检验参数竞争风险模型以识别医疗保健中潜在相似的路径
Testing similarity of parametric competing risks models for identifying potentially similar pathways in healthcare
AI总结：
本研究提出一种基于参数竞争风险模型的相似性检验方法，通过测量转移强度最大差异并采用参数化自助法，有效识别医疗保健中潜在相似的患者路径。
摘要：
识别相似的患者路径是医疗保健分析中的一项关键任务。解决这一问题的灵活工具是参数竞争风险模型，其中转移强度可由多种参数分布指定，因此特别可能是时间依赖的。我们通过检查不同健康状态之间的转移来评估两个此类模型之间的相似性。本研究引入了一种测量转移强度随时间变化的最大差异的方法，从而开发出一种用于评估相似性的检验程序。为此，我们提出了一种参数化自助法方法，并提供了证明以确认该程序的有效性。我们通过一项模拟研究评估了所提出方法的性能，考虑了不同的样本量、不同的删失量以及各种相似性阈值。最后，我们通过一项来自泌尿科临床常规实践的案例研究展示了该方法的实际应用，该案例研究启发了本研究。
英文摘要：
The identification of similar patient pathways is a crucial task in healthcare analytics. A flexible tool to address this issue are parametric competing risks models, where transition intensities may be specified by a variety of parametric distributions, thus in particular being possibly time-dependent. We assess the similarity between two such models by examining the transitions between different health states. This research introduces a method to measure the maximum differences in transition intensities over time, leading to the development of a test procedure for assessing similarity. We propose a parametric bootstrap approach for this purpose and provide a proof to confirm the validity of this procedure. The performance of our proposed method is evaluated through a simulation study, considering a range of sample sizes, differing amounts of censoring, and various thresholds for similarity. Finally, we demonstrate the practical application of our approach with a case study from urological clinical routine practice, which inspired this research.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
