报告题目：Precision Medicine: Subgroup Identification in Longitudinal Pharmacogenetic Studies
报 告 人：刘磊 教授（美国圣路易斯华盛顿大学）
In clinical studies, treatment effect may be heterogeneous among patients. It is of interest to identify subpopulations which benefit most from the treatment, regardless of the treatment's overall performance. In this study we are interested in subgroup identification methods in longitudinal pharmacogenetic studies where nonlinear trajectory patterns may be present. Under such a situation, evaluation of the treatment effect entails comparing longitudinal trajectories. We propose a tree-structured subgroup identification method, termed interaction tree for longitudinal trajectories or IT-LT in short, which combines mixed effects models with regression splines to model the nonlinear progression patterns among repeated measures. Extensive simulation studies are conducted to evaluate its performance and an application to an alcohol addiction pharmacogenetic trial demonstrates its advantage.