Mixture Cure Survival Model with Weibull Distribution for Brain Cancer

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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Publication Details

Journal
The Journal of Administration & Economics
Published
2025-09-01
DOI
https://doi.org/10.31272/jae.i149.1359
Primary Topic
Cancer Genomics and Diagnostics
Type
article
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article

Mixture Cure Survival Model with Weibull Distribution for Brain Cancer

Nejmaddin A. Sulaiman, Kurdistan Ibrahim Mawlood, Awaz Sh. Mohamad
The Journal of Administration & Economics
Cancer Genomics and Diagnostics
article

Mixture Cure Survival Model with Weibull Distribution for Brain Cancer

Nejmaddin A. Sulaiman, Kurdistan Ibrahim Mawlood, Awaz Sh. Mohamad
article en

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.

The Journal of Administration & EconomicsVol. 50(149)
Salahaddin University-Erbil (IQ)
Openalex Percentile: Top 71%
Cancer Genomics and Diagnostics
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Mixture Cure Survival Model with Weibull Distribution for Brain Cancer — Nejmaddin A. Sulaiman, Kurdistan Ibrahim Mawlood, et al. · The Journal of Administration & Economics (2025) | TGRS Research Map | TGRS