Modelling time-dependent hazard ratios in relative survival: application to colon cancer

The Cox model is widely used in the evaluation of prognostic factors in clinical research. In population-based studies, however, which assess long-term survival of unselected populations, relative survival models are often considered more appropriate. In both approaches, the validity of proportional hazard hypothesis should be evaluated. To explore the validity of the proportional hazard assumption in a population-based study of colon cancer, to propose non-proportional hazard relative survival models and to evaluate their utility. The use of a piecewise proportional hazard relative survival model in colon cancer has shown that the effects of most clinical prognostic factors such as age, period of diagnosis and stage are non-proportional. The non-proportional hazard relative survival models developed in this article have been found to be efficient tools for better understanding the time-dependent aspect of prognostic factors.