RESUMEN
In the Cox proportional hazards regression model, which is the most commonly used model in survival analysis, the effects of independent variables on survival may not be constant over time and proportionality cannot be achieved, especially when long-term follow-up is required. When this occurs, it would be better to use alternative methods that are more powerful for the evaluation of various effective independent variables, such as milestone survival analysis, restricted mean survival time analysis (RMST), area under the survival curve (AUSC) method, parametric accelerated failure time (AFT), machine learning, nomograms, and offset variable in logistic regression. The aim
RESUMEN
In clinical follow-up studies,hazard ratio (HR) is routinely used to quantify the differences between-groups,however,it is being estimated by the Cox procedure.HR,the ratio of two hazard functions has abstract meaning only and is in lack of the context to give an intuitive explanation of the survival of patients and the assumption of proportional hazards (PH) must be satisfied.Under this context,the restricted mean survival time (RMST) can be used as a relatively effective measure or index of statistics.This paper introduces the RMST-based statistical analysis methods,including estimation of RMST and its difference,hypothesis testing and regression analysis.The application of RMST in data analysis is also introduced.All the evidence demonstrates that RMST can be used as an effective analytical tool with straightforward interpretation.RMST is also more effective than HR in comparing differences between groups,when non-PH is observed.Therefore,RMST is suggested to be stated along with HR in the process of disease efficacy evaluation and prognosis analysis.Cooperation and complement of the two,a precise reflection on the characteristics of data can be expected.
RESUMEN
In clinical follow-up studies,hazard ratio (HR) is routinely used to quantify the differences between-groups,however,it is being estimated by the Cox procedure.HR,the ratio of two hazard functions has abstract meaning only and is in lack of the context to give an intuitive explanation of the survival of patients and the assumption of proportional hazards (PH) must be satisfied.Under this context,the restricted mean survival time (RMST) can be used as a relatively effective measure or index of statistics.This paper introduces the RMST-based statistical analysis methods,including estimation of RMST and its difference,hypothesis testing and regression analysis.The application of RMST in data analysis is also introduced.All the evidence demonstrates that RMST can be used as an effective analytical tool with straightforward interpretation.RMST is also more effective than HR in comparing differences between groups,when non-PH is observed.Therefore,RMST is suggested to be stated along with HR in the process of disease efficacy evaluation and prognosis analysis.Cooperation and complement of the two,a precise reflection on the characteristics of data can be expected.