A new Bayesian model for survival data with a surviving fraction
A new Bayesian model for survival data with a surviving fraction
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DOI：
10.2307/2670006
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发表时间：
1999-09-01
影响因子：
3.7
通讯作者：
Sinha, D
中科院分区：
文献类型：
--
作者：
Chen, MH;Ibrahim, JG;Sinha, D
我们考虑使用贝叶斯方法对具有存活（治愈）分数的人群的右截尾存活数据进行处理。我们提出一个模型，是完全不同于标准的混合模型的固化率。我们提供了一个自然的动机和模型的解释，并得出了它的几个新性质。首先，我们证明了模型具有比例风险结构，协变量自然取决于治愈率。其次，我们推导了所提模型的几个危险函数的性质，并与混合模型建立了固化率的数学关系。详细讨论了先验启发，并提出了非信息先验分布和信息先验分布的分类。推导了所提出的先验和后验的几个理论性质，并与标准混合模型进行了比较。详细讨论了黑色素瘤临床试验的真实数据集。
We consider Bayesian methods for right-censored survival data for populations with a surviving (cure) fraction. We propose a model that is quite different from the standard mixture model for cure rates. We provide a natural motivation and interpretation of the model and derive several novel properties of it. First, we show that the model has a proportional hazards structure, with the covariates depending naturally on the cure rate. Second, we derive several properties of the hazard function for the proposed model and establish mathematical relationships with the mixture model for cure rates. Prior elicitation is discussed in detail, and classes of noninformative and informative prior distributions are proposed. Several theoretical properties of the proposed priors and resulting posteriors are derived, and comparisons are made to the standard mixture model. A real dataset from a melanoma clinical trial is discussed in detail.