title: Basic concepts and methods for joint models of longitudinal and survival data.
abstract: Joint models for longitudinal and survival data are particularly relevant to many cancer clinical trials and observational studies in which longitudinal biomarkers (eg, circulating tumor cells, immune response to a vaccine, and quality-of-life measurements) may be highly associated with time to event, such as relapse-free survival or overall survival. In this article, we give an introductory overview on joint modeling and present a general discussion of a broad range of issues that arise in the design and analysis of clinical trials using joint models. To demonstrate our points throughout, we present an analysis from the Eastern Cooperative Oncology Group trial E1193, as well as examine some operating characteristics of joint models through simulation studies.
authors.affiliation: Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. ibrahim@bios.unc.edu
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Ibrahim
authors.forename: Haitao
authors.initials: H
authors.lastname: Chu
authors.forename: Liddy M
authors.initials: LM
authors.lastname: Chen
mesh_terms: D002986:Clinical Trials as Topic; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D015233:Models, Statistical; D009369:Neoplasms / Q000175:diagnosis / Q000401:mortality* / Q000628:therapy; D016016:Proportional Hazards Models; D011788:Quality of Life; D012680:Sensitivity and Specificity; D016019:Survival Analysis