ArticleEpidemiology (Cambridge, Mass.)2020
Toward Causally Interpretable Meta-analysis: Transporting Inferences from Multiple Randomized Trials to a New Target Population.
Article in Epidemiology (Cambridge, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 7 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
41 citing papers in PubMed, 7 syntheses or guidelines pooled it, 72 citations in OpenAlex.
- Safety of Stimulants Across Patient Populations: A Meta-Analysis.JAMA network open · 2025Pooled it
- Systematically missing data in causally interpretable meta-analysis.Biostatistics (Oxford, England) · 2024Pooled it
- Assessing the causal effects of a stochastic intervention in time series data: are heat alerts effective in preventing deaths and hospitalizations?Biostatistics (Oxford, England) · 2023Pooled it
- Transportability Methods for Time-to-Event Outcomes: Application in Adjuvant Colon Cancer Trials.JCO clinical cancer informatics · 2022Pooled it
- Systematic review and meta-analysis of randomized trials of hydroxychloroquine for the prevention of COVID-19.European journal of epidemiology · 2022Pooled it
- Methods to Address Confounding and Other Biases in Meta-Analyses: Review and Recommendations.Annual review of public health · 2022Pooled it
- Causally Interpretable Meta-analysis: Application in Adolescent HIV Prevention.Prevention science : the official journal of the Society for Prevention Research · 2022Pooled it
- Aligning Estimands to Strengthen the Credibility of Network Meta-Analysis: Implications for Indirect Treatment Comparisons.Statistics in biopharmaceutical research · 2026Article
- Reluctant Transfer Learning in Penalized Regressions for Individualized Treatment Rules Under Effect Heterogeneity.Statistics in medicine · 2026Article
- Towards a Unified Theory for Semiparametric Data Fusion with Individual-Level Data.Annals of statistics · 2026Article
- A causal meta-analysis framework for clinical trials with unequal randomization ratios.Research synthesis methods · 2026Article
- Article
- Multi-study R-learner for estimating heterogeneous treatment effects across studies using statistical machine learning.Biostatistics (Oxford, England) · 2025Article
- Precision Mental Health: Predicting Heterogeneous Treatment Effects for Depression through Data Integration.Journal of the Royal Statistical Society. Series C, Applied statistics · 2025Article
- Center-specific causal inference with multicenter trials-Interpreting trial evidence in the context of each participating center.Statistical methods in medical research · 2025Article
- Causal inference in multi-cohort studies using the target trial framework to identify and minimize sources of bias.American journal of epidemiology · 2025Article
- Bridged treatment comparisons: an illustrative application in HIV treatment.American journal of epidemiology · 2025Article
- A Two-Stage Method for Extending Inferences From a Collection of Trials.Statistics in medicine · 2025Article
- Strengthening health technology assessment for cancer treatments in Europe by integrating causal inference and target trial emulation.The Lancet regional health. Europe · 2025Review
- When, why and how are estimated effects transported between populations? A scoping review of studies applying transportability methods.European journal of epidemiology · 2025Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
We take steps toward causally interpretable meta-analysis by describing methods for transporting causal inferences from a collection of randomized trials to a new target population, one trial at a time and pooling all trials. We discuss identifiability conditions for average treatment effects in the target population and provide identification results. We show that the assumptions that allow inferences to be transported from all trials in the collection to the same target population have implications for the law underlying the observed data. We propose average treatment effect estimators that rely on different working models and provide code for their implementation in statistical software. We discuss how to use the data to examine whether transported inferences are homogeneous across the collection of trials, sketch approaches for sensitivity analysis to violations of the identifiability conditions, and describe extensions to address nonadherence in the trials. Last, we illustrate the proposed methods using data from the Hepatitis C Antiviral Long-Term Treatment Against Cirrhosis Trial.
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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.