Use of Quantile Treatment Effects Analysis to Describe Antidepressant Response in Randomized Clinical Trials Submitted to the US Food and Drug Administration: A Secondary Analysis of Pooled Trial Data.

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Major depressive disorder (MDD) is a leading cause of global distress and disability. Earlier studies have indicated that antidepressant therapy confers a modest reduction in depressive symptoms on average, but the distribution of this reduction requires more research.


To estimate the distribution of antidepressant response by depression severity.

Design, setting, and participants

In this secondary analysis of pooled trial data, quantile treatment effect (QTE) analysis was conducted from the US Food and Drug Administration (FDA) database of antidepressant monotherapy for patients with MDD, encompassing 232 positive and negative trials submitted to the FDA between 1979 and 2016. Analysis was restricted to participants with severe MDD (17-item Hamilton Rating Scale for Depression [HAMD-17] score ≥20). Data analysis was conducted from August 16, 2022, to April 16, 2023.


Antidepressant monotherapy compared with placebo.

Main outcomes and measures

The distribution of percentage depression response was compared between the pooled treatment arm and pooled placebo arm. Percentage depression response was defined as 1 minus the ratio of final depression severity to baseline depression severity, expressed as a percentage. Depression severity was reported in HAMD-17-equivalent units.


A total of 57 313 participants with severe depression were included in the analysis. There was no significant imbalance in baseline depression severity between the pooled treatment arm and pooled placebo arm, with a mean HAMD-17 difference of 0.037 points (P = .11 by Wilcoxon rank sum test). An interaction term test for rank similarity did not reject the rank similarity governing percentage depression response (P > .99). The entire distribution of depression response was more favorable in the pooled treatment arm than in the pooled placebo arm. The maximum separation between treatment and placebo occurred at the 55th quantile and corresponded to an absolute improvement in depression due to active drug of 13.5% (95% CI, 12.4%-14.4%). The separation between treatment and placebo diminished near the tails of the distribution.

Conclusions and relevance

In this QTE analysis of pooled clinical trial data from the FDA, antidepressants were found to confer a small reduction in depression severity that was broadly distributed across participants with severe depression. Alternatively, if the assumptions behind the QTE analysis are not met, then the data are also compatible with antidepressants eliciting more complete response in a smaller subset of participants than is suggested by this QTE analysis.





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Publication Info

Meyerson, William U, Carl F Pieper and Rick H Hoyle (2023). Use of Quantile Treatment Effects Analysis to Describe Antidepressant Response in Randomized Clinical Trials Submitted to the US Food and Drug Administration: A Secondary Analysis of Pooled Trial Data. JAMA network open, 6(6). p. e2317714. 10.1001/jamanetworkopen.2023.17714 Retrieved from

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Rick Hoyle

Professor of Psychology and Neuroscience

Research in my lab concerns the means by which adolescents and emerging adults manage pursuit of their goals through self-regulation. We take a broad view of self-regulation, accounting for the separate and interactive influences of personality, environment (e.g., home, school, neighborhood), cognition and emotion, and social influences on the many facets of goal management. Although we occasionally study these influences in controlled laboratory experiments, our preference is to study the pursuit of longer-term, personally meaningful goals “in the wild.” Much of our work is longitudinal and involves repeated assessments focused on the pursuit of specific goals over time. Some studies span years and involve data collection once or twice per year. Others span weeks and involve intensive repeated assessments, sometimes several times per day. We use these rich data to model the means by which people manage real goals in the course of everyday life.

In conjunction with this work, we spend considerable time and effort on developing and refining means of measuring or observing the many factors at play in self-regulation. In addition to developing self-report measures of self-control and grit and measures of the processes we expect to wax and wane over time in the course of goal pursuit, we are working on unobtrusive approaches to tracking goal pursuit and progress through mobile phones and wearable devices.

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