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Stat Med. 2013 May 30;32(12):2031-47. doi: 10.1002/sim.5665. Epub 2012 Oct 22.

Dynamic prediction by landmarking in competing risks.

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Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, 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.

[Indexed for MEDLINE]

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