SynthesisPloS one2020
On the treatment effect heterogeneity of antidepressants in major depression: A Bayesian meta-analysis and simulation study.
Synthesis in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 6 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Application of variance ratios to assess heterogeneity of spinal manipulative therapy for chronic low back pain: A meta-epidemiological study.PM & R : the journal of injury, function, and rehabilitation · 2026Pooled it
- Do all individuals benefit equally from non-surgical periodontal therapy? Secondary analyses of systematic review data.Journal of periodontal research · 2025Pooled it
- Heterogeneity of Treatment Effects in Internet- and Mobile-Based Interventions for Depression: A Systematic Review and Meta-Analysis.JAMA network open · 2024Pooled it
- Omega-3 fatty acids for depression in adults.The Cochrane database of systematic reviews · 2021Pooled it
- Examining Side Effect Variability of Antipsychotic Treatment in Schizophrenia Spectrum Disorders: A Meta-analysis of Variance.Schizophrenia bulletin · 2021Pooled it
- Individual response to antidepressants for depression in adults-a meta-analysis and simulation study.PloS one · 2020Pooled it
- How amenable is type 2 diabetes treatment for precision diabetology? A meta-regression of glycaemic control data from 174 randomised trials.Diabetologia · 2023Trial
- Response to acute monotherapy for major depressive disorder in randomized, placebo controlled trials submitted to the US Food and Drug Administration: individual participant data analysis.BMJ (Clinical research ed.) · 2022Trial
- Unusual outcome variances as a method to identify potentially problematic clinical trials.PloS one · 2026Article
- An Update on the Effect of Physical Exercise on Depressive Disorder: A Systematic Review with Meta-Analysis and Meta-Regression of Randomized Controlled Trials.Journal of functional morphology and kinesiology · 2025Review
- Article
- Comparing type 1 and type 2 error rates of different tests for heterogeneous treatment effects.Behavior research methods · 2024Article
- Can the potential benefit of individualizing treatment be assessed using trial summary statistics alone?American journal of epidemiology · 2024Article
- Design, analysis, and interpretation of treatment response heterogeneity in personalized nutrition and obesity treatment research.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2023 · on this mapReview
- Reappraising the variability of effects of antipsychotic medication in schizophrenia: a meta-analysis.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2022Article
- Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research.PLoS biology · 2021Article
- Individual Differences in Response to Antidepressants: A Meta-analysis of Placebo-Controlled Randomized Clinical Trials.JAMA psychiatry · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe average treatment effect of antidepressants in major depression was found to be about 2 points on the 17-item Hamilton Depression Rating Scale, which lies below clinical relevance. Here, we searched for evidence of a relevant treatment effect heterogeneity that could justify the usage of antidepressants despite their low average treatment effect.
methodsBayesian meta-analysis of 169 randomized, controlled trials including 58,687 patients. We considered the effect sizes log variability ratio (lnVR) and log coefficient of variation ratio (lnCVR) to analyze the difference in variability of active and placebo response. We used Bayesian random-effects meta-analyses (REMA) for lnVR and lnCVR and fitted a random-effects meta-regression (REMR) model to estimate the treatment effect variability between antidepressants and placebo.
resultsThe variability ratio was found to be very close to 1 in the best fitting models (REMR: 95% highest density interval (HDI) [0.98, 1.02], REMA: 95% HDI [1.00, 1.02]). The between-study standard deviation τ under the REMA with respect to lnVR was found to be low (95% HDI [0.00, 0.02]). Simulations showed that a large treatment effect heterogeneity is only compatible with the data if a strong correlation between placebo response and individual treatment effect is assumed.
conclusionsThe published data from RCTs on antidepressants for the treatment of major depression is compatible with a near-constant treatment effect. Although it is impossible to rule out a substantial treatment effect heterogeneity, its existence seems rather unlikely. Since the average treatment effect of antidepressants falls short of clinical relevance, the current prescribing practice should be re-evaluated.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.