Diverse psychological approach or psychotherapy in psilocybin-assisted therapy for clinical depression
Abstract
The resurgent exploration of psilocybin for major depressive disorder management has sparked enthusiasm. In standard clinical trials, psilocybin is administered with accompanying psychological support or psychotherapy. The efficacy of psilocybin-assisted therapy in MDD is conceptualized as a synergistic interplay between psychotherapeutic techniques and psilocybin. However, the psychotherapeutic approaches employed in previous clinical trials vary widely. The absence of a standardized psychological support or psychotherapy poses challenges in training therapists to conduct psilocybin-assisted therapy, thereby limiting the application of RCT findings in clinical practice. Pharmaceutical companies have significantly invested in clinical research and filed patents on the production of psilocybin as well as the therapeutic processes (e.g., training of therapists). In psilocybin clinical trials, the inclusion of psychological support or psychotherapy is expected to influence future labeling. The aim of the current study was to explore the association between psychological approaches and antidepressant efficacy in adult patients receiving psilocybin-assisted therapy. Our paper will provide important information for further studies to select the optimal psychological approaches is psilocybin-assisted therapy for adult patients with clinically diagnosed depression Eligibility Criteria Eligible studies were clinical trials in adult patients (≥18 years) with clinical depression (i.e., diagnosed depression), such as distress related to life-threatening diagnoses and terminal illness, MDD, or other psychiatric disorders with comorbid clinical depression. We considered clinical trials with the following study designs: blinded randomized controlled trials (RCTs), open-label RCTs, and single-arm pre-post studies. We excluded microdosing studies, follow-up studies (follow-up after trial completion), head-to-head trials, fixed-order trials, and studies with healthy volunteers. We also excluded conference abstracts, editorials, reviews, meta-analyses, case reports, and case series, as well as publications reporting duplicate data. Data Sources and Search Two reviewers independently searched MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), EMBASE, ClinicalTrial.gov, and PubMed without language restrictions from database inception to January 15, 2024. We also searched grey literature and reviewed reference lists of included studies and related systematic reviews.10 Study Selection and Data Extraction The primary outcome was change in depressive symptoms from baseline (continuous outcome), as measured by a validated rating scale such as the Hamilton Rating Scale for Depression. When multiple measurement tools were used, they were selected in the following order: the Hamilton Rating Scale for Depression, Montgomery-Åsberg Depression Rating Scale, and Beck Depression Inventory (second edition). Outcome data were extracted from the original intention-to-treat or the last observation carrying forward analysis. Two authors independently extracted and reviewed the data, which was further verified by another author. WebPlot Digitizer (https://automeris.io/WebPlotDigitizer/) was used to extract numerical data from the figures. Two reviewers independently extracted data and discrepancies were resolved by consensus and, when necessary, by consulting corresponding authors. WebPlot Digitizer (https://automeris.io/WebPlotDigitizer/) was used to extract numerical data from the figures. We extracted the methodology of the psychological support or psychotherapy of each trial. The extracted study-level variables include author, year, condition, psychotherapeutic model, therapist, preparation session, and integration session. We also extracted sample size, study design, dose of psilocybin, age, sex, comorbidities, and baseline and post-treatment severity of depressive symptoms. Statistical Analysis All statistical analyses were performed using R version 4.3.1 (The R Foundation for Statistical Computing; Vienna, Austria). The meta-analysis within a Bayesian framework was fitted using the Bayesian statistical software Stan called multinma.14 The posterior distributions were obtained from tour Markov chains. There were 50000 iterations per chain and the first 20000 iterations for each chain were discarded as a warm-up. Convergence was assessed by visual inspection of the trace plots of the key parameters for each analysis.
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