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.
RESUMEN
Objective Nonparametric maximum likelihood estimate(NPMLE)and Breslow-Fleming-Harrington estimate(BFH)are extremely sensitive to small risk set for left truncated and right censored data,this study aims to develop estimation methods to improve the estimation accuracy and compare the existing methods.Methods We introduced the NPMLE,weighted NPMLE,conditional NPMLE,BFH and a new weighted BFH estimate.Simulation studies were carried out to compare five methods via the integrated absolute error(IAE) and integrated average width(IAW).Results The IAE of NPMLE,BFH,weighted NPMLE,weighted BFH and conditional NPMLE is ascending in turn;The IAW of weighted BFH is the lowest and NPMLE is the largest,BFH,conditional NPMLE and weighted NPMLE is reversed under different censored rate.Conclusion According to the results of simulation and example,weighted BFH and weighted NPMLE is recommended in turn when the risk set is small.Otherwise,the results of five methods would be consistent.