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不择手段?临床试验数据监测中的一些困境。

Stopping at nothing? Some dilemmas of data monitoring in clinical trials.

作者信息

Goodman Steven N

机构信息

Johns Hopkins University Schools of Medicine and Public Health, Baltimore, Maryland 21205, USA.

出版信息

Ann Intern Med. 2007 Jun 19;146(12):882-7. doi: 10.7326/0003-4819-146-12-200706190-00010.

Abstract

This commentary reviews the argument that clinical trials with data monitoring committees that use statistical stopping guidelines should generally not be stopped early for large observed efficacy differences because efficacy estimates may be exaggerated and there is minimal information on treatment harms. Overall, the average of estimates from trials that use these boundaries differs minimally from the true value. Estimates from a given trial that seem implausibly high can be moderated by using Bayesian methods. Data monitoring committees are not ethically required to precisely estimate a large efficacy difference if that difference differs convincingly from zero, and the requirement to detect harms and balance efficacy against harm depends on whether the nature of the harm is known or unknown before the trial.

摘要

本评论回顾了这样一种观点,即对于设有数据监测委员会并采用统计停止准则的临床试验,一般不应因观察到的疗效差异巨大而提前终止,因为疗效估计可能存在夸大,且关于治疗危害的信息极少。总体而言,采用这些界限的试验估计值的平均值与真实值的差异极小。通过使用贝叶斯方法,可以对给定试验中看似高得离谱的估计值进行调整。如果疗效差异与零有明显区别,那么从伦理角度而言,数据监测委员会并不需要精确估计巨大的疗效差异,而且检测危害以及权衡疗效与危害的要求取决于在试验前危害的性质是否已知。

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