<scp>WATCH</scp>: A Workflow to Assess Treatment Effect Heterogeneity in Drug Development for Clinical Trial Sponsors

This article proposes a Workflow for Assessing Treatment effeCt Heterogeneity (WATCH) in clinical drug development targeted at clinical trial sponsors. WATCH is designed to address the challenges of investigating treatment effect heterogeneity (TEH) in randomized clinical trials, where sample size and multiplicity limit the reliability of findings. The proposed workflow includes four steps: analysis planning, initial data analysis and analysis dataset creation, TEH exploration, and multidisciplinary assessment. The workflow offers a general overview of how treatment effects vary by baseline covariates in the observed data and guides the interpretation of the observed findings based on external evidence and the best scientific understanding. The workflow is exploratory and not inferential/confirmatory in nature but should be preplanned before database lock and analysis start. It is focused on providing a general overview rather than a single specific finding or subgroup with a differential effect.

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Publication Details

Journal
Pharmaceutical Statistics
Published
2024-12-26
DOI
https://doi.org/10.1002/pst.2463
Citations
3
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
2.13

Funders

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article

WATCH: A Workflow to Assess Treatment Effect Heterogeneity in Drug Development for Clinical Trial Sponsors

David Ohlssen, Marc Vandemeulebroecke, Sophie Sun, Yao Chen et al.
3 citations
Pharmaceutical Statistics
Statistical Methods in Clinical Trials
2.13
article

WATCH: A Workflow to Assess Treatment Effect Heterogeneity in Drug Development for Clinical Trial Sponsors

David Ohlssen, Marc Vandemeulebroecke, Sophie Sun, Yao Chen, Björn Bornkamp, Konstantinos Sechidis, Rob Hemmings, Mark Baillie, Stephen J. Ruberg, Jiarui Lu, Cong Zhang
article en
3 citations

Abstract

This article proposes a Workflow for Assessing Treatment effeCt Heterogeneity (WATCH) in clinical drug development targeted at clinical trial sponsors. WATCH is designed to address the challenges of investigating treatment effect heterogeneity (TEH) in randomized clinical trials, where sample size and multiplicity limit the reliability of findings. The proposed workflow includes four steps: analysis planning, initial data analysis and analysis dataset creation, TEH exploration, and multidisciplinary assessment. The workflow offers a general overview of how treatment effects vary by baseline covariates in the observed data and guides the interpretation of the observed findings based on external evidence and the best scientific understanding. The workflow is exploratory and not inferential/confirmatory in nature but should be preplanned before database lock and analysis start. It is focused on providing a general overview rather than a single specific finding or subgroup with a differential effect.

Pharmaceutical StatisticsVol. 24(2)
Novartis (Switzerland) (CH), Novartis (China) (CN), Constellium (United Kingdom) (GB), Tris Pharma (United States) (US), Vertex Pharmaceuticals (United States) (US)
Novartis Pharma
Good health and well-being
Openalex Percentile: Top 11%
Statistical Methods in Clinical Trials
2.13
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