Overcoming blinding confounds in psychedelic randomized controlled trials using biomarker driven causal mediation analysis
June 13, 2023 preprint DOI: 10.31234/osf.io/d52ay via OpenAlex
Summary
Psychedelic-assisted therapies show promise for treating mental health conditions, but reported effect sizes in randomized controlled trials may be inflated due to expectancy effects from the de-blinding of participants and study personnel. The article discusses using causal mediation analysis with objectively measured biomarkers to clarify causal pathways in these trials. It emphasizes that psychedelic therapies should not be approved as regular medicines until these pathways are established to avoid low-quality evidence leading to unstable efficacy.
Study at a glance
| Design | randomized controlled trial |
|---|---|
| Key finding | Causal mediation analysis using objectively measured biomarkers could help clarify the causal pathways between treatment and outcome in psychedelic RCTs. |
Abstract
There is great interest in the use of psychedelic-assisted therapies to treat a range of mental health conditions and initial randomized controlled trials (RCTs) trials have generated positive results. However, the effect sizes reported in psychedelic RCTs are likely inflated due to expectancy effects due to the de-blinding of both participants and study personnel to treatment allocation caused by the distinctive psychoactive effects of psychedelic drugs. In this article an introduction to causal inference for randomized controlled trials, the underlying assumptions, and potential confounders along with graphical illustrations is provided. It is proposed that causal mediation analysis using objectively measured mediating biomarkers could be used to identify causal pathways between treatment and outcome in psychedelic RCTs, even with de-blinding of participants and give greater confidence as to the mechanistic basis and efficacy of psychedelic therapies. It is argued that psychedelic therapies should not be approved as regular medicines until causal pathways are clearly established between treatment and outcome. Potential downsides of doing so include, future indication expansion based on low quality clinical trial evidence, the approval of other therapies based on similarly low-quality evidence, and the potential for efficacy to be unstable over time after approval.