Bagging survival trees

Stat Med. 2004 Jan 15;23(1):77-91. doi: 10.1002/sim.1593.


Predicted survival probability functions of censored event free survival are improved by bagging survival trees. We suggest a new method to aggregate survival trees in order to obtain better predictions for breast cancer and lymphoma patients. A set of survival trees based on B bootstrap samples is computed. We define the aggregated Kaplan-Meier curve of a new observation by the Kaplan-Meier curve of all observations identified by the B leaves containing the new observation. The integrated Brier score is used for the evaluation of predictive models. We analyse data of a large trial on node positive breast cancer patients conducted by the German Breast Cancer Study Group and a smaller 'pilot' study on diffuse large B-cell lymphoma, where prognostic factors are derived from microarray expression values. In addition, simulation experiments underline the predictive power of our proposal.

Publication types

  • Comment

MeSH terms

  • Breast Neoplasms / mortality
  • Clinical Trials as Topic
  • Female
  • Germany / epidemiology
  • Humans
  • Lymphoma / mortality
  • Male
  • Models, Statistical
  • Survival Analysis*