The Cox Model With Adaptive Fused Group Bridge Penalty to Incorporate Historical Data Into the Analysis of Clinical Trials With an Application to BMT CTN 1101. Stat Med 2025 Aug;44(18-19):e70233
Date
08/16/2025Pubmed ID
40817818Pubmed Central ID
PMC12614236DOI
10.1002/sim.70233Scopus ID
2-s2.0-105013464110 (requires institutional sign-in at Scopus site)Abstract
The incorporation of historical data (HD) into a clinical trial analysis can improve the precision and efficiency of treatment evaluation if the HD are exchangeable with clinical trial data. Evaluating the exchangeability of these two data sets is challenging, however, as an incorrect assessment of exchangeability yields invalid inference on the treatment effect that may produce bias and inflate the Type I error rate. To address this practical problem, we propose an adaptive fused group bridge penalty to evaluate the comparability of parameters between HD and clinical trial data and make inferences on the treatment effect. The proposed penalty has oracle properties, including consistency for identifying the underlying model and the asymptotic normality of the estimators. Simulation studies show that the proposed method controls the Type I error rate better and has higher power than competing methods under both exchangeable and non-exchangeable settings. We apply the proposed method by reanalyzing a Phase III trial while also leveraging a corresponding HD set.
Author List
Fang X, Kim S, Martens MJ, Logan BR, Woo Ahn KAuthors
Xi Fang Assistant Professor in the Data Science Institute department at Medical College of WisconsinSoyoung Kim PhD, BS, MS Associate Professor in the Data Science Institute department at Medical College of Wisconsin
Brent R. Logan PhD Director, Professor in the Data Science Institute department at Medical College of Wisconsin
Michael Martens PhD Assistant Professor in the Data Science Institute department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
BiasBone Marrow Transplantation
Clinical Trials as Topic
Clinical Trials, Phase III as Topic
Computer Simulation
Data Interpretation, Statistical
Humans
Proportional Hazards Models
