David O. Antonuccio
Veterans Affairs Sierra
Nevada Health Care System and University of Nevada School of Medicine
David D. Burns
Stanford University
William G. Danton
Veterans Affairs Sierra
Nevada Health Care System and University of Nevada School of Medicine
Correspondence concerning this article should be addressed to David O.
Antonuccio, University of Nevada School of Medicine, 401 West 2nd Street,
Suite 216, Reno, Nevada 89503.
E-mail: oliver2@aol.com
Apparently antidepressants work, but just barely better than inert
placebos. Kirsch,
Moore, Scoboria, and Nicholls (2002) have gone straight to the heart
of the Food and Drug Administration (FDA) database of blinded, randomized,
placebo-controlled trials used in the initial approval of the most popular
antidepressant medications, including fluoxetine, paroxetine, sertraline,
venlafaxine, nefazadone, and citalopram. The results of their analysis are
stunning and offer the potential for a paradigm shift in the way we view
the efficacy of antidepressant medications. They analyzed 38 studies
involving 6,944 patients treated for an average of 6 weeks and found that
approximately 80% of the antidepressant response was duplicated by
placebo. In the subsample of fluoxetine trials, the placebo response
duplicated 89% of the fluoxetine response.
The mean differences between the drug and placebo conditions averaged
only 2 points on the Hamilton Rating Scale for Depression (HAM-D; Hamilton,
1960). For a typical depressed patient from the FDA sample, with an
average pretreatment HAM-D score of about 25, a 2-point difference is not
clinically significant (Jacobson,
Roberts, Berns, & McGlinchey, 1999). Kirsch
et al. (2002) also found that higher doses of medication did not
result in more improvement, raising the question about whether the small
differences between drug and placebo reflect a "true" antidepressant
effect.
The FDA Database: Science's Trojan Horse
It is hard to think of a database that would offer a more fair
opportunity to evaluate antidepressants. These studies were underwritten
by the pharmaceutical manufacturers themselves, under conditions most
favorable to the active drug condition. They all used a placebo washout
procedure prior to randomization (Antonuccio,
Danton, DeNelsky, Greenberg, & Gordon, 1999), potentially
eliminating both antidepressant nonresponders (i.e., patients already on
an antidepressant before the study starts who get better when they are
taken off of an antidepressant) and placebo responders (i.e., patients who
are not on antidepressants before the study who respond to placebo). The
placebo washout procedure may also tend to retain patients who exhibit
withdrawal symptoms from a prior antidepressant. Imagine the converse: an
antidepressant washout procedure that eliminates all of the antidepressant
responders before a study begins. Such a procedure would surely be
considered biased (Antonuccio,
Burns, Danton, & O'Donohue, 2000).
The FDA studies incorporate another bias as well. The double blind in
these studies is likely to be unintentionally penetrated because of the
pattern of side effects in the active and inactive drug conditions (Greenberg
& Fisher, 1997). Research clinicians routinely educate patients
about potential side effects as part of the standard informed consent
process. Further, these studies rely on measures by clinicians who often
have a major allegiance or stake in the outcome. Efforts to ensure the
integrity of the blind tend to diminish drug efficacy. For example, a
recent review of the Cochrane database of antidepressant studies using
"active" placebos (making side-effect differences more difficult to
detect) found very small or nonsignificant outcome differences, suggesting
that trials using inert placebos may overestimate drug effects (Moncrieff,
Wessely, & Hardy, 2001).
Kirsch
et al. (2002) noted that at least six studies allowed replacement of
nonresponders. This may also inflate estimates of the drug response if it
is subtly related to side effects and limited primarily to the subjects in
the active drug condition (Moncrieff,
2001). A separate analysis excluding these studies might be
illuminating. Also, most studies allowed the prescription of a sedative,
consistent with findings from another recent meta-analysis of
antidepressant trials (Walsh,
Seidman, Sysko, & Gould, 2002). If patients in the drug condition
were more likely to take sedatives or antidepressants with sedative
properties, results could be distorted because there are at least 6 points
on the HAM-D that favor medications with sedative properties (Moncrieff,
2001).
Given that patients tend to report smaller differences than clinicians
(Moncrieff,
2001), one is left to wonder how the pattern of results would look
using self-report measures like the Beck Depression Inventory (Beck,
Ward, Mendelson, Mock, & Erbaugh, 1961). Another question that
remains unanswered has to do with what happens to these patients over
longer periods, especially after the medications are withdrawn.
In spite of the research design flaws that may favor the drug
condition, there is a huge advantage to the FDA database from a scientific
perspective. The database includes all of the data from initial trials,
published or not, and therefore it is not subject to the usual "file
drawer" and publication biases. It would be interesting to know how many
of these studies actually were published, to get an estimate of the
publication bias in this literature. An indirect estimate of publication
bias is possible by looking at the percentage of studies that resulted in
significant differences. Antidepressants are significantly more effective
than inert placebos in about two thirds of published studies (Thase,
1999). In the FDA database, Kirsch
et al. (2002) found the study medication had a significant advantage
over inert placebo less than half the time (in 20 of 46 trials), similar
to findings from other independent analyses of the same database (Khan,
Khan, & Brown, in press; Laughren,
2001). Such a pattern would be consistent with a failure to publish
about 23% of antidepressant trials, presumably those showing no advantage
to the antidepressant, slightly more than has been estimated in the
fluoxetine literature (Gram,
1994). This is a serious problem, because clinical practice guidelines
based on the published literature fail to take this distortion of the
literature into account (Gilbody
& Song, 2000).
Klein
(2000) and Quitkin
(1999) have argued that because antidepressants have been established
as effective in the treatment of depression, trials that do not find a
statistical advantage of antidepressants over placebo lack "assay
sensitivity" (i.e., the ability to detect specific treatment effects). In
other words, they argue that something is wrong with the sampling or
methodology of such trials, and the results should be discounted or
discarded. If that logic were applied to this meta-analysis, more than
half of the studies would have to be discarded, a strategy that would
seriously distort the overall results. This example graphically
illustrates the hazards of using established "fact" as a reason to throw
out newer contradictory data (see Otto
& Nierenberg, in press).
Some might suggest that comparing antidepressants and placebos after
only 6 weeks of treatment is unfair to the active drug condition and that
longer-term outcome will surely favor the medication. However, data from
the National Institute of Mental Health Collaborative Depression Study
suggest otherwise. The 18-month follow-up data from that multisite trial
(Shea
et al., 1992) found patients assigned to placebo (plus clinical
management) had intent-to-treat outcome comparable to that in the active
drug condition (plus clinical management). Other research suggests that
longer treatment does not lower relapse following drug withdrawal (Viguera,
Baldessarini, & Friedberg, 1998). Even with maintenance
antidepressant treatment, the published literature suggests that up to 33%
of remitted patients experience a return of depressive symptoms (Byrne
& Rothschild, 1998).
It is important to note that the results of Kirsch
et al. (2002) are not entirely new or isolated, even though they may
surprise many readers. The modest advantage over inert placebo replicates
results from many other studies (e.g., Bech
et al., 2000; Khan
et al., in press; Khan,
Warner, & Brown, 2000; Kirsch
& Sapirstein, 1998; Laughren,
2001; Moncrieff
et al., 2001; Preskorn,
1997; Thase,
Entsuah, & Rudolph, 2001). The lack of a dose-response
relationship has also come up repeatedly (e.g., Amsterdam
et al., 1997; Freemantle,
Anderson, & Young, 2000; Preskorn,
1997). Until there are data to support it, increasing an unresponsive
patient's dose of an antidepressant would not seem justified. The 63%
completion rate in the drug conditions from the FDA database is consistent
with an intent-to-treat response rate of about 42% (assuming 66% of
completers are also classified as responders), far below expectations but
quite typical of antidepressant trials (Thase,
1999). On the basis of the usual inclusionary and exclusionary
criteria, only about 15% of patients in a typical outpatient primary care
clinic would even qualify to participate in most antidepressant trials (Zimmerman,
Mattia, & Posternak, 2002), suggesting that the real world outcome
may be even lower. However, despite lack of evidence (Shean,
2001), beliefs about correcting "chemical imbalances" and more
powerful antidepressant effects are likely to persist (Antonuccio
et al., 2000; Double,
2002; Muņoz,
2000).
In Search of "True" Antidepressant Effects
However, the blind is still subject to penetration in the balanced
placebo design. In other words, patients and clinicians may still see
through the deception. A more practical solution that doesn't involve as
much deception and does not require designs more complicated than those
currently in use may be to simply ask clinicians and patients to guess the
actual condition (Hughes
& Krahn, 1985). Then the outcome impact of blind penetration can
be estimated by comparing those patients who are truly blind with those
who are not. This strategy can simulate a balanced placebo design and can
be implemented right now in ongoing studies, with very little additional
cost. At the very least, such a procedure would help settle the debate
about the extent of blind penetration and its impact. To address concerns
that outcome may tip off the condition, clinicians and patients could make
their guesses early in the study before treatment effects take hold (e.g.,
within the first 2 weeks). It has been demonstrated that independent
raters were able to fairly accurately guess treatment conditions in a
placebo-controlled antidepressant study without any outcome data and while
relying only on side-effect profiles (White,
Kando, Park, Waternaux, & Brown, 1992). It is our contention that
no study should be able to claim double blind status and pass peer review
without testing the integrity of the blind (Antonuccio
et al., 2000; Piasecki,
Antonuccio, Steinagel, & Kohlenberg, in press). Statistical
strategies for estimating clinician rater bias (Petkova,
Quitkin, McGrath, Stewart, & Klein, 2000) are laudable but not a
substitute for an actual test of the blind.
There are some important questions that this database won't help
answer. How is it that, with such a weak advantage over placebo,
antidepressants have apparently become the most popular treatment for
depression in the United States (Langer,
2000; Olfson
et al., 2002) and in many parts of the world? Does the small advantage
of antidepressants over placebo justify the risks and side effects
associated with these medications? How have we come to think of
antidepressants as powerful, even "life-saving" treatments in the face of
such weak outcome data (see Beutler,
1998)?
Part of the answer to the last question probably lies in widely
acknowledged publication biases (e.g., Blumenthal,
Campbell, Anderson, Causino, & Louis, 1997; Callaham,
Wears, Weber, Barton, & Young, 1998; Chalmers,
2000; Gilbody
& Song, 2000; Lancet,
2001; Misakian
& Bero, 1998; Rennie,
1999; Wise
& Drury, 1996), often related to conflicts of interest (Campbell,
Louis, & Blumenthal, 1998; Cech
& Leonard, 2001; DeAngelis,
Fontanarosa, & Flanagin, 2001; Fava,
2001; Lo,
Wolf, & Berkeley, 2000) that favor pharmaceutical industry
products. In fact, these biases have so eroded the credibility of the
medical literature (Quick,
2001) that new proposals call for stringent accountability guidelines
(e.g., Davidoff
et al., 2001; Moses
& Martin, 2001) aimed at ensuring researcher independence in study
design, access to data, and right to publish. It remains to be seen
whether these new guidelines will have the desired effect of improving the
quality and the credibility of the literature. Unfortunately, the New
England Journal of Medicine has recently had to relax its strict
policy against financial conflicts of interest by editorial and review
authors (Drazen
& Curfman, 2002), because it could not find enough experts without
financial ties to the drug industry, an issue that has been highlighted in
the antidepressant literature (Angell,
2000).
Yet, publication biases that may inflate the perceived efficacy of
antidepressants cannot fully explain the popularity of some of the newer
medications (Gram,
1994), especially given the reduced cost and equivalent efficacy of
older antidepressants (Geddes,
Freemantle, Mason, Eccles, & Boynton, 2001). A second factor in
the popularity of antidepressant medications generally, and selective
serotonin reuptake inhibitors (SSRIs) in particular, undoubtedly has to do
with extremely effective marketing practices, often framed as
education.
Continuing Medical Advertising
The pharmaceutical industry is at least a $250 billion annual business
worldwide, with the United States accounting for about one third of all
pharmaceutical sales (Louie,
2001). It is America's most profitable industry, number one in return
on revenues, return on assets, and return on equity (Fortune,
2000). According to IMS Health, a pharmaceutical consulting firm, the
industry spent more than $19 billion in 2001 in U.S. advertising alone.
The pharmaceutical industry had a combined lobbying and campaign
contribution budget of $197 million in 1999 and 2000, larger than any
other industry (Wayne
& Peterson, 2001). The industry has 625 registered lobbyists, more
than there are members of congress (Wayne
& Peterson, 2001). Industry underwrites about 70% of all clinical
drug trials in the United States (DeAngelis
et al., 2001).
The pharmaceutical industry does an outstanding job of marketing its
products, and antidepressants are no exception. In 1999, 3 of the top 10
best-selling pharmaceuticals were the SSRIs Prozac, Paxil, and Zoloft,
accounting for combined revenues of $6.7 billion (Louie,
2001). Revenues generated by SSRIs are growing by about 25% each year
(Kroenke
et al., 2001). Recent polling data suggested that as many as 1 in 8
adult Americans had taken an antidepressant in the past 10 years, and 3.5
billion doses of SSRIs were consumed in 1999 alone (Langer,
2000). About 60% of those who had taken antidepressants indicated they
had taken them for more than 3 months, whereas 46% indicated they had been
taking them for a year or more.
Consumer Reports has documented marketing strategies (Miracle
or Media Drugs, 1992; Pushing
Drugs to Doctors, 1992) that include but are not limited to the
following: (a) giving free samples and information to doctors, (b)
advertising in medical journals, (c) using "ask your doctor" media
advertisements aimed directly at the consumer (see Wolfe,
2002), (d) sponsoring promotional dinner meetings with substantial
gifts or even cash provided for attendees, (e) paying consultants to speak
at scientific meetings where it is possible to circumvent FDA guidelines
that require disclosure of side effects, (f) funding only those research
projects that have a high likelihood of producing favorable results for a
particular drug company's product (see Bodenheimer,
2000), (g) terminating negative studies before they are ready for
publication, (h) involving large numbers of physicians in studies not
intended to yield publishable information but simply designed to yield
maximum product exposure, (i) including "look alike" publication
supplements in professional journals, (j) offering to pay journalists to
cover their products, (k) offering prepackaged information for journalists
in the form of video news releases that give the appearance of having been
independently developed, and (l) helping to fund patient advocacy and
other public interest groups so the consumer group appears to be publicly
carrying the banner of a particular drug.
It is difficult to think of any arena involving information about
medications that does not have significant industry financial or marketing
influences. Industry financial influences extend to federal regulatory
agencies (e.g., Cimons,
1999; Horton,
2001), professional organizations and their journals (Pellegrino
& Relman, 1999), continuing medical education (Christensen
& Tueth, 1998; Coyle,
2002; Romano,
2001; Ross,
Lurie, Wolfe, & Public Citizen's Health Research Group, 2000; Wazana,
2000), scientific researchers (Angell,
2000; Bodenheimer,
2000; Brennan,
1994; Choudry,
Stelfox, & Detsky, 2002; Drazen
& Curfman, 2002; Elliot,
2001; Flanagin
et al., 1998; Krimsky
& Rothenberg, 2001; Krimsky,
Rothenberg, Stott, & Kyle, 1998), media experts (Moynihan
et al., 2000; Steinbrook,
2000; Woloshin
& Schwartz, 2002), and consumer advocacy organizations (e.g., Silverstein,
1999). Respected psychiatric researchers like Marks (Marks
et al., 1993) and Fava
(1998) have warned that such widespread corporate interests may result
in self-selecting academic oligarchies influencing clinical and scientific
information. In fact, those who produce data contrary to industry
interests may find themselves vulnerable to legal, professional, or even
personal attack, directly or indirectly financed by the industry (e.g., Boseley,
2002; Deyo,
Psaty, Simon, Wagner, & Omenn, 1997; Healy,
2002; Marks
et al., 1993; Monbiot,
2002; Rennie,
1997).
It is entirely reasonable for the pharmaceutical industry to market its
products as effectively as possible. The question can be raised, however,
about whether effective marketing sometimes clashes with good science and
with the public interest. Company-sponsored experts, whether they are
researchers or educators, are by definition company employees. They will
be retained only if they offer consistently favorable treatment to the
company's products. It could be argued that their efforts on behalf of
antidepressants often fit more properly under the rubric of marketing or
advertising, not science or education.
Psychotherapy for Depression: No Stronger Medicine
Some might suggest that because there appears to be a small advantage
over placebo, antidepressants should still be considered a first line of
treatment for depression. However, there may be several reasons why
nondrug alternatives ought to be considered first. First, most of the drug
only conditions in studies of antidepressants use supportive weekly visits
adjunctively (e.g., Elkin
et al., 1989) and do not adequately evaluate the efficacy of
medication alone. The resultant therapeutic alliance (e.g., Blatt,
Sanislow, Zuroff, Pilkonis, 1996) may enhance the efficacy of the
medication and give an inaccurate picture of the effectiveness of these
medications in a managed care environment where antidepressants are often
delivered in conjunction with infrequent visits to a mental health
professional.
Another reason to consider psychotherapy as a preferred first line of
treatment is that psychotherapy (particularly cognitive therapy,
behavioral activation, and interpersonal therapy) compares favorably with
medications in the short term, even when the depression is severe (e.g.,
DeRubeis,
Gelfand, Tang, & Simons, 1999), and appears superior to
medications when long term follow-up is considered (Antonuccio,
Danton, & DeNelsky, 1995; Hollon,
Shelton, & Loosen, 1991). In accepting that psychotherapy has
efficacy comparable with that of antidepressants, it is not necessary to
give up the biological model completely, because there is evidence of
metabolic changes associated with improvement in psychotherapy that are
similar to those seen with antidepressants (Brody
et al., 2001; Martin,
Martin, Rai, Richardson, & Royall, 2001). In fact, distinct
metabolic (Mayberg
et al., 2002) and electroencephalogram changes (Leuchter,
Cook, Witte, Morgan, & Abrams, 2002) have also been documented in
patients who respond to placebo.
Whether one subscribes to the Hippocratic dictum "first do no harm" or
takes a cost-benefit approach to treatment, it is impossible to ignore the
fact that antidepressants are not medically benign treatments. The
short-term side effects of SSRIs are well-established and commonly include
agitation, sleep disruption, gastrointestinal problems, and sexual
dysfunction (Antonuccio
et al., 1999). Side effects and medical risks (including risk of
dying) increase when SSRIs are combined with other medications (Dalfen
& Stewart, 2001), as is often the case (Antonuccio
et al., 1999). In addition, the withdrawal symptoms of SSRIs are
substantial for many, if not most, patients (Coupland,
Bell, & Potokar, 1996; Fava,
2002; Rosenbaum,
Fava, Hood, Ashcroft, & Krebs, 1998). Although the data are mixed
and somewhat controversial, other potential risks that warrant further
investigation include the association (although not an established causal
relationship) of SSRIs with breast cancer (e.g., Cotterchio,
Kreiger, Darlington, & Steingart, 2000), acts of deliberate
self-harm (e.g., Donovan
et al., 2000; Healy,
2002), manic episodes (e.g., Preda,
MacLean, Mazure, & Bowers., 2001), and the possibility of
irreversible biochemical changes predisposing some susceptible patients to
chronic depression (e.g., Baldessarini,
1995; Fava,
1995, 2002).
When medical cost offset (Hunsley,
in press), relapse, and side effects are considered in a cost-benefit
analysis, psychotherapy can be very cost-effective, particularly in a
psychoeducational (e.g., therapist-assisted bibliotherapy) or group format
(Antonuccio,
Thomas, & Danton, 1997).
Some might argue that antidepressants are important to stave off
suicide in very depressed patients. However, there is no evidence that
antidepressants reduce the risk of suicide or suicide attempts in
comparison with a placebo in randomized controlled trials (Khan
et al., 2000; Storosum,
van Zwieten, van den Brink, Gersons, & Broekmans, 2001). Finally,
most patients seem to prefer a psychotherapeutic intervention when given
the choice (Chilvers
et al., 2001; Hall
& Robertson, 1998; Jorm,
2000; Paykel,
Hart, & Priest, 1998; Priest,
Vize, Roberts, Roberts, & Tylee, 1996). Despite this repeated
finding, it is often concluded that consumers just need more "education"
about the benefits and safety of antidepressants to bring their
preferences in line with accepted practice (e.g., Paykel
et al., 1998; Priest
et al., 1996).
A Bitter Pill to Swallow
The silver lining in these results for psychiatry is that the
psychiatrist, or at least something about the psychiatric relationship,
and not the pill, appears to facilitate improvement in depression.
Figuring out ways to enhance the therapeutic alliance, originally
pioneered but recently marginalized by organized psychiatry, may prove
more fruitful than modifying the selectivity of antidepressants. There is
no doubt that antidepressants have a biochemical impact on the brain, but
the valence of that impact is open for considerable debate, and whether it
corrects a chemical imbalance is in grave doubt. It may take another
decade, but when the logical arguments and the advertising blitz fail to
discredit the FDA data and when we begin to fully appreciate the cost of
side effects and long-term health risks associated with antidepressants,
American medicine's preference for these medications as the primary
treatment for depression may change. Other popular medical practices have
certainly proven ineffective or too risky over time. One day we may look
back and marvel at the stroke of marketing genius that led to calling
these medications antidepressants in the first place. Kirsch
et al. (2002) have demonstrated that just because a pill is called an
antidepressant, it doesn't necessarily make it so.
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