A targeted learning framework for estimating restricted mean survival time difference using pseudo-observations.

Authors

Man Jin, Yixin Fang

Published in

Contemporary clinical trials. Pages 108489. Oct 08, 2026. Epub Oct 08, 2026.

Abstract

A targeted learning (TL) framework is developed to estimate the difference in the restricted mean survival time (RMST) for a clinical trial with time-to-event outcomes. The approach starts by defining the target estimand as the RMST difference between investigational and control treatments. Next, an efficient estimation method is introduced: a targeted minimum loss estimator (TMLE) utilizing pseudo-observations. Moreover, a version of the copy reference (CR) approach is developed to perform a sensitivity analysis for right-censoring. The proposed TL framework is demonstrated using a real data application.

PMID:
42849710
Bibliographic data and abstract were imported from PubMed on 09 Oct 2026.

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