Power behind the throne: A clinical trial simulation study evaluating the impact of controllable design factors on the power of antidepressant trials. Issue 3 (17th April 2019)

• Record Type: Journal Article
• Authors: Chevance, Astrid; Naudet, Florian; Gaillard, Raphaël; Ravaud, Philippe; Porcher, Raphaël
• Is Part Of: International journal of methods in psychiatric research. Volume 28:Issue 3(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-17
• Subjects: antidepressants -- clinical trials -- depression -- methodology -- modeling; Psychiatry -- Research -- Methodology -- Periodicals; Psychiatry -- Periodicals; 616.890072
• DOI: 10.1002/mpr.1779
• Languages: English
• ISSNs: 1049-8931

Abstract

Abstract: Objective: To evaluate the impact of controllable design factors on the power of antidepressants trials. Methods: Using clinical trial simulation (CTS), we analyzed the combined impact on the power of trials of controllable design factors (sample size, outcome metrics, and disease severity at inclusion) and uncontrollable parameters (heterogeneity of diseases labeled "depression" in the source population and selective effects of drugs on items of the Hamilton Depression Rating Scale [HDRS], the most used outcome measurement tool). We elaborated 3, 840 scenarios calibrated with real data, particularly the publication bias‐corrected effect size. Results: For an effect size of 0.26, simulations revealed that in trials with ≤650 participants, power was less than 80%. Among the tested outcome metrics, the "remission" outcome provided more robustness for sample heterogeneity, whereas the continuous outcome "HDRS changes" provided more robustness when investigating drugs with a selective effect on the HDRS items. For the "remission" outcome, the power of trials increased with increasing HDRS threshold at inclusion but decreased with the outcomes "response" and "HDRS changes. Drugs with a selective effect on the HDRS items could not reach the same power as for the reference drug. Conclusion: Our study allows for drawing recommendations to avoid underpowered trials of antidepressants.