数学大讲堂

Multistate Models for Recurrent Events and Terminal Events

Abstract

During the process of colorectal cancer progression, patients may experience new lesions and are censored by deaths. In this talk, we introduce a class of multistate models with error-prone dynamic covariate and semiparametric coefficients to analyse such a disease progression process. Association between recurrent events and terminal events are naturally addressed under the multistate modelling framework. Past event feedbacks are introduced through dynamic covariates, which are observed as longitudinal data with possible measurement errors. Addressing the dynamic features helps to gain better insights into the mechanism governing the occurrence of multistate event. Both time-varying and time-fixed effects from the prognostic factors are considered. To improve efficiency, we adopt the one-step backfitting algorithm. Asymptotic results of the proposed estimators are provided. Simulation study shows that our proposed model and estimation procedure perform well. We apply the model to a phase III clinical trial of metastatic colorectal cancer conducted by the French Federation of Digestive Oncology.


(Joint work with Miss Chuoxin Ma)


个人简介:潘建新教授,中组部国家“千人计划” 入选者,英国曼彻斯特大学(University of Manchester)数学学院终身教授,英国皇家统计学会(The Royal Statistical Society) 会士(Fellow), 国际统计学会(International Statistical Institute)当选会员(elected member)和美国数理统计学会(Institute of Mathematical Statistics)会员。统计学杂志Biometrics和Biometrical Journal 编委(Associated Editor)。1996年在香港浸会大学获得统计学博士学位,之后到英国洛桑(Rothamsted)实验中心从事博士后研究。2002年10月加盟曼彻斯特大学数学学院,先后仼讲师(2002)、高级讲师(2004)、Reader(2005)。2006年被曼彻斯特大学聘为终身教授,并兼任曼彻斯特大学医学院研究员。曾担任曼大数学学院概率统计系系主任。致力于统计学领域内复杂数据模型的理论研究及其在医学、金融及工业上的应用,取得了多项创新性研究成果。成果发表在包括Journal of the American Statistical Association和Biometrika在内的统计学主流期刊上。至今已发表学术论文100余篇,出版学术专著2部(Growth Curve Models and Statistical Diagnostics和Case-Deletion Diagnostics in Linear Mixed Models),其中1部于2002年由Springer出版社出版。已指导18名博士研究生并获得学位。