Seo, M;
White, IR;
Furukawa, TA;
Imai, H;
Valgimigli, M;
Egger, M;
Zwahlen, M;
(2020)
Comparing methods for estimating patient‐specific treatment effects in individual patient data meta‐analysis.
Statistics in Medicine
10.1002/sim.8859.
(In press).
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Abstract
Meta-analysis of individual patient data (IPD) is increasingly used to synthesize data from multiple trials. IPD meta-analysis offers several advantages over meta-analyzing aggregate data, including the capacity to individualize treatment recommendations. Trials usually collect information on many patient characteristics. Some of these covariates may strongly interact with treatment (and thus be associated with treatment effect modification) while others may have little effect. It is currently unclear whether a systematic approach to the selection of treatment-covariate interactions in an IPD meta-analysis can lead to better estimates of patient-specific treatment effects. We aimed to answer this question by comparing in simulations the standard approach to IPD meta-analysis (no variable selection, all treatment-covariate interactions included in the model) with six alternative methods: stepwise regression, and five regression methods that perform shrinkage on treatment-covariate interactions, that is, least absolute shrinkage and selection operator (LASSO), ridge, adaptive LASSO, Bayesian LASSO, and stochastic search variable selection. Exploring a range of scenarios, we found that shrinkage methods performed well for both continuous and dichotomous outcomes, for a variety of settings. In most scenarios, these methods gave lower mean squared error of the patient-specific treatment effect as compared with the standard approach and stepwise regression. We illustrate the application of these methods in two datasets from cardiology and psychiatry. We recommend that future IPD meta-analysis that aim to estimate patient-specific treatment effects using multiple effect modifiers should use shrinkage methods, whereas stepwise regression should be avoided.
| Type: | Article |
|---|---|
| Title: | Comparing methods for estimating patient‐specific treatment effects in individual patient data meta‐analysis |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/sim.8859 |
| Publisher version: | https://doi.org/10.1002/sim.8859 |
| Language: | English |
| Additional information: | This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Bayesian analysis, individual patient data, meta-regression, shrinkage, variable selection |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10118434 |
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