Optimal decision rules for biomarker-based subgroup selection for a targeted therapy in oncology.

ABSTRACT: Throughout recent years, there has been a rapidly increasing interest regarding the evaluation of so-called targeted therapies. These therapies are assumed to show a greater benefit in a pre-specified subgroup of patients-commonly identified by a predictive biomarker-as compared to the total patient population of interest. This situation has led to the necessity to develop biostatistical methods allowing an efficient evaluation of such treatments. Among others, adaptive enrichment designs have been proposed as a solution. These designs allow the selection of the most promising patient population based on an efficacy analysis at interim and restricting recruitment to these patients afterwards. As has recently been shown, the performance of the applied interim decision rule in such a design

SUBMITTER: Krisam J 

PROVIDER: S-EPMC4463650 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature