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学术报告:Testing superiority after the confirmation of non-inferiority for Three-arm Clinical Trials with Multiple Experimental Treatments
编辑:发布时间:2018年10月08日

报告人:钟俊江讲师

        厦门理工学院

报告题目:Testing superiority after the confirmation of non-inferiority for Three-arm Clinical Trials with Multiple Experimental Treatments

报告时间:2018年10月19日下午15:00

报告地点:海韵实验楼108

报告摘要:The objective of a non-inferiority (NI) trial is to assert the efficacy of an experimental (new) treatment compared with a reference (standard) treatment by showing that the experimental treatment retains a substantial proportion of the efficacy of the reference treatment. The marginal loss of efficacy of adopting the experimental treatment has to be justified by its other benefits, such as the alleviation of side effects, reduction of costs, and introduction of less complicated regimens. In three-arm NI studies, it is usual that the sole objective is to demonstrate the experimental treatment is non-inferior to the standard treatment. However, there is a likelihood that the experimental treatment performs better than the standard treatment. In this talk, we propose testing procedures that test superiority after the confirmation of non-inferiority. The advantage of the proposed test procedures is the additional ability to identify superior treatments while retaining an NI testing power comparable to that of existing testing procedures. Single-step and stepwise procedures are derived, and all procedures are designed to control the family-wise type I error rate, then compared with each other to determine their relative testing power and testing error in a simulation study. Based on a general concept of test power, we derive a viable scheme that enables NI researchers to determine the required sample size of an NI trial. Clinical trial examples will be presented to illustrate our proposed procedures.

报告人简介:钟俊江博士,厦门理工学院应用数学系讲师,2004年于东北师范大学数学与统计学院获得学士学位,2007年在北京师范大学获得概率论与数理统计硕士学位,2017年1月在台湾地区成功大学统计学系获得博士学位。2007年8月应聘到厦门理工学院应用数学系工作,期间曾多次在香港中文大学统计系进行学术访问。研究方向为临床试验、生物医学统计。

联系人:胡杰助理教授

 

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