Mixture cure survival models with dependent censoring
Mixture cure survival models with dependent censoring
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DOI：
10.1111/j.1467-9868.2007.00589.x
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发表时间：
2007-01-01
影响因子：
5.8
通讯作者：
Guha, Subharup
中科院分区：
文献类型：
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作者：
Li, Yi;Tiwari, Ram C.;Guha, Subharup
这篇论文的灵感来自于美国国立卫生研究院监测流行病学和最终结果方案中前列腺癌患者的治愈检测，其中主要终点(例如前列腺癌死亡)和审查原因(例如心脏病死亡)可能是相关的。虽然许多研究人员研究了具有不可忽略治愈分数的混合生存模型来分析生存数据，但还没有人研究存在相依截尾的混合治愈模型。为了解释这种依赖，我们提出了一个更一般的修正模型，该模型允许依赖的删失。我们从竞争风险的角度推导了治愈模型，并利用一类阿基米德Copula模型模拟了截尾时间与生存时间之间的依赖关系。在这个框架内，我们考虑了部分患者被认为治愈时的参数估计、治愈检测和相依截尾情况下潜伏期分布的两样本比较。在此基础上，利用鞅理论得到了大样本结果。我们通过仿真检验了提出的方法的有限样本性能，并将其应用于前列腺癌监测、流行病学和最终结果数据的分析。
The paper is motivated by cure detection among the prostate cancer patients in the National Institutes of Health surveillance epidemiology and end results programme, wherein the main end point (e.g. deaths from prostate cancer) and the censoring causes (e.g. deaths from heart diseases) may be dependent. Although many researchers have studied the mixture survival model to analyse survival data with non-negligible cure fractions, none has studied the mixture cure model in the presence of dependent censoring. To account for such dependence, we propose a more general cure model that allows for dependent censoring. We derive the cure models from the perspective of competing risks and model the dependence between the censoring time and the survival time by using a class of Archimedean copula models. Within this framework, we consider the parameter estimation, the cure detection and the two-sample comparison of latency distributions in the presence of dependent censoring when a proportion of patients is deemed cured. Large sample results by using martingale theory are obtained. We examine the finite sample performance of the proposed methods via simulation and apply them to analyse the surveillance epidemiology and end results prostate cancer data.