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二维剂量探索的序贯连续重新评估方法

Sequential continual reassessment method for two-dimensional dose finding.

作者信息

Yuan Ying, Yin Guosheng

机构信息

Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, U.S.A.

出版信息

Stat Med. 2008 Nov 29;27(27):5664-78. doi: 10.1002/sim.3372.

Abstract

It is common to encounter two-dimensional dose finding in phase I trials, for example, in trials combining multiple drugs, or in single-agent trials that simultaneously search for the maximum tolerated dose (MTD) and the optimal treatment schedule. In these cases, the traditional single-agent dose-finding methods are not directly applicable. We propose a simple and adaptive two-dimensional dose-finding design that can accommodate any type of single-agent dose-finding method. In particular, we convert the two-dimensional dose-finding trial to a series of one-dimensional dose-finding subtrials along shortened line search segments by fixing the dose level of one drug. We then conduct the subtrials sequentially. Based on the MTD obtained from the completed one-dimensional trial, we eliminate the doses that lie outside of the search range based on the partial order, and thereby efficiently shrink the two-dimensional dose-finding space. The proposed design dramatically reduces the sample size and still maintains good performance. We illustrate the design through extensive simulation studies motivated by clinical trials evaluating multiple drugs or dose and schedule combinations.

摘要

在I期试验中,二维剂量探索很常见,例如在联合多种药物的试验中,或在同时寻找最大耐受剂量(MTD)和最佳治疗方案的单药试验中。在这些情况下,传统的单药剂量探索方法并不直接适用。我们提出了一种简单且自适应的二维剂量探索设计,它可以采用任何类型的单药剂量探索方法。具体而言,我们通过固定一种药物的剂量水平,将二维剂量探索试验转换为一系列沿着缩短的线搜索段进行的一维剂量探索子试验。然后我们依次进行这些子试验。基于从已完成的一维试验中获得的MTD,我们根据偏序消除搜索范围之外的剂量,从而有效地缩小二维剂量探索空间。所提出的设计显著减少了样本量,同时仍保持良好的性能。我们通过由评估多种药物或剂量与方案组合的临床试验推动的广泛模拟研究来说明该设计。

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