collaborators

5 papers

stat.AP2026

A Workflow for Evaluating Regional Treatment Effect Heterogeneity in Multi-Regional Clinical Trials

Cong Zhang, Meihua Long, Tianyu Zheng +8

Multi-regional clinical trials (MRCTs) enable efficient global drug development by assessing treatment effects across regions within a single protocol. While powered for overall ef…

stat.ME2026

Assessment of evidence against homogeneity in exhaustive subgroup treatment effect plots

Björn Bornkamp, Jiarui Lu, Frank Bretz

Exhaustive subgroup treatment effect plots are constructed by displaying all subgroup treatment effects of interest against subgroup sample size, providing a useful overview of the…

stat.AP2026

Comparing methods to assess treatment effect heterogeneity in general parametric regression models

Yao Chen, Sophie Sun, Konstantinos Sechidis +3

This paper reviews and compares methods to assess treatment effect heterogeneity in the context of parametric regression models. These methods include the standard likelihood ratio…

stat.AP2026

Using Individualized Treatment Effects to Assess Treatment Effect Heterogeneity

Konstantinos Sechidis, Cong Zhang, Sophie Sun +3

Assessing treatment effect heterogeneity (TEH) in clinical trials is crucial, as it provides insights into the variability of treatment responses among patients, influencing import…

stat.ME2026

Data-driven controlled subgroup selection in clinical trials

Manuel M. Müller, Björn Bornkamp, Frank Bretz +7

Subgroup selection in clinical trials is essential for identifying patient groups that react differently to a treatment, thereby enabling personalised medicine. In particular, subg…