Assessing time-by-covariate interactions in relative survival models using restrictive cubic spline functions.

@article{Bolard2002AssessingTI,
  title={Assessing time-by-covariate interactions in relative survival models using restrictive cubic spline functions.},
  author={Philippe Bolard and Catherine Quantin and Michal Abrahamowicz and Jacques Est{\`e}ve and Roch Giorgi and Harbajan Chadha-Boreham and Christine Binquet and Jean Faivre},
  journal={Journal of cancer epidemiology and prevention},
  year={2002},
  volume={7 3},
  pages={113-22}
}
BACKGROUND The Cox model is widely used in the evaluation of prognostic factors in clinical research. However, in population-based studies, which assess long-term survival of unselected populations, relative-survival models are often considered more appropriate. In both approaches, the validity of proportional hazards hypothesis should be evaluated. METHODS We propose a new method in which restricted cubic spline functions are employed to model time-by-covariate interactions in relative… CONTINUE READING

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