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非劣效性临床试验的一种循证方法。

An evidential approach to non-inferiority clinical trials.

作者信息

Wang Sue-Jane, Blume Jeffrey D

机构信息

Office of Biostatistics, Office of Translational Sciences, CDER/US FDA, 10903 New Hampshire Ave., Silver Spring, MD 20993, USA.

出版信息

Pharm Stat. 2011 Sep-Oct;10(5):440-7. doi: 10.1002/pst.513. Epub 2011 Sep 19.

Abstract

We present likelihood methods for defining the non-inferiority margin and measuring the strength of evidence in non-inferiority trials using the 'fixed-margin' framework. Likelihood methods are used to (1) evaluate and combine the evidence from historical trials to define the non-inferiority margin, (2) assess and report the smallest non-inferiority margin supported by the data, and (3) assess potential violations of the constancy assumption. Data from six aspirin-controlled trials for acute coronary syndrome and data from an active-controlled trial for acute coronary syndrome, Organisation to Assess Strategies for Ischemic Syndromes (OASIS-2) trial, are used for illustration. The likelihood framework offers important theoretical and practical advantages when measuring the strength of evidence in non-inferiority trials. Besides eliminating the influence of sample spaces and prior probabilities on the 'strength of evidence in the data', the likelihood approach maintains good frequentist properties. Violations of the constancy assumption can be assessed in the likelihood framework when it is appropriate to assume a unifying regression model for trial data and a constant control effect including a control rate parameter and a placebo rate parameter across historical placebo controlled trials and the non-inferiority trial. In situations where the statistical non-inferiority margin is data driven, lower likelihood support interval limits provide plausibly conservative candidate margins.

摘要

我们提出了在“固定界值”框架下定义非劣效性界值以及衡量非劣效性试验证据强度的似然方法。似然方法用于:(1)评估和整合来自历史试验的证据以定义非劣效性界值;(2)评估并报告数据支持的最小非劣效性界值;(3)评估恒定性假设可能被违反的情况。用于说明的是六项急性冠状动脉综合征阿司匹林对照试验的数据以及一项急性冠状动脉综合征活性对照试验(即缺血综合征评估策略组织(OASIS - 2)试验)的数据。在衡量非劣效性试验的证据强度时,似然框架具有重要的理论和实际优势。除了消除样本空间和先验概率对“数据中的证据强度”的影响外,似然方法还保持了良好的频率主义性质。当适合为试验数据假设一个统一的回归模型以及在历史安慰剂对照试验和非劣效性试验中包括对照率参数和安慰剂率参数的恒定对照效应时,可在似然框架中评估恒定性假设的违反情况。在统计非劣效性界值由数据驱动的情况下,较低的似然支持区间下限提供了合理保守的候选界值。

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