The Cross-Validated Adaptive Signature Design
The Cross-Validated Adaptive Signature Design
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DOI：
10.1158/1078-0432.ccr-09-1357
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发表时间：
2010-01-15
影响因子：
11.5
通讯作者：
Simon, Richard
中科院分区：
文献类型：
--
作者：
Freidlin, Boris;Jiang, Wenyu;Simon, Richard
目的：许多抗癌疗法仅使一小部分接受治疗的患者受益，并且可能会被设计 III 期临床试验的传统广泛资格方法所忽视。微阵列等新生物技术可用于识别最有可能从抗癌治疗中受益的患者。然而，由于基因组数据的高维性质，在设计最终的 III 期试验时开发可靠的分类器可能不可行。 实验设计：此前，Freidlin 和 Simon（临床癌症研究，2005 年）引入了自适应特征设计，该设计结合了敏感患者分类器的前瞻性开发和单个关键试验中总体效果的适当动力测试。在本文中，我们提出了自适应签名设计的交叉验证扩展，它优化了分类器开发和设计验证组件的效率。结果：新设计通过模拟进行评估，并应用于随机乳腺癌试验的数据。结论：交叉验证方法被证明可以显着提高自适应签名设计的性能。我们还描述了估计已确定的敏感亚群治疗效果的方法。临床癌症研究； 16(2)； 691-8。 (C) 2010 AACR。
Purpose: Many anticancer therapies benefit only a subset of treated patients and may be overlooked by the traditional broad eligibility approach to design phase III clinical trials. New biotechnologies such as microarrays can be used to identify the patients that are most likely to benefit from anticancer therapies. However, due to the high-dimensional nature of the genomic data, developing a reliable classifier by the time the definitive phase III trail is designed may not be feasible.Experimental Design: Previously, Freidlin and Simon (Clinical Cancer Research, 2005) introduced the adaptive signature design that combines a prospective development of a sensitive patient classifier and a properly powered test for overall effect in a single pivotal trial. In this article, we propose a cross-validation extension of the adaptive signature design that optimizes the efficiency of both the classifier development and the validation components of the design.Results: The new design is evaluated through simulations and is applied to data from a randomized breast cancer trial.Conclusion: The cross-validation approach is shown to considerably improve the performance of the adaptive signature design. We also describe approaches to the estimation of the treatment effect for the identified sensitive subpopulation. Clin Cancer Res; 16(2); 691-8. (C) 2010 AACR.