Joint modeling of longitudinal proportional measurements and survival time with a cure fraction
Joint modeling of longitudinal proportional measurements and survival time with a cure fraction作者机构:School of Mathematical Sciences Dalian University of Technology Departments of Public Health Sciences & Mathematics and StatisticsQueen's UniversityKingston Canadian Cancer Trials Group Queen's UniversityKingston
出 版 物:《Science China Mathematics》 (中国科学:数学(英文版))
年 卷 期:2016年第59卷第12期
页 面:2427-2442页
核心收录:
学科分类:1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
基 金:supported by the Fundamental Research Funds for the Central Universities of China National Natural Science Foundation of China (Grant No. 11601060) Dalian High Level Talent Innovation Programme (Grant No.2015R051) Research Grants from Natural Sciences and Engineering Research Council of Canada
主 题:cure fraction joint model Laplace approximation proportional data simplex distribution survival times
摘 要:In cancer clinical trials and other medical studies, both longitudinal measurements and data on a time to an event(survival time) are often collected from the same patients. Joint analyses of these data would improve the efficiency of the statistical inferences. We propose a new joint model for the longitudinal proportional measurements which are restricted in a finite interval and survival times with a potential cure fraction. A penalized joint likelihood is derived based on the Laplace approximation and a semiparametric procedure based on this likelihood is developed to estimate the parameters in the joint model. A simulation study is performed to evaluate the statistical properties of the proposed procedures. The proposed model is applied to data from a clinical trial on early breast cancer.