Apply Parametric Shared Frailty Models to Colorectal Cancer Patients

Abstract

Colorectal cancer is a combination of colon and rectal cancer that indicates an abnormal growth of cells in either the colon or rectum and is named according to its original location. After treatment, cancer may return to the primary site of the original tumor or to a different location in the body once or more, which is called recurrent. This paper aimed to model this type of data from 128 colorectal cancer patients collected at Hiwa hospital in Sulaimani considering the gamma shared and inverse Gaussian shared frailty models for analyzing the patient’s survival times with colorectal cancer recurrence and estimate the prognostic factor’s impact on their survival. Comparison of the results of these models with those without a frailty model using Weibull, log-logistic, and lognormal as a baseline distribution. To identify the best model for the data the (AIC) Akaike Information Criterion and (BIC) Bayesian Information Criterion were also used. Results showed that the cancer stage was the only significant factor affecting survival in recurrent events, as well as evidence of existing heterogeneity in colorectal patients. According to (AIC) and (BIC), the Weibull as baseline distribution with shared Gamma frailty model proved the most efficient model for the colorectal recurrent data. In Conclusion, the shared frailty model is better than no frailty when analyzing this type of data.