标题： 一种用于疾病-死亡数据的加速失效时间回归模型：易感性方法 显示英文标题

标题： An Accelerated Failure Time Regression Model for Illness-Death Data: A Frailty Approach

摘要： 本文提出了一种新的模型和估计程序，用于处理病程死亡生存数据，其中风险函数遵循加速失效时间（AFT）模型。 共享易感变量通过诱导受试者失效时间之间的正相关性，来处理在给定观察到的协变量时非终止事件与终止事件之间的未观察到的依赖关系。 通过基于核平滑的期望最大化（EM）算法开发了半参数最大似然估计程序，并通过加权自助法估计方差。 该模型在现有的基于易感性的病程死亡模型背景下提出，强调了当前工作的贡献。 使用提议的和现有的病程死亡模型分析了鹿特丹肿瘤库的乳腺癌数据。 结果根据新的图形拟合优度程序进行对比和评估。 模拟结果和数据分析很好地展示了在病程死亡框架下，共享易感变量与AFT回归模型的实际实用性。 显示英文摘要

摘要： This work presents a new model and estimation procedure for the illness-death survival data where the hazard functions follow accelerated failure time (AFT) models. A shared frailty variate induces positive dependence among failure times of a subject for handling the unobserved dependency between the non-terminal and the terminal failure times given the observed covariates. Semi-parametric maximum likelihood estimation procedure is developed via a kernel smoothed-aided EM algorithm, and variances are estimated by weighted bootstrap. The model is presented in the context of existing frailty-based illness-death models, emphasizing the contribution of the current work. The breast cancer data of the Rotterdam tumor bank are analyzed using the proposed and existing illness-death models. The results are contrasted and evaluated based on a new graphical goodness-of-fit procedure. Simulation results and data analysis nicely demonstrate the practical utility of the shared frailty variate with the AFT regression model under the illness-death framework.