Survival competing risks models are very useful for studying the incidence of diseases whose occurrence competes with other possible diseases or health conditions. These models perform properly when working with terminal events, such as death, that imply the conclusion of the corresponding study. But they do not allow the treatment of scenarios with non-terminal competing events that may occur sequentially. Multi-state models are complex survival models. They focus on pathways defined by the temporal and sequential occurrence of numerous events of interest and thus they are suitable for connecting competing non-terminal events as well as to manage other survival scenarios with higher complexity. We discuss competing risks within the framework of multi-state models and clarify the usefulness of both models for analysing epidemiological data. We highlight the power of multi-state models through a real-world study of recurrent hip fracture from Bayesian inferential methodology.
翻译:生存相互竞争的风险模型对于研究发病率非常有用,这些模型的发生与其他可能发生的疾病或健康条件相竞争。这些模型在与诸如死亡等终极事件合作时运作得当,这意味着相应的研究的结论。但是,这些模型不允许处理可能相继发生的非终极竞争事件的各种假设情景。多国家模型是复杂的生存模型。它们侧重于由许多重大事件的时间和连续发生所决定的路径,因此适合将相互竞争的非终点事件联系起来,并管理其他复杂程度更高的生存情景。我们在多国家模型的框架内讨论相互竞争的风险,并澄清这两种模型对分析流行病学数据的有用性。我们通过对贝耶斯人猜想方法的经常断裂痕进行现实世界性研究,强调多国家模型的力量。