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用治疗获益率和治疗伤害率来描述治疗效果的异质性。

Treatment benefit and treatment harm rate to characterize heterogeneity in treatment effect.

作者信息

Shen Changyu, Jeong Jaesik, Li Xiaochun, Chen Peng-Sheng, Buxton Alfred

机构信息

Department of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana 46202, U.S.A.

出版信息

Biometrics. 2013 Sep;69(3):724-31. doi: 10.1111/biom.12038. Epub 2013 Jul 19.

Abstract

It is well recognized that the conventional summary of treatment effect by averaging across individual patients has its limitation in ignoring the heterogeneous responses to the treatment in the target population. However, there are few alternative metrics in the literature that are designed to capture such heterogeneity. We propose the concept of treatment benefit rate (TBR) and treatment harm rate (THR) that characterize both the overall treatment effect and the magnitude of heterogeneity. We discuss a method to estimate TBR and THR that easily incorporates a sensitivity analysis scheme, and illustrate the idea through analysis of a randomized trial that evaluates the implantable cardioverter-defibrillator (ICD) in reducing mortality. A simulation study is presented to assess the performance of the proposed method.

摘要

众所周知,通过对个体患者进行平均来常规总结治疗效果存在局限性,即忽略了目标人群对治疗的异质性反应。然而,文献中几乎没有旨在捕捉这种异质性的替代指标。我们提出了治疗受益率(TBR)和治疗伤害率(THR)的概念,它们既可以表征总体治疗效果,又能体现异质性的程度。我们讨论了一种估计TBR和THR的方法,该方法很容易纳入敏感性分析方案,并通过对一项评估植入式心脏复律除颤器(ICD)降低死亡率的随机试验的分析来说明这一概念。我们进行了一项模拟研究来评估所提出方法的性能。

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本文引用的文献

1
Subgroup identification from randomized clinical trial data.随机临床试验数据中的亚组识别。
Stat Med. 2011 Oct 30;30(24):2867-80. doi: 10.1002/sim.4322. Epub 2011 Aug 4.

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