Application of the Joint Frailty Copula Model for Analyzing Time to Relapse and Time to Death of Women with Cervical Cancer.

Abstract

Worldwide, there were 12.7 million new cervical cancer cases, of which 5.6 million took place in industrialized nations and 7.1 million in underdeveloped nations. In eastern, western, middle, and southern Africa, it is the main cancer-related cause of death in female patients. In Ethiopia, cancer was responsible for roughly 5.8% of all fatalities. This study makes use of sophisticated statistical models that take into account population heterogeneity in terms of frailty and dependence between two endpoints in terms of copulas. Based on hospital registry data, this retrospective study intends to examine the time to relapse and time to death of cervical cancer. This study analyzes 907 cervical cancer-positive women from various parts of Ethiopia. The copula model was used to link time to relapse and time to death of women with cervical cancer. Shared frailty model was used to incorporate unexplained heterogeneity for women with cervical cancer patients. Of the 907 cervical cancer patients, 275 (30.32%) experienced a relapse, 353 (38.92%) died, and 554 (61.08%) were censored. Age, smoking status, family planning, HIV status, family history, abortion, and stage are the most reliable predictors of both time to relapse and time to death of cervical cancer patients. The estimate of the copula parameter (θ = 1.476, 95% CI: 1.082, 1.870) shows moderate amount of dependence between time to relapse and time to death (Kendall's rank correlation (τ) = 0.425). The estimate of the variability (heterogeneity) parameter in the population of clusters (region) is η = 0.495, 95% CI: 0.101, 0.889. Age, smoking status, family planning, HIV status, family history, abortion, and more advanced stage significantly increase the risk of relapse and death of female cervical patients. There was a significant association between the time to relapse and the time to die for women with cervical cancer. There was a significant heterogeneity effect in the Tikur Anbessa Specialized Hospital.