ArticleStatistics in medicine2013
Interpreting meta-regression: application to recent controversies in antidepressants' efficacy.
Article in Statistics in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Pooled it
- Corticosteroids and Cognition: A Meta-Analysis.Neuropsychology review · 2019Pooled it
- A meta-analysis of the effects of antidepressants on cognitive functioning in depressed and non-depressed samples.Neuropsychology review · 2018Pooled it
- Dynamic Resistance Training as Stand-Alone Antihypertensive Lifestyle Therapy: A Meta-Analysis.Journal of the American Heart Association · 2016Pooled it
- Acute Exercise and Appetite-Regulating Hormones in Overweight and Obese Individuals: A Meta-Analysis.Journal of obesity · 2016Pooled it
- Effects of low-volume high-intensity interval training (HIT) on fitness in adults: a meta-analysis of controlled and non-controlled trials.Sports medicine (Auckland, N.Z.) · 2014Pooled it
- Baseline symptom severity and efficacy of Silexan in patients with anxiety disorders: A symptom-based, patient-level analysis of randomized, placebo-controlled trials.European psychiatry : the journal of the Association of European Psychiatrists · 2024Review
- Gender, Racial, and Socioeconomic Disparities on Social and Behavioral Skills for K-8 Students With and Without Interventions: An Integrative Data Analysis of Eight Cluster Randomized Trials.Prevention science : the official journal of the Society for Prevention Research · 2023Article
- The clinical significance of duration of untreated psychosis: an umbrella review and random-effects meta-analysis.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2021Article
- Evaluating construct equivalence of youth depression measures across multiple measures and multiple studies.Psychological assessment · 2019Article
- Two-Year Impact of Prevention Programs on Adolescent Depression: an Integrative Data Analysis Approach.Prevention science : the official journal of the Society for Prevention Research · 2018Article
- Causal Inference for Meta-Analysis and Multi-Level Data Structures, with Application to Randomized Studies of Vioxx.Psychometrika · 2017Article
- No role for initial severity on the efficacy of antidepressants: results of a multi-meta-analysis.Annals of general psychiatry · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
A recent meta-regression of antidepressant efficacy on baseline depression severity has caused considerable controversy in the popular media. A central source of the controversy is a lack of clarity about the relation of meta-regression parameters to corresponding parameters in models for subject-level data. This paper focuses on a linear regression with continuous outcome and predictor, a case that is often considered less problematic. We frame meta-regression in a general mixture setting that encompasses both finite and infinite mixture models. In many applications of meta-analysis, the goal is to evaluate the efficacy of a treatment from several studies, and authors use meta-regression on grouped data to explain variations in the treatment efficacy by study features. When the study feature is a characteristic that has been averaged over subjects, it is difficult not to interpret the meta-regression results on a subject level, a practice that is still widespread in medical research. Although much of the attention in the literature is on methods of estimating meta-regression model parameters, our results illustrate that estimation methods cannot protect against erroneous interpretations of meta-regression on grouped data. We derive relations between meta-regression parameters and within-study model parameters and show that the conditions under which slopes from these models are equal cannot be verified on the basis of group-level information only. The effects of these model violations cannot be known without subject-level data. We conclude that interpretations of meta-regression results are highly problematic when the predictor is a subject-level characteristic that has been averaged over study subjects.
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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.