Gaining more flexibility in Cox proportional hazards regression models with cubic spline functions

Comput Methods Programs Biomed. 1997 Nov;54(3):201-8. doi: 10.1016/s0169-2607(97)00043-6.


The Cox proportional hazards model is the most popular model for the analysis of survival data. The use of cubic spline functions allows investigation of non-linear effects of continuous covariates and flexible assessment of time-by-covariate interactions. Two main advantages are provided--no particular functional form has to be specified and standard computer software packages like SAS or BMDP can be used. A SAS macro which implements the method is presented.

MeSH terms

  • Antimetabolites, Antineoplastic / therapeutic use
  • Clinical Trials as Topic
  • Data Interpretation, Statistical
  • Humans
  • Leukemia / drug therapy
  • Mathematical Computing
  • Mercaptopurine / therapeutic use
  • Proportional Hazards Models*
  • Software Design
  • Software*


  • Antimetabolites, Antineoplastic
  • Mercaptopurine