title: Dynamic prediction by landmarking in competing risks.
abstract: We propose an extension of the landmark model for ordinary survival data as a new approach to the problem of dynamic prediction in competing risks with time-dependent covariates. We fix a set of landmark time points tLM within the follow-up interval. For each of these landmark time points tLM , we create a landmark data set by selecting individuals at risk at tLM ; we fix the value of the time-dependent covariate in each landmark data set at tLM . We assume Cox proportional hazard models for the cause-specific hazards and consider smoothing the (possibly) time-dependent effect of the covariate for the different landmark data sets. Fitting this model is possible within the standard statistical software. We illustrate the features of the landmark modelling on a real data set on bone marrow transplantation.
authors.affiliation: Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. M.A.Nicolaie@lumc.nl
authors.forename: M A
authors.initials: MA
authors.lastname: Nicolaie
authors.forename: J C
authors.initials: JC
authors.lastname: van Houwelingen
authors.forename: T M
authors.initials: TM
authors.lastname: de Witte
authors.forename: H
authors.initials: H
authors.lastname: Putter
mesh_terms: D016026:Bone Marrow Transplantation / Q000592:standards; D005544:Forecasting / Q000379:methods*; D006086:Graft vs Host Disease / Q000209:etiology; D006801:Humans; D015464:Leukemia, Myelogenous, Chronic, BCR-ABL Positive / Q000628:therapy; D009364:Neoplasm Recurrence, Local; D016016:Proportional Hazards Models; D012306:Risk