A relative survival regression model using B-spline functions to model non-proportional hazards.
Relative survival, a method for assessing prognostic factors for disease-specific mortality in unselected populations, is frequently used in population-based studies. However, most relative survival models assume that the effects of covariates on disease-specific mortality conform with the proportional hazards hypothesis, which may not hold in some long-term studies. To accommodate variation over time of a predictor's effect on disease-specific mortality, we developed a new relative survival regression model using B-splines to model the hazard ratio as a flexible function of time, without having to specify a particular functional form. Our method also allows for testing the hypotheses of hazards proportionality and no association on disease-specific hazard. Accuracy of estimation and inference were evaluated in simulations. The method is illustrated by an analysis of a population-based study of colon cancer.
Giorgi
Roch
R
LERTIM, Faculté de Médecine, Université de la Méditerranée, 27 Bd Jean Moulin 13385 Marseille Cedex, France.
Abrahamowicz
Michal
M
Quantin
Catherine
C
Bolard
Philippe
P
Esteve
Jacques
J
Gouvernet
Joanny
J
Faivre
Jean
J
D000368:Aged; D003110:Colonic Neoplasms / Q000401:mortality*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D016016:Proportional Hazards Models; D012044:Regression Analysis; D016019:Survival Analysis