Thall Peter F, Cook John D, Estey Elihu H
Department of Biostatistics and Applied Mathematics, The University of Texas, MD Anderson Cancer Center, Houston, USA.
J Biopharm Stat. 2006;16(5):623-38. doi: 10.1080/10543400600860394.
The purpose of this paper is to describe and illustrate an outcome-adaptive Bayesian procedure, proposed by Thall and Cook (2004), for assigning doses of an experimental treatment to successive cohorts of patients. The method uses elicited (efficacy, toxicity) probability pairs to construct a family of trade-off contours that are used to quantify the desirability of each dose. This provides a basis for determining a best dose for each cohort. The method combines the goals of conventional Phase I and Phase II trials, and thus may be called a "Phase I-II" design. We first give a general review of the probability model and dose-finding algorithm. We next describe an application to a trial of a biologic agent for treatment of acute myelogenous leukemia, including a computer simulation study to assess the design's average behavior. To illustrate how the method may work in practice, we present a cohort-by-cohort example of a particular trial. We close with a discussion of some practical issues that may arise during implementation.
本文旨在描述并阐释由索尔和库克（2004年）提出的一种结果适应性贝叶斯程序，该程序用于为连续的患者队列分配实验性治疗的剂量。该方法使用引出的（疗效、毒性）概率对来构建一族权衡轮廓，这些轮廓用于量化每个剂量的合意性。这为确定每个队列的最佳剂量提供了基础。该方法结合了传统I期和II期试验的目标，因此可称为“ I-II期”设计。我们首先对概率模型和剂量寻找算法进行一般性综述。接下来，我们描述该方法在一种用于治疗急性髓性白血病的生物制剂试验中的应用，包括一项计算机模拟研究，以评估该设计的平均表现。为了说明该方法在实际中如何运作，我们给出一个特定试验的逐队列示例。最后，我们讨论了实施过程中可能出现的一些实际问题。
