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网络荟萃分析-预测方法在非劣效性试验中的应用。

The network meta-analytic-predictive approach to non-inferiority trials.

机构信息

Statistical Methodology, Development, Novartis Pharma AG, CH-4002 Basel, Switzerland.

出版信息

Stat Methods Med Res. 2013 Apr;22(2):219-40. doi: 10.1177/0962280211432512. Epub 2012 Jan 4.

Abstract

In non-inferiority clinical trials, a test treatment is compared to an active-control rather than to placebo. Such designs are considered when placebo is unethical or not feasible. The critical question is whether the test treatment would have been superior to placebo, had placebo been used in the non-inferiority trial. This question can only be addressed indirectly, based on information from relevant historical trials with data on active-control and placebo. The network meta-analytic-predictive approach to non-inferiority trials is based on a network meta-analysis of the data from the historical trials and the non-inferiority trial, and the prediction of the putative test vs. placebo effect in the non-inferiority trial. The approach extends previous work by incorporating between-trial variability for all relevant parameters and focusing on the parameters in the non-inferiority trial rather than on population means. Two prominent examples with binary outcomes are used to illustrate the approach.

摘要

在非劣效临床试验中,将受试治疗与活性对照药物进行比较,而不是与安慰剂进行比较。当安慰剂不道德或不可行时,会考虑采用此类设计。关键问题是,如果在非劣效试验中使用安慰剂,受试治疗是否会优于安慰剂。这个问题只能基于来自相关历史试验的信息(这些历史试验的数据包含活性对照和安慰剂)进行间接推断。非劣效试验的网络荟萃分析预测方法基于对历史试验和非劣效试验数据的网络荟萃分析,以及对非劣效试验中推测的受试药物与安慰剂效应的预测。该方法通过纳入所有相关参数的试验间变异性,并侧重于非劣效试验中的参数,而不是群体平均值,对之前的工作进行了扩展。使用两个具有二分类结局的著名示例来说明该方法。

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