Estimating unknown heterogeneity in head and neck cancer survival: a parametric shared frailty approach

The term frailty was introduced by Vaupel et al. to indicate that dierentindividuals are at risks even though on the surface they may appear tobe quite similar with respect to the measurable attributes such as age, sex, habits etc. The term frailty can be utilized to represent an unobservablerandom eect shared by subjects with similar risks in the analysis of timeto event data and/or mortality rates. In this article, we make use of theparametric shared frailty models to a real life data for identifying the distributionalform of baseline hazard function. The gamma shared frailty, withdisease stages as clusters, with log-logistic baseline hazard model came outto be the best choice for modeling survival data of head and neck cancerpatients treated with radiotherapy. The suitability of the best-chosen modelis justied considering two signicant covariates, namely age of the patientsand habit of their alcohol consumption. We obtain the estimates of frailty (or unknown heterogeneity) for ve stages of disease taken as clusters forGamma-log-logistic shared frailty model.