title: A relative survival regression model using B-spline functions to model non-proportional hazards.
abstract: 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.
authors.affiliation: LERTIM, Faculté de Médecine, Université de la Méditerranée, 27 Bd Jean Moulin 13385 Marseille Cedex, France.
authors.forename: Roch
authors.initials: R
authors.lastname: Giorgi
authors.forename: Michal
authors.initials: M
authors.lastname: Abrahamowicz
authors.forename: Catherine
authors.initials: C
authors.lastname: Quantin
authors.forename: Philippe
authors.initials: P
authors.lastname: Bolard
authors.forename: Jacques
authors.initials: J
authors.lastname: Esteve
authors.forename: Joanny
authors.initials: J
authors.lastname: Gouvernet
authors.forename: Jean
authors.initials: J
authors.lastname: Faivre
mesh_terms: 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