Competing Risk Modelling using Cumulative Incidence Function: Application to Recurrent Bladder Cancer Data

In this study, the effects of some clinical variables on the survival times of patients with bladder cancer were examined. The effects of these variables on sub-distribution of the failure types were determined using the proportional sub-distribution hazards regression model described in Fine and Gray (1999). Published dataset on 294 bladder cancer patients with four clinical outcomes were analyzed using Cumulative Incidence Function approach. The four outcomes included 184 (64%) patients that experienced recurrence of bladder cancer after receiving chemotherapy treatments. Two patients died of bladder cancer while 27 patients died of other causes and the remaining 76 patients did not experienced any of these three outcomes, and as a result, were considered censored. Among the covariates considered, only the patients’ initial number of tumors and initial size of tumor were incorporated into our analysis due to high proportion of missing observations in others. Results from this work showed that, patients with tumour recurrence have highest risk of dying than those from other causes. Further results showed that, the number of tumor was positively associated with the recurrence of cancer of the bladder. However, the size of the tumor did not demonstrate a significant effect on the patients’ survival time. It can therefore, be concluded that patients with tumor recurrence have low probability of survival from bladder cancer than patients that experienced other events. Above all, number, but not size of tumor could adversely affect the survival time of bladder cancer patients, especially those with tumor recurrence after bladder cancer treatment