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Causal Inference SIG Webinar: Modern Approaches for Covariate Adjustment in Clinical Trials

30 June 2026

This webinar provides a comprehensive overview of covariate adjustment in clinical trials, covering both regulatory foundations and recent methodological developments. The session opens with an introduction (Daniel Rubin, FDA) to the potential gains from covariate adjustment and discuss key recommendations from the 2023 FDA guidance. This includes considerations for both linear and non-linear models, as well as areas where further research may help refine best practices for registrational trials.

Building on this foundation, Dominic Magirr (Novartis) will review well-accepted methods for covariate adjustment, including standardization (g-computation) using generalized linear models, and covariate-adjusted extensions of the log-rank test with corresponding hazard ratio estimation. The presentation will also highlight the distinction between marginal and conditional estimands and discuss the potential role of prognostic risk scores or “supercovariates.”

The webinar then moves to recent methodological developments beyond current standard practice. Sanne Roels (Johnson & Johnson) will explore extensions such as covariate adjustment in group sequential designs, with particular attention to type I error control, and discuss the move toward data-adaptive approaches, including pre-specified strategies such as Targeted Minimum Loss-Based Estimation (TMLE) across common endpoint types.

Looking ahead, Marlena Bannick (Fred Hutch (Incoming) / University of Washington) will link these future directions with practical implementation. The talk will introduce the RobinCar Family of R packages and discuss the use of machine learning, handling of missing data, and adjustments for small sample sizes. The talk will also discuss promising future directions including covariate adjustment for time-to-event outcomes and how covariate adjustment can be implemented in trials with complex and innovative designs.

The session concludes with a panel discussion led by Jürgen Hummel (Cytel), bringing together regulatory, industry, and academic perspectives to reflect on current practice and future directions in covariate adjustment.

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