Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms
Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms
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DOI：
10.1007/s10985-017-9393-4
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发表时间：
2018-04-01
影响因子：
1.3
通讯作者：
Hughes, Michael D.
中科院分区：
文献类型：
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作者：
Lok, Judith J.;Yang, Shu;Hughes, Michael D.
竞争风险发生在事件发生时间分析中，其中患者可能经历几种类型的事件之一。传统的处理竞争风险数据的方法假定一个删失过程是独立的。在对照临床试验中，删失可能有几个原因：一些是独立的，另一些是依赖的。我们提出了一个估计的累积发病率函数存在独立和依赖的删失机制。我们依赖于半参数理论推导出一个增广逆概率截尾加权（AIPCW）估计。我们证明了使用AIPCW估计相比，通过模拟非增广估计的效率。然后，我们应用我们的方法来评估三种抗HIV方案的安全性和有效性，在艾滋病临床试验组ACTG A5095进行的随机试验。
Competing risks occur in a time-to-event analysis in which a patient can experience one of several types of events. Traditional methods for handling competing risks data presuppose one censoring process, which is assumed to be independent. In a controlled clinical trial, censoring can occur for several reasons: some independent, others dependent. We propose an estimator of the cumulative incidence function in the presence of both independent and dependent censoring mechanisms. We rely on semi-parametric theory to derive an augmented inverse probability of censoring weighted (AIPCW) estimator. We demonstrate the efficiency gained when using the AIPCW estimator compared to a non-augmented estimator via simulations. We then apply our method to evaluate the safety and efficacy of three anti-HIV regimens in a randomized trial conducted by the AIDS Clinical Trial Group, ACTG A5095.