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The publication of this meta-analysis1 received a vast amount of coverage in the UK. This is despite the “bottom line” that the review does not report any novel findings—antidepressants work and their effectiveness increases with baseline severity of depression. This was not the picture painted in the media. Rather the conclusions drawn by the authors took an extreme viewpoint and the review’s publication was sensationalised both by the journal editor and the media. It is difficult to fully understand the reasons for this. Antidepressants have had a bad press in recent years over a number of issues (for example, discontinuation/withdrawal and suicidality) and the authors’ conclusions were in a similar “anti-antidepressant” vein—that they don’t work.
This is not the first time that Irvine Kirsch, Professor of Psychology at the University of Hull has caused a storm about antidepressants. A previous paper in the BMJ2 argued that antidepressants have little or no clinically significant effects. This was a similar conclusion to that of the current paper although drawn for different reasons. To understand how the findings have been sensationalised, and I believe misinterpreted, it is important to separate out the findings in the meta-analysis from the conclusions drawn by the authors.
STUDY DESIGN AND METHODS
The meta-analysis described in this paper has been robustly carried out using standard methodology. Any meta-analysis of published data runs the risk of suffering from publication bias (studies with positive findings being more likely to be submitted by authors and accepted by editors for publication). In an attempt to avoid this bias, Kirsch and colleagues obtained all trial data submitted to the United States Food and Drug Administration (FDA) for six newer antidepressants—fluoxetine, venlafaxine, nefazadone, paroxetine, sertraline and citalopram. The FDA has a requirement that all controlled studies of a particular drug relating to a particular indication have to be submitted to them, irrespective of whether the data are positive and/or published or not. Data from 47 trials were obtained. However it was not possible to obtain mean endpoint depression rating scale scores (the outcome measure being used in the analysis) for five of these studies. Rather than just exclude these studies, the authors decided to exclude antidepressants for which they did not have a full data set in order to minimise the risk of bias. Thus the analysis was actually of 35 trials (5 of fluoxetine, 6 of venlafaxine, 8 of nefazodone and 16 of paroxetine).
Studies included in the analysis were all acute treatment studies of 4–8 weeks’ duration (the majority were for six weeks). It is important to note that most of the studies were done in outpatients. It is stated that two were conducted in in-patients and three in a mixture of in- and outpatients, while 39 were in outpatients. It is not clear how these numbers relate to the 35 studies included in the final meta-analysis.
It is important to understand what the primary outcomes of the meta-analysis were and how they were chosen. This relates to the authors’ previous arguments in this area2 based around the use of categorical outcomes (for example, response vs non-response). It was argued that if the distribution of severity ratings of patients is shifted by just a small extent (for example, reduced by one point on the Hamilton Depression Rating Scale (HDRS) by the active treatment) but the cut-off for the categorical outcome is chosen carefully, then it can appear that the treatment has led to a large increase in the percentage of responders. Moncrieff and Kirsch’s paper led to a deluge of correspondence challenging their conclusions (see http://www.bmj.com/cgi/eletters/331/7509/155#112381). However the argument is statistically correct, and is also the rationale behind the National Institute for Health and Clinical Excellence (NICE) in their depression clinical guideline3 deciding a priori to assess the clinical effectiveness of antidepressants by comparing mean endpoint rating scale scores rather than categorical outcomes. For the difference from placebo to be deemed clinically significant by NICE it needs to be a minimum of three points on the HDRS. Alternatively, NICE said that the standardised mean difference, d (the difference between two means divided by their pooled standard deviation) had to be 0.5 or greater (a standard definition of a “moderate” effect size). These were the cut-offs used for this review although it should be remembered that they are entirely arbitrary by NICE it.
RESULTS OF THE META-ANALYSIS
In the 35 trials analysed 3292 patients had been randomised to active treatment and 1841 to placebo. This analysis showed that those treated with antidepressants had a mean decrease in HDRS of 9.60, while those treated with placebo had a decrease of 7.80 points, a difference of 1.80. This difference was statistically significant, but did not meet the NICE-defined criteria of three points for clinical significance. Likewise the standardised difference, d, was 1.24 for antidepressants and 0.92 for placebo, an effect size of 0.32 and so below the cut-off of 0.5 set by NICE.
Secondary analysis demonstrated a lack of an effect of duration of treatment study or the different antidepressants, although the mean differences for the four antidepressants did vary somewhat (venlafaxine d = 0.42, paroxetine d = 0.47, fluoxetine d = 0.22 and nefazodone d = 0.21). However there was a significant effect of baseline severity of depression on response to antidepressant versus placebo. Data are only shown in relation to the standardised mean difference scores. All the studies except one had approximate baseline Hamilton scores ranging from 23 to 30 and they showed a similar level of improvement with antidepressant (d around 1.24) irrespective of baseline severity. One outlying study with a lower baseline severity of depression (HDRS approximately 17) had a smaller d with active drug. Improvement with placebo decreased with increasing baseline severity across all studies. The difference between antidepressant and placebo was projected to exceed the NICE criteria of d ⩾0.5 when baseline severity exceeded a HDRS score of 28.
Kirsch and colleagues explored the publications relating to the data they obtained from the FDA. For those studies that had been published (at least once) there were frequent inconsistencies in the reported data with that submitted to the FDA, mainly minor differences in the number of patients reported in the studies.
CONCLUSIONS DRAWN BY THE AUTHORS
The authors state that they find that “efficacy reaches clinical significance only in trials involving the most extremely depressed patients, and that this pattern is due to a decrease in the response to placebo rather than an increase in the response to medication.” Their description of the very severe nature of the depression of the patients included in the analysis is based on American Psychiatric Association (APA) definitions of cut-off scores for the HDRS with 23 or more being “very severe” depression.4
COMMENTS ON THE AUTHORS’ CONCLUSIONS
Undoubtedly the findings in this analysis are robust, as far as the studies included in the analysis are concerned. The choice of the data set was based on logical reasoning in trying to avoid publication bias. However it does not include all possible data from studies completed subsequent to FDA submissions. Nevertheless, in line with many previous analyses (including NICE’s own), the meta-analysis demonstrates that antidepressants are significantly better than placebo. Further, in line with previous evidence, the drug-placebo difference increases with increasing severity of baseline illness.5 The conclusion that this is due to a decrease in response to placebo rather than an increase in effectiveness of the drug is entirely fallacious because the magnitude of the therapeutic effect is the difference between active drug and placebo, not the absolute response to active drug.
The subsequent arguments around the conclusions drawn then come down to semantics: how is severity of depression and clinical significance defined. Although Kirsch and colleagues use the APA definition of “very severe” depression (HDRS >23), this is not a universally accepted cut-off. Others have argued that an HDRS of at least 30 indicates severe depression.6 Whatever the rights and wrongs of this debate, it is hard to accept the language used in the paper’s conclusions that only “the most extremely depressed patients” showed a clinically significant response to antidepressants. At most only two out of 35 trials were conducted in inpatients, and suicidality is a virtually universal exclusion criterion from a clinical trial of antidepressants. Many of the studies included in the analysis were conducted in the USA. Such studies rely heavily on patients recruited by advertisement and who may join the study in order to receive free medication and care. It has been argued that there is a tendency in such trials for inflation of baseline HDRS scores so as to allow patients to meet the study entry criteria.
With regard to clinical significance, NICE a priori set a minimum antidepressant-placebo mean end-point difference of three points on the HDRS. As already stated, this figure is entirely arbitrary and not based on any evidence other than the guideline development group’s view that anything less might be hard to see in an individual patient in the clinic. However there are many problems with applying this criterion to data obtained from randomised controlled trials (RCTs). RCTs are simply experimental tools used to test hypotheses—they are not well designed to assess clinical effectiveness. The reason for this is that a response to a drug (that is, change in rating scale score at the end of a trial compared to the baseline) in an RCT results from many processes. Extreme values at baseline can regress to the mean, there can be measurement bias and the illness itself might spontaneously improve. An RCT controls for these through the process of randomisation. Improvement can also result from patients (and doctors) being conditioned to expect a response and attaching meaning to any “side effect” as implying the person is on active drug. These processes, in essence, are the “placebo effect” and in an RCT are controlled for through blinding of patients and raters. Finally, for the active drug alone, there is the specific therapeutic effect. This is calculated by subtracting the response to placebo from the response to the drug. The null hypothesis is that this difference is zero. To be statistically robust, RCT data are analysed on an “intention-to-treat” basis including all randomised patients. This leads to small effect sizes compared to a “per protocol” analysis that looks at the outcomes of patients who complete the study. There are at least two reasons why the placebo response rates might have been particularly high in this meta-analysis that would have made detection of a therapeutic effect of the antidepressants particularly difficult. First, as already described, the patients recruited into RCTs conducted in the USA might be particularly likely to show an early decrease in symptoms following a possibly inflated baseline score to enable them to enter the study. Secondly, overall in the meta-analysis there were two patients treated with antidepressant for every one treated with placebo. If patients have a 2/3 chance of being on an active drug, their placebo response rate is greater than if the chance is just 50%.
In clinical practice we are concerned about how much benefit a patient will get from a drug if they take it for long enough (safety is a separate issue). Further, it matters little whether the patient responds due to a placebo effect or the specific pharmacological actions of the drug, as long as they get better. This is because it is ethically not possible to prescribe placebos, which also work less well if the doctor does not believe the prescription is an active drug.7 It should also be noted that most psychological therapies have been assessed by comparing outcomes with “waiting list controls” or “treatment as usual”. This combines the therapeutic effect of the intervention with any placebo response. If antidepressants were similarly assessed the difference in HDRS end point scores would be way in excess of three points for most RCTs. In the data analysed here, the smallest improvement was six HDRS points with antidepressant.
A noteworthy point of this meta-analysis is that of the minor discrepancies between the published data and that submitted to the FDA. When the media were reporting the study there was a significant focus on the question of hidden data—pharmaceutical companies not publishing negative studies. This issue is an extremely important one, although it should be noted that none of the data analysed had been “hidden”, as they had been submitted to the USA regulatory authorities. Nevertheless, it is of concern that the data submitted were not exactly the same as those published.
It is intriguing that given the same findings different people draw completely different conclusions. As a psychiatrist specialising in the management of mood disorders I have, and will continue, to prescribe patients antidepressants. I believe they work and have an acceptable risk:benefit ratio for many patients. Professor Kirsch has long argued that antidepressants either don’t work or that they have only limited value. The data included in this meta-analysis had been submitted to the FDA. On the basis of their own review, they concluded that the drugs work and should be granted a marketing licence for use in depressed patients, a conclusion that European regulatory authorities arrived at independently.
Competing interests: I have received support to attend academic meetings, and honorarium for speaking engagements and attendance at advisory boards, from a number of pharmaceutical companies who manufacture antidepressants including Eli Lilly, GlaxoSmithKline, Lundbeck, Organon, Pfizer, Servier and Wyeth. I do not hold stock in any pharmaceutical company.