A Bayesian Reanalysis of a Trial of Psilocybin versus Escitalopram for Depression
Using Bayes factors with sceptical priors to reanalyse a randomised trial (n=59), the authors found that psilocybin statistically outperformed escitalopram on several depression scales but generally not by clinically meaningful margins (with HAMD‑17 showing moderate evidence for a clinically meaningful benefit), while providing extremely strong evidence of non‑inferiority; results were robust to prior sensitivity. This Bayesian reanalysis offers a more precise, nuanced interpretation of an otherwise indeterminate frequentist outcome and supports further comparative research on psilocybin therapy for depression.
Authors
- Robin Carhart-Harris
- David Nutt
- David Erritzoe
Published
Abstract
Background
A trial of psilocybin (COMP360) versus escitalopram for major depressive disorder (MDD) was reported as negative, as there was no significant difference in the primary outcome, mean change in the 16-item Quick Inventory of Depressive Symptomatology–Self-Report (QIDS SR-16). However, analyses using three other depression scales (17-item Hamilton Depression Rating Scale [HAMD-17], Montgomery and Åsberg Depression Rating Scale [MADRS], and Beck Depression Inventory 1A [BDI-1A]) all significantly favored psilocybin, although without a prespecified plan for multiple comparisons correction.
Methods
Bayesian reanalysis of a trial of two doses of psilocybin (25 mg) versus 6 weeks of escitalopram (20 mg) was done in 59 patients with MDD. We used skeptical priors, which bias estimates toward zero, and Bayes factors, which quantify evidence for or against a hypothesis. We report posterior estimates for the difference between psilocybin and escitalopram for four different depression scales.
Results
Using Bayes factors and “skeptical priors” that bias estimates toward zero, for the hypothesis that psilocybin is superior by any margin, we found indeterminate evidence for QIDS SR-16, strong evidence for BDI-1A and MADRS, and extremely strong evidence for HAMD-17. For the stronger hypothesis that psilocybin is superior by a “clinically meaningful amount” (using literature-defined values of the minimally clinically important difference), we found moderate evidence against it for the QIDS-SR-16, but indeterminate evidence to support it for the BDI-1A. Further, we found moderate evidence supporting psilocybin's clinically meaningful superiority on the MADRS and HAMD-17. For all scales, we found extremely strong evidence for psilocybin's noninferiority versus escitalopram. Findings were robust to prior sensitivity analysis.
Conclusions
The overall pattern of evidence provided by this Bayesian reanalysis supports the following inferences: (1) psilocybin did indeed outperform escitalopram in this trial, but not to an extent that was uniformly clinically meaningful and (2) psilocybin is almost certainly noninferior to escitalopram. These results provide a more precise and nuanced interpretation to previously reported results from this trial and support the need for further research into the relative efficacy of psilocybin therapy for depression with respect to current leading treatments.
Research Summary of 'A Bayesian Reanalysis of a Trial of Psilocybin versus Escitalopram for Depression'
Introduction
A recent randomised trial comparing psilocybin therapy to escitalopram for major depressive disorder reported a non-significant difference on its pre-specified primary outcome, the QIDS SR-16 score from baseline to 6 weeks, yet found significant between-group differences favouring psilocybin on three secondary depression scales. Because multiple comparisons were not pre-specified for correction, the original frequentist interpretation treated the primary outcome as indeterminate and the secondary outcomes as uninterpretable. This pattern motivated a secondary analytic approach that could provide more informative statements about the strength of evidence across all outcomes. Nayak and colleagues therefore performed a Bayesian reanalysis of the original two-arm, double-blind trial to estimate the probability that psilocybin was superior to escitalopram, to test whether any observed differences reached literature-defined minimally clinically important differences (MCIDs), and to assess non-inferiority. The authors argued that Bayesian methods can overcome several limitations of the original frequentist analysis by providing direct probabilistic statements about hypotheses (any effect, clinically meaningful effect, and non-inferiority), by being less vulnerable to multiple comparisons when using appropriate priors, and by distinguishing indeterminate from genuinely null findings.
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Study Details
- Study Typeindividual
- Journal
- Compound
- Topics
- Authors
- APA Citation
Nayak, S. M., Bari, B. A., Yaden, D. B., Spriggs, M. J., Rosas, F. E., Peill, J. M., ... & Carhart-Harris, R. (2023). A Bayesian reanalysis of a trial of psilocybin versus escitalopram for depression. Psychedelic Medicine, 1(1), 18-26.
References (1)
Papers cited by this study that are also in Blossom
Carhart-Harris, R. L., Giribaldi, B., Watts, R. et al. · New England Journal of Medicine (2021)
Cited By (2)
Papers in Blossom that reference this study
Martens, M. A. G., Cunha, B. G., Erritzoe, D. et al. · Translational Psychiatry (2025)
Thurgur, H., Sessa, B., Higbed, L. et al. · Alcohol and Alcoholism (2025)
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