3 citations · 4 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
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…
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…
Evaluating causal effects on time-to-event outcomes in an RCT in Oncology with treatment discontinuation
Veronica Ballerini, Björn Bornkamp, Alessandra Mattei +3
In clinical trials, patients may discontinue treatments prematurely, breaking the initial randomization and, thus, challenging inference. Stakeholders in drug development are gener…