Dynamic prediction by landmarking in competing risks

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

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bone Marrow Transplantation / standards
  • Forecasting / methods*
  • Graft vs Host Disease / etiology
  • Humans
  • Leukemia, Myelogenous, Chronic, BCR-ABL Positive / therapy
  • Neoplasm Recurrence, Local
  • Proportional Hazards Models*
  • Risk*