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Dynamic prediction by landmarking in competing risks


Correspondence to: M. A. Nicolaie, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands.



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. Copyright © 2012 John Wiley & Sons, Ltd.