title: Analysis of time-dependent covariates in failure time data.
abstract: In failure time analyses, time-dependent covariates are only rarely used. In some clinical studies, however, consideration of available covariate information over time could be relevant to understanding complex disease processes. We propose the time-dependent Cox model and the linear model of Aalen as two possible approaches for such time-dependent survival analyses. The approaches are illustrated with the data of the Stanford Heart Transplantation Study and a study of malignant glioma. Differences between these models and the baseline analysis are discussed.
authors.affiliation: Department of Biometry and Epidemiology, Ludwig-Maximilians-University, Marchioninistr.15, 81377 München, Germany. aydemir@ibe.med.uni-muenchen.de
authors.forename: U
authors.initials: U
authors.lastname: Aydemir
authors.forename: S
authors.initials: S
authors.lastname: Aydemir
authors.forename: P
authors.initials: P
authors.lastname: Dirschedl
mesh_terms: D000328:Adult; D005910:Glioma / Q000401:mortality / Q000628:therapy; D016027:Heart Transplantation / Q000401:mortality; D006801:Humans; D017567:Karnofsky Performance Status; D016014:Linear Models; D011379:Prognosis; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic; D012984:Software; D016019:Survival Analysis; D013997:Time Factors