Competing Risk Modeling Using Cumulative Incidence Function: Application to Recurrent Bladder Cancer data
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Date
2018
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FUOYE Journal of Engineering and Technology, Federal University of Science and Technology, Oye-Ekiti, Nigeria
Abstract
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 the 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 experience any of these three outcomes, and as a result, were considered censored. Among the covariates
considered, only the patients’ initial number of tumours and initial size of tumour 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 the highest risk of dying than those from other causes. Further results showed that the number of tumours was positively associated with the recurrence of cancer of the bladder . However, the size of the tumour did not demonstrate a significant effect on the patients’ survival time. It can therefore, be concluded that patients with tumour recurrence have a low probability of survival from bladder cancer than patients that experienced other events. Above all, number, but not size of tumour could adversely affect the survival time of bladder cancer patients, especially those with tumour recurrence after bladder cancer treatment.
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Keywords
Bladder Cancer, Competing risks, Cumulative Incidence Function, Survival time, Transurethral resection