Comparing predictions among competing risks models with time-dependent covariates

Stat Med. 2013 Aug 15;32(18):3089-101. doi: 10.1002/sim.5773. Epub 2013 Mar 13.

Abstract

Prediction of cumulative incidences is often a primary goal in clinical studies with several endpoints. We compare predictions among competing risks models with time-dependent covariates. For a series of landmark time points, we study the predictive accuracy of a multi-state regression model, where the time-dependent covariate represents an intermediate state, and two alternative landmark approaches. At each landmark time point, the prediction performance is measured as the t-year expected Brier score where pseudovalues are constructed in order to deal with right-censored event times. We apply the methods to data from a bone marrow transplant study where graft versus host disease is considered a time-dependent covariate for predicting relapse and death in remission.

Keywords: Brier score; bone marrow transplant studies; competing risks; prediction models; pseudovalues; time-dependent covariates.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bone Marrow Transplantation / adverse effects
  • Graft vs Host Disease / etiology
  • Humans
  • Models, Statistical*
  • Neoplasm Recurrence, Local / etiology
  • Precursor Cell Lymphoblastic Leukemia-Lymphoma / therapy
  • Predictive Value of Tests
  • Risk*