Statistical power in clinical trials of interventions for mood, anxiety, and psychotic disorders

Abstract

Background: Previous research has suggested that statistical power is suboptimal in many biomedical disciplines, but it is unclear whether power is better in trials for particular interventions, disorders, or outcome types. We therefore performed a detailed examination of power in trials of psychotherapy, pharmacotherapy, and complementary and alternative medicine (CAM) for mood, anxiety, and psychotic disorders. Methods: We extracted data from the Cochrane Database of Systematic Reviews (Mental Health). We focused on continuous efficacy outcomes and estimated power to detect standardized effect sizes (SMD=0.20-0.80, primary effect size SMD=0.40) and the meta-analytic effect size (ESMA). We performed meta-regression to estimate the influence of including underpowered studies in meta-analyses. Results: We included 216 reviews with 8809 meta-analyses and 36540 studies. Statistical power for continuous efficacy outcomes was very low across intervention and disorder types (overall median [IQR] power for SMD=0.40: 0.33 [0.19-0.54]; for ESMA: 0.15 [0.07-0.44]), only reaching conventionally acceptable levels (80%) for SMD=0.80. Median power to detect the ESMA was higher in TAU/waitlist-controlled (0.54-0.66) or placebo-controlled (0.15-0.40) trials than in trials comparing active treatments (0.07-0.10). Meta-regression indicated that adequately-powered studies produced smaller effect sizes than underpowered studies (B=-0.06, p=0.008). Conclusions: Power to detect both fixed and meta-analytic effect sizes in clinical trials in psychiatry was low across all interventions and disorders examined. As underpowered studies produced larger effect sizes than adequately-powered studies, these results confirm the need to increase sample sizes and to reduce reporting bias against studies reporting null results to improve the reliability of the published literature.