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适应性特征设计:一种用于生成并前瞻性测试敏感患者基因表达特征的适应性临床试验设计。

Adaptive signature design: an adaptive clinical trial design for generating and prospectively testing a gene expression signature for sensitive patients.

作者信息

Freidlin Boris, Simon Richard

机构信息

Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA.

出版信息

Clin Cancer Res. 2005 Nov 1;11(21):7872-8. doi: 10.1158/1078-0432.CCR-05-0605.

Abstract

PURPOSE

A new generation of molecularly targeted agents is entering the definitive stage of clinical evaluation. Many of these drugs benefit only a subset of treated patients and may be overlooked by the traditional, broad-eligibility approach to randomized clinical trials. Thus, there is a need for development of novel statistical methodology for rapid evaluation of these agents.

EXPERIMENTAL DESIGN

We propose a new adaptive design for randomized clinical trials of targeted agents in settings where an assay or signature that identifies sensitive patients is not available at the outset of the study. The design combines prospective development of a gene expression-based classifier to select sensitive patients with a properly powered test for overall effect.

RESULTS

Performance of the adaptive design, relative to the more traditional design, is evaluated in a simulation study. It is shown that when the proportion of patients sensitive to the new drug is low, the adaptive design substantially reduces the chance of false rejection of effective new treatments. When the new treatment is broadly effective, the adaptive design has power to detect the overall effect similar to the traditional design. Formulas are provided to determine the situations in which the new design is advantageous.

CONCLUSION

Development of a gene expression-based classifier to identify the subset of sensitive patients can be prospectively incorporated into a randomized phase III design without compromising the ability to detect an overall effect.

摘要

目的

新一代分子靶向药物正进入临床评估的决定性阶段。这些药物中的许多仅使一部分接受治疗的患者受益,可能会被传统的广泛入选标准的随机临床试验方法所忽视。因此,需要开发新的统计方法来快速评估这些药物。

实验设计

我们提出了一种新的适应性设计,用于在研究开始时无法获得识别敏感患者的检测方法或特征的情况下进行靶向药物的随机临床试验。该设计将基于基因表达的分类器的前瞻性开发与用于总体效应的适当效能检验相结合,以选择敏感患者。

结果

在一项模拟研究中评估了适应性设计相对于更传统设计的性能。结果表明,当对新药敏感的患者比例较低时,适应性设计可大幅降低错误拒绝有效新治疗方法的可能性。当新治疗方法广泛有效时,适应性设计检测总体效应的效能与传统设计相似。提供了公式以确定新设计具有优势的情况。

结论

开发基于基因表达的分类器以识别敏感患者子集可以前瞻性地纳入随机III期设计,而不会损害检测总体效应的能力。

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