A standardized framework for risk-based assessment of treatment effect heterogeneity in observational healthcare databases

Alexandros Rekkas*, David van Klaveren, Patrick B. Ryan, Ewout W. Steyerberg, David M. Kent, Peter R. Rijnbeek

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
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Abstract

Treatment effects are often anticipated to vary across groups of patients with different baseline risk. The Predictive Approaches to Treatment Effect Heterogeneity (PATH) statement focused on baseline risk as a robust predictor of treatment effect and provided guidance on risk-based assessment of treatment effect heterogeneity in a randomized controlled trial. The aim of this study is to extend this approach to the observational setting using a standardized scalable framework. The proposed framework consists of five steps: (1) definition of the research aim, i.e., the population, the treatment, the comparator and the outcome(s) of interest; (2) identification of relevant databases; (3) development of a prediction model for the outcome(s) of interest; (4) estimation of relative and absolute treatment effect within strata of predicted risk, after adjusting for observed confounding; (5) presentation of the results. We demonstrate our framework by evaluating heterogeneity of the effect of thiazide or thiazide-like diuretics versus angiotensin-converting enzyme inhibitors on three efficacy and nine safety outcomes across three observational databases. We provide a publicly available R software package for applying this framework to any database mapped to the Observational Medical Outcomes Partnership Common Data Model. In our demonstration, patients at low risk of acute myocardial infarction receive negligible absolute benefits for all three efficacy outcomes, though they are more pronounced in the highest risk group, especially for acute myocardial infarction. Our framework allows for the evaluation of differential treatment effects across risk strata, which offers the opportunity to consider the benefit-harm trade-off between alternative treatments.

Original languageEnglish
Article number58
Journalnpj Digital Medicine
Volume6
Issue number1
DOIs
Publication statusPublished - 30 Mar 2023

Bibliographical note

ACKNOWLEDGEMENTS:
A.R. and P.R.R. have received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 80696. The JU receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA.

Publisher Copyright: © 2023, The Author(s).

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