[A new perspective of survival data on clinical epidemiology: introduction of competitive risk model].

Competing risks occur frequently in the analysis of survival data that should be dealt with competing risk models. Competing risk is an event whose occurrence precludes the occurrence of the primary event of interest. Previous commonly used Kaplan-Meier method tends to overestimate the cumulative survival functions, while the traditional Cox proportional hazards model falsely evaluates the effects of covariates on the hazard related to the occurrence of the event. There are few domestic reports mentioning the concept, application and methodology of competing risk model as well as the implementation procedures or resolution of model conditions and parameters. The current work aims to explain the core concept and methodology of the competing risk model and to illustrate the process of analysis on cumulative incidence rate, using both the cause-specific hazard function model and the sub-distribution hazard function model. Software macro code in SAS 9.4 is also provided to assist clinical researchers to further understand the application of the model so to properly analyze the survival data.临床生存数据常常伴有多个结局，各结局间存在竞争关系，忽略竞争风险使用传统单因素Kaplan-Meier法会高估累积死亡率，使用传统多因素Cox有可能错误估计HR值。目前国内临床文献较少提及竞争风险且方法学均未提供具体实现程序，亦无解析主流模型应用条件与参数。为此本文旨在阐述竞争风险的概念与核心模型，以实例解析累积发生率、原因别风险模型、部分分布风险模型正确的应用，并提供相应SAS 9.4程序以便临床研究人员进行竞争风险建模时参考。.