose of clinical trials, which are fundamentally designed as the
centerpiece of a company marketing program. When the company eventually submits
their data to the FDA, then they must submit all their data, even the negative
data. But it is up to the company to publish whatever data it wants, and in
most cases, the companies have published the positive trials and withheld the
negative trial data. In other words, the published literature, especially the
early literature, is not a true representation of all the available data on a
drug. And in the case of psychiatric medications, when one examines all
of the data that was collected, the
drugs look less effective, and more harmful, than originally portrayed.
This does not mean the drugs have slowly lost their efficacy- it means
that when all the data are examined, or unbiased experiments finally take place, the scientific community
is able to examine a less biased database regarding the true efficacy of the
drug.
In
psychiatric drug research, this process appears to take 10-20 years, as
increasingly contradictory data slowly trickles in.
But,
Back to Fundamentals
But,
perhaps a more important point is the premise that atypical antipsychotics were
shown to be highly effective in the 1990s. We understand that the drugs were
marketed as highly superior to first-generation antipsychotics- one of us
worked in a psychiatric hospital in the late 1990s, and we watched as
clinicians told patients that the new antipsychotics were miracle drugs. So, it
is surely easy to find research psychiatrists who endorse their use – some with
conflicts-of-interest with the makers of atypicals, others with no such
conflicts but who are eager to find alternatives to first-generation drugs such
as thorazine and haldol. However, it is just as easy to find evidence that
these drugs never should have been considered to be a major improvement over
these older drugs in the 1990s. For instance:
In
1992, the FDA wrote Johnson and Johnson regarding their atypical antipsychotic,
Risperdal: “We would consider any advertisement or promotion labeling for
RISPERDAL false, misleading or lacking fair balance under section 502 of the
Act if there is a presentation of data that conveys the impression that
Risperidone is superior to haloperidol or any other marketed antipsychotic drug
product with regard to safety or effectiveness.” It is hard to imagine a more
clear statement from the FDA- they would not allow advertisements claiming that
Risperdal that superior to the older antipsychotics. (Although they couldn’t
run advertisements claiming this fact, they did use the peer-reviewed
scientific literature to convince clinicians of this claim).
Ten
years later, in 2002, psychiatric historian David Healy wrote the authoritative
history of the antipsychotic drugs, “The Creation of Psychopharmacology.” Healy
dedicated only a few pages to the atypicals, writing, “…they were not obviously
more effective than haloperidol [haldol], except for their marginal benefits on
negative symptoms.”
Professor David Cohen published an article in 2002 analyzing
the methodology used in clinical trials of atypical antipsychotics, concluding
that biased study designs were likely responsible for many of the purported
“benefits” of the newer medications. The list of deliberate confounds is long.
The studies he analyzed were almost exclusively funded by the makers of
atypical antipsychotics.
Many
more examples could be given, but the point should be clear- an examination of
the available evidence from the 1990s forward surely calls in question the
degree to which the atypicals were a major step forward; this issue is
well-covered in the critical literature.
More
recently, there has been clear evidence that scientific evidence of adverse effects was deliberately
withheld by the makers of atypical antipsychotics. Almost every
manufacturer of atypicals has been fined millions of dollars for illegal marketing.
As time goes by, a flow of documents generated through legal discovery
increases what is known about these drugs. Again, this just means that we
uncover more (previously discovered but hidden) data about these drugs, not
that their efficacy is now waning.
Conclusion
The
issue of replicability in research is an interesting one. However, it would be
a mistake to buy into the premise that the efficacy of atypicals has been
dropping dramatically since their introduction in the 1990s. Instead, what has
been waning is the influence of bias and marketing on the perception of the
atypical antipsychotics.
A
more important scientific question, perhaps, is: How do we reduce the amount of
time (nearly 20 years?) that it takes to reduce the impact of this bias and
marketing, and learn the true utility of a new psychiatric medication?
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