Tree-structured prediction for censored survival data and the Cox model

J Clin Epidemiol. 1995 May;48(5):675-89. doi: 10.1016/0895-4356(94)00164-l.

Abstract

Prediction trees for the analysis of survival data are discussed. It is shown that trees are useful not only in summarizing the prognostic information contained in a set of covariates (prognostic classification), but also in detecting and displaying treatment-covariates interactions (subgroup analysis). The RECPAM approach to tree-growing is outlined; prognostic classification and subgroup analysis are then formulated within the RECPAM framework and on the basis of the Cox proportional hazards models with a priori strata. Two examples of data analysis are presented. The issue of cross-validation is discussed in relation to computationally cheaper model selection criteria.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Decision Trees*
  • Humans
  • Lung Neoplasms / classification
  • Lung Neoplasms / mortality
  • Middle Aged
  • Models, Statistical
  • Prognosis
  • Proportional Hazards Models
  • Software
  • Survival Analysis*