ArticleEvidence-based mental health2019
Development and validation of a prediction model for the probability of responding to placebo in antidepressant trials: a pooled analysis of individual patient data.
Article in Evidence-based mental health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 4 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
6 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Prediction model developed on the basis of meta-analysis in the field of medicine: a systematic survey and methodological summaries.BMC medical research methodology · 2025Pooled it
- The risks of adverse events with mirtazapine for adults with major depressive disorder: a systematic review with meta-analysis and trial sequential analysis.BMC psychiatry · 2025Pooled it
- Placebo and nocebo responses in randomised, controlled trials of medications for ADHD: a systematic review and meta-analysis.Molecular psychiatry · 2022Pooled it
- Antidepressants in Children and Adolescents: Meta-Review of Efficacy, Tolerability and Suicidality in Acute Treatment.Frontiers in psychiatry · 2020Pooled it
- Side effect profile and comparative tolerability of 21 antidepressants in the acute treatment of major depression in adults: protocol for a network meta-analysis.Evidence-based mental health · 2019Article
- Optimizing ExpectationsFrontiers in psychiatry · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundIdentifying potential placebo responders among apparent drug responders is critical to dissect drug-specific and nonspecific effects in depression.
objectiveThis project aimed to develop and test a prediction model for the probability of responding to placebo in antidepressant trials. Such a model will allow us to estimate the probability of placebo response among drug responders in antidepressants trials.
methodsWe identified all placebo-controlled, double-blind randomised controlled trials (RCTs) of second generation antidepressants for major depressive disorder conducted in Japan and requested their individual patient data (IPD) to pharmaceutical companies. We obtained IPD (n=1493) from four phase II/III RCTs comparing mirtazapine, escitalopram, duloxetine, paroxetine and placebo. Out of 1493 participants in the four clinical trials, 440 participants allocated to placebo were included in the analyses. Our primary outcome was response, defined as 50% or greater reduction on Hamilton Rating Scale for Depression at study endpoint. We used multivariable logistic regression to develop a prediction model. All available candidate of predictor variables were tested through a backward variable selection and covariates were selected for the prediction model. The performance of the model was assessed by using Hosmer-Lemeshow test for calibration and the area under the ROC curve for discrimination.
findingsPlacebo response rates differed between 31% and 59% (grand average: 43%) among four trials. Four variables were selected from all candidate variables and included in the final model: age at onset, age at baseline, bodily symptoms, and study-level difference. The final model performed satisfactorily in terms of calibration (Hosmer-Lemeshow p=0.92) and discrimination (the area under the ROC curve (AUC): 0.70).
conclusionsOur model is expected to help researchers discriminate individuals who are more likely to respond to placebo from those who are less likely so. CLINICAL IMPLICATIONS: A larger sample and more precise individual participant information should be collected for better performance. Examination of external validity in independent datasets is warranted. TRIAL REGISTRATION NUMBER: CRD42017055912.
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.