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

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.

Authors

Institutions

Publication Details

Journal
Statistics in Medicine
Published
2025-08-01
DOI
https://doi.org/10.1002/sim.70233
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Michael J. Martens, Kwang Woo Ahn, Brent R. Logan, Soyoung Kim et al.
Statistics in Medicine
Statistical Methods in Clinical Trials
article

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

Michael J. Martens, Kwang Woo Ahn, Brent R. Logan, Soyoung Kim, Xi Fang
article en

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.

Statistics in MedicineVol. 44(18-19)
Medical College of Wisconsin (US)
U.S. Department of Health and Human Services, National Institutes of Health, Health Resources and Services Administration, National Heart, Lung, and Blood Institute, Office of Naval Research, National Cancer Institute, National Institute of Allergy and Infectious Diseases, National Center for Advancing Translational Sciences
Good health and well-being
Openalex Percentile: Top 80%
Statistical Methods in Clinical Trials
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

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 — Michael J. Martens, Kwang Woo Ahn, et al. · Statistics in Medicine (2025) | TGRS Research Map | TGRS