Godolphin, Peter J;
White, Ian R;
Tierney, Jayne F;
Fisher, David J;
(2022)
Estimating interactions and subgroup-specific treatment effects in meta-analysis without aggregation bias: A within-trial framework.
Research Synthesis Methods
10.1002/jrsm.1590.
(In press).
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Abstract
Estimation of within-trial interactions in meta-analysis is crucial for reliable assessment of how treatment effects vary across participant subgroups. However, current methods have various limitations. Patients, clinicians and policy-makers need reliable estimates of treatment effects within specific covariate subgroups, on relative and absolute scales, in order to target treatments appropriately - which estimation of an interaction effect does not in itself provide. Also, the focus has been on covariates with only two subgroups, and may exclude relevant data if only a single subgroup is reported. Therefore, in this article we further develop the "within-trial" framework by providing practical methods to (1) estimate within-trial interactions across two or more subgroups; (2) estimate subgroup-specific ("floating") treatment effects that are compatible with the within-trial interactions and make maximum use of available data; and (3) clearly present this data using novel implementation of forest plots. We described the steps involved and apply the methods to two examples taken from previously published meta-analyses, and demonstrate a straightforward implementation in Stata based upon existing code for multivariate meta-analysis. We discuss how the within-trial framework and plots can be utilised with aggregate (or "published") source data, as well as with individual participant data, to effectively demonstrate how treatment effects differ across participant subgroups.
| Type: | Article |
|---|---|
| Title: | Estimating interactions and subgroup-specific treatment effects in meta-analysis without aggregation bias: A within-trial framework |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/jrsm.1590 |
| Publisher version: | https://doi.org/10.1002/jrsm.1590 |
| Language: | English |
| Additional information: | Copyright © 2022 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Covariate interaction, effect modifier, floating subgroup, meta-analysis, subgroup analysis, within-trial |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10152223 |
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