Innovative Thinking on Endpoint Selection in Clinical Trials

被引:3
作者
Chow, Shein-Chung [1 ]
Huang, Zhipeng [1 ]
机构
[1] Duke Univ, Sch Med, Dept Biostat & Bioinformat, 2424 Erwin Rd, Durham, NC 27705 USA
关键词
Endpoint Selection; composite endpoint; utility function; therapeutic index;
D O I
10.1080/10543406.2019.1657140
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
In clinical trials, selection of appropriate study endpoints is critical for an accurate and reliable evaluation of safety and effectiveness of a test treatment under investigation. In practice, however, there are usually multiple endpoints available for measurement of disease status and/or therapeutic effect of the test treatment under study. For example, in cancer clinical trials, overall survival, response rate, and/or time to disease progression are usually considered as primary clinical endpoints for evaluation of safety and effectiveness of the test treatment under investigation. Once the study endpoints have been selected, sample size required for achieving a desired power is then determined. It, however, should be noted that different study endpoints may result in different sample sizes. In practice, it is usually not clear which study endpoint can best inform the disease status and measure the treatment effect. Moreover, different study endpoints may not translate one another although they may be highly correlated one another. In this article, we intend to develop an innovative endpoint namely therapeutic index based on a utility function to combine and utilize information collected from all study endpoints. Statistical properties and performances of the proposed therapeutic index are evaluated theoretically. A numerical example concerning a cancer clinical trial is given to illustrate the use of the proposed therapeutic index.
引用
收藏
页码:941 / 951
页数:11
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