Zhaohui Su, VP of Biostatistics at Ontada, shared a post on LinkedIn:
“Precision medicine is accelerating, and basket trials have emerged as a powerful method to evaluate targeted therapies across biomarker-defined subgroups.
This paper introduces a novel approach that employs covariate adjustment with Bayesian borrowing to enhance inference. This method facilitates more efficient learning across related subgroups while preserving the integrity of subgroup-specific conclusions. It is encouraging to see another effective tool added to our toolbox.”
Title: Covariate Adjustment in Basket Trials Borrowing Information Across Subgroups
Authors: Jiyang Ren, David Robertson, Haiyan Zheng
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