An individualized dynamic risk prediction model that incorporates all available information collected over the follow‐up can be used to choose an optimal treatment strategy in realtime, although existing methods have not been designed to handle competing risks. In this study, we developed a landmark proportional subdistribution hazard (PSH) model and a comprehensive supermodel for dynamic risk prediction with competing risks. Simulations showed that our proposed models perform satisfactorily (assessed by the time‐dependent relative difference, Brier score and area under the receiver operating characteristics curve) under PSH or non‐PSH settings. The models were used to predict the probabilities of developing a distant metastasis among breast cancer patients where death was treated as a competing risk. Prediction can be estimated by using standard statistical packages.

中文翻译：

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具有里程碑意义的比例子分布危害模型，用于动态预测累积入射函数

尽管没有设计现有的方法来应对竞争风险，但可以使用结合了随访过程中收集的所有可用信息的个性化动态风险预测模型来实时选择最佳治疗策略。在这项研究中，我们开发了具有里程碑意义的比例子分布危害（PSH）模型和具有竞争风险的动态风险预测的综合超级模型。仿真表明，在PSH或非PSH设置下，我们提出的模型的性能令人满意（通过与时间有关的相对差异，Brier得分和接收器工作特性曲线下的面积进行评估）。该模型用于预测乳腺癌患者中发生远处转移的可能性，其中将死亡视为竞争风险。