| Abstract: | We deal with the problem of finding a suitable model to predict survival of patients suffering from glial tumours as a function of several covariates. Estimation is based upon a retrospective study on 192 patients. Data were collected in the Hospital of Bordeaux and are analysed by Commenges and Dartigues1 using a Cox model. In the present paper we use dynamic Bayesian models which allow effects of the covariates to change with time through a stochastic structure. The survival function at one year is also calculated as a function of the covariates with the highest prognostic values and two factors (linear combinations of the covariates) are identified which synthesize information related to the general state of the patient (age, first symptom, etc.) and the characteristics of the tumour (diameter, localization, etc.), respectively. Survival at one year is then calculated as function of the two factors. Results are reported in tabular and graphic forms. |
