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改良毒性概率区间法在探索性剂量试验中的应用。

A modified toxicity probability interval method for dose-finding trials.

机构信息

Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.

出版信息

Clin Trials. 2010 Dec;7(6):653-63. doi: 10.1177/1740774510382799. Epub 2010 Oct 8.

Abstract

BACKGROUND

Building on earlier work, the toxicity probability interval (TPI) method, we present a modified TPI (mTPI) design that is calibration-free for phase I trials.

PURPOSE

Our goal is to improve the trial conduct and provide more effective designs while maintaining the simplicity of the original TPI design.

METHODS

Like the TPI method, the mTPI consists of a practical dose-finding scheme guided by the posterior inference for a simple Bayesian model. However, the new method proposes improved dose-finding decision rules based on a new statistic, the unit probability mass (UPM). For a given interval and a probability distribution, the UPM is defined as the ratio of the probability mass of the interval to the length of the interval.

RESULTS

The improvement through the use of the UPM for dose finding is threefold: (1) the mTPI method appears to be safer than the TPI method in that it puts fewer patients on toxic doses; (2) the mTPI method eliminates the need for calibrating two key parameters, which is required in the TPI method and is a known difficult issue; and (3) the mTPI method corresponds to the Bayes rule under a decision theoretic framework and possesses additional desirable large- and small-sample properties.

LIMITATION

The proposed method is applicable to dose-finding trials with a binary toxicity endpoint.

CONCLUSION

The new method mTPI is essentially calibration free and exhibits improved performance over the TPI method. These features make the mTPI a desirable choice for the design of practical trials.

摘要

背景

基于早期的工作,毒性概率区间(TPI)方法,我们提出了一种改进的 TPI(mTPI)设计,该设计对 I 期试验是无校准的。

目的

我们的目标是改进试验实施,并在保持原始 TPI 设计简单性的同时提供更有效的设计。

方法

与 TPI 方法一样,mTPI 由一个实用的剂量发现方案组成,该方案由一个简单贝叶斯模型的后验推断指导。然而,新方法提出了基于新统计量——单位概率质量(UPM)的改进的剂量发现决策规则。对于给定的区间和概率分布,UPM 定义为区间的概率质量与区间长度的比值。

结果

通过使用 UPM 进行剂量发现,有三个改进:(1)mTPI 方法在将患者置于毒性剂量方面似乎比 TPI 方法更安全,因为它将更少的患者置于毒性剂量;(2)mTPI 方法消除了校准 TPI 方法中所需的两个关键参数的需要,这是一个已知的困难问题;(3)mTPI 方法在决策理论框架下对应于贝叶斯规则,并具有额外的理想大样本和小样本特性。

局限性

所提出的方法适用于具有二元毒性终点的剂量发现试验。

结论

新方法 mTPI 本质上是无校准的,并且在性能上优于 TPI 方法。这些特点使 mTPI 成为实用试验设计的理想选择。

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