In the process of clinical diagnosis and treatment, the restricted mean survival time (RMST), which reflects the life expectancy of patients up to a specified time, can be used as an appropriate outcome measure. However, the RMST only calculates the mean survival time of patients within a period of time after the start of follow-up and may not accurately portray the change in a patient's life expectancy over time. The life expectancy can be adjusted for the time the patient has already survived and defined as the conditional restricted mean survival time (cRMST). A dynamic RMST model based on the cRMST can be established by incorporating time-dependent covariates and covariates with time-varying effects. We analysed data from a study of primary biliary cirrhosis (PBC) to illustrate the use of the dynamic RMST model. The predictive performance was evaluated using the C-index and the prediction error. The proposed dynamic RMST model, which can explore the dynamic effects of prognostic factors on survival time, has better predictive performance than the RMST model. Three PBC patient examples were used to illustrate how the predicted cRMST changed at different prediction times during follow-up. The use of the dynamic RMST model based on the cRMST allows for optimization of evidence-based decision-making by updating personalized dynamic life expectancy for patients.
翻译:在临床诊断和治疗过程中,可以把反映患者预期寿命至特定时间的有限平均存活时间(RMST)作为适当的结果衡量标准,但是,RMST只计算患者在后续跟踪开始后一段时间内的平均存活时间,可能无法准确描述患者预期寿命的变化;可以对患者已经存活的时间进行调整,并将预期寿命定义为有条件的有限平均存活时间(CRMST);可以采用基于时间的可变变量和具有时间变化效应的可变变量来建立基于PRMST的动态RMST模型;我们从对初级血浆粘合症(PBC)的研究中分析了数据,以说明动态RMST模型的使用情况;利用C-index和预测错误对预测性表现进行评估;拟议的RMST动态模型可以探索预测性因素对生存时间的动态影响,比RMST模型更能预测性绩效。 三个PBC的病人例子用来说明预测的CRMST患者动态模型是如何用动态模型更新个人生命变化的。