Inference on tree-structured subgroups with subgroup size and subgroup effect relationship in clinical trials在临床试验中对具有子组大小和子组效应关系的树形结构子组进行推断

光华讲坛——社会名流与企业家论坛第6534期

主题：Inference on tree-structured subgroups with subgroup size and subgroup effect relationship in clinical trials在临床试验中对具有子组大小和子组效应关系的树形结构子组进行推断

主讲人：香港科技大学 罗远晖 在读博士生

主持人：统计学院 陈雪蓉教授

时间：5月24日 15:30-16:30

举办地点：柳林校区弘远楼408会议室

主办单位：统计研究中心 统计学院 科研处

主讲人简介：

罗远晖，香港科技大学在读博士生。

内容简介：

Subgroup analysis is frequently used to uncover and confirm treatment effect heterogeneity in clinical trials. When multiple candidate subgroups are considered, we often need to make statistical inference on the subgroups simultaneously. Classical multiple testing procedures might suffer from the loss of interpretability and efficiency as they often fail to take subgroup size and subgroup effect relationship into account. In this talk, built on the selective traversed accumulation rules (STAR), we propose a data-adaptive and interactive multiple testing procedure for subgroups which can take subgroup size and subgroup effect relationship into account under tree structure. The proposed method is easy-to-implement and can lead to a more efficient and interpretable inference on tree-structured subgroups. We demonstrate the merit of our proposed method by re-analyzing the panitumumab trial with the proposed method. This talk is based on joint work with Prof. Xinzhou Guo (HKUST).

子组分析经常用于在临床试验中揭示和确认治疗效应的异质性。当考虑多个候选子组时，我们通常需要同时对子组进行统计推断。经典的多重检验程序可能会导致解释性和效率的损失，因为它们通常未考虑子组大小和子组效应关系。在本报告中，基于选择性遍历累积规则（STAR），我们提出了一种数据自适应和交互式的多重检验程序，用于考虑树结构下的子组大小和子组效应关系。所提出的方法易于实现，并可以实现对树形结构子组的更高效和可解释的推断。我们通过使用所提出的方法重新分析泛替单抗试验来展示我们提出的方法的优点。本报告基于与XinzhouGuo教授（香港科技大学）的合作研究。