Mixture Cure Survival Model with Weibull Distribution for Brain Cancer
DOI:
https://doi.org/10.31272/jae.i149.1359Keywords:
Weibull Distribution, Mixture Cure Survival Model, Akaike Information Criterion.Abstract
Brain cancers include primary brain tumours, and a brain tumour refers to an abnormal growth of cells in the brain that can be either benign or malignant. Benign tumours lack cancer cells, and once removed, they seldom reappear. However, benign brain tumours can lead to significant health complications and may eventually become malignant. Malignant brain tumours are cancerous, grow aggressively, invade nearby tissue, and are often life-threatening. In recent years, the treatment of many cancers, particularly brain cancer, has advanced significantly. Consequently, the number of patients who fail to achieve favorable outcomes, including death, has decreased. In the statistical evaluation of this type of disease, recovery models are applied instead of traditional survival models. This study analyzed 215 cases of brain cancer from Rzgari Hospital in Erbil city during the period from 2020 to 2024. Among these cases, 99 patients (31.4%) were classified as cured. The data was modelled using the mixture cure approach with several statistical distributions, incorporating the cured fraction in this population and the significance of the Maller-Zhou test. Based on the research outcomes and a comparison of the Akaike Information Criterion and Bayesian Information Criterion, the cure model employing the Weibull distribution for survival time was deemed the most suitable.
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