What is it about?
Conventional antidepressant trials exclude approximately 80% of clinically depressed patients. In the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, the largest and most expensive antidepressant trial ever conducted, these exclusion criteria were relaxed so as to obtain a sample that is representative of clinical practice. However, the degree of change on the most widely used measure of depression (the Hamilton Rating Scale for Depression – HAMD – which had been designated the primary outcome in the study’s protocol) had not been reported until a recently published paper in Psychology of Consciousness: Theory, Research, and Practice, permitting, for the first time, a comparison between the STAR*D results and those of conventional clinical trials. In the current analysis, Irving Kirsch and colleagues obtained the raw data from the STAR*D trial from the National Institute of Mental Health. They analyzed the HAMD results and compared them to those of conventional trials. The STAR*D trial did not include a placebo control group. The presence of a placebo group has been shown to decrease the response to antidepressants. Therefore, the most relevant comparison is between the STAR*D results and the results of comparator trials, studies in which one antidepressant is compared to another, with no placebo control group.
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Why is it important?
Kirsch and colleagues reported a mean improvement of 6.6 HAMD points in the STAR*D, less than half that reported in conventional comparator trials (14.8 HAMD points). It is even less than the response to placebo in placebo-controlled randomized clinical trials. A 14-point improvement on the HAMD is equivalent to a rating of “much improved” on the Clinical Global Impression Improvement scale (CGI-I), a widely used scale on which clinicians rate their patients from “very much worse” to “very much improved”. A 7-point improvement corresponds to a CGI-I rating of “minimally improved.” Besides challenging the widespread belief that antidepressants are effective for those to whom they are prescribed, the new analysis suggests the need for changes in the way clinical trials are conducted. Conventional clinical trials exclude mildly and moderately depressed patients, who make up the bulk of those to whom antidepressants are prescribed. They also exclude patients with comorbid medical or psychiatric conditions, well as those who are chronically depressed, substance abusers, or suicidal. These patients were included in the STAR*D trial, and they improved less than those who would have been included in clinical trials.
Perspectives
FDA labelling guidelines state that product labels “should identify important inclusion and exclusion criteria,” including those based on the minimal severity required for entry into the study. As the FDA notes, this information is “important for understanding how to interpret and apply the study results.” The STAR*D outcome data suggests that antidepressants might not be the treatment of choice for those not meeting current clinical trial inclusion criteria. Finally, because the STAR*D trial did not include placebo controls, we cannot evaluate the degree to which the improvement seen was due to the placebo effect or the passage of time. Therefore, it seems important for new randomized clinical trials to be done, in which patients representative of those currently prescribed antidepressants are randomized to receive drug or placebo. Only then can we judge the efficacy of antidepressants for this population.
Irving Kirsch
Harvard University
Read the Original
This page is a summary of: Do outcomes of clinical trials resemble those “real world” patients? A reanalysis of the STAR*D antidepressant data set., Psychology of Consciousness Theory Research and Practice, September 2018, American Psychological Association (APA),
DOI: 10.1037/cns0000164.
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