Multipopulation Tailoring Clinical Trials: Design, Analysis, and Inference Considerations

被引：3

作者：

Millen, Brian A. ^{[1
]}

Dmitrienko, Alex ^{[2
]}

Mandrekar, Sumithra J. ^{[3
]}

Zhang, Zongjun ^{[1
]}

Williams, Dominique ^{[1
]}

机构：

[1] Eli Lilly & Co, Lilly Res Labs, Indianapolis, IN 46285 USA

[2] Quintiles, Durham, NC USA

[3] Mayo Clin, Rochester, MN USA

来源：

THERAPEUTIC INNOVATION & REGULATORY SCIENCE | 2014年 / 48卷 / 04期

关键词：

subgroup analysis; tailored therapeutics; familywise error rate; influence condition; interaction condition; PRESPECIFIED SUBGROUP; BIOMARKER; TRASTUZUMAB; SIGNATURE;

D O I：

10.1177/2168479013519630

中图分类号：

R-058 [];

学科分类号：

摘要：

Several recent publications have focused on statistical considerations that arise in multipopulation tailoring clinical trials that evaluate treatment effect in an overall patient population as well as one or more predefined subpopulations. This paper presents a decision-making framework applicable to these trials and evaluates the operating characteristics of this framework versus one based solely on the results of primary hypothesis tests. The operating characteristics are presented as rates of applicable errors, known as influence errors and interaction errors.

引用

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页码：453 / 462

页数：10

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