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外文期刊>Asian Pacific Journal of Cancer Prevention
>Factors Affecting Long-Survival of Patients with Breast Cancer by Non-Mixture and Mixture Cure Models Using the Weibull, Log-logistic and Dagum Distributions: A Bayesian Approach
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Factors Affecting Long-Survival of Patients with Breast Cancer by Non-Mixture and Mixture Cure Models Using the Weibull, Log-logistic and Dagum Distributions: A Bayesian Approach
Background: Breast cancer is a top biomedical research priority, and it is a major health problem. Therefore, the present study aimed to determine the prognostic factors of breast cancer survival using cure models. Methods: In this retrospective cohort analytic study, data of 140 breast cancer patients were collected from Ali Ibn Abi Taleb hospital, Rafsanjan, Southeastern Iran. Since in this study, a part of the population had long-term survival, cure models were used and evaluated using DIC index. The data were analyzed using Openbugs Software. Results: In this study, of 140 breast cancer patients, 23 (16.4%) cases died of breast cancer. Based on the findings, the Bayesian nonmixture cure model, with type I Dagum distribution, was the best fitted model. The variables of BMI, number of children, number of natural deliveries, tumor size, metastasis, consumption of canned food, tobacco use, and breastfeeding affected patients’ survival based on type I Dagum distribution. Conclusion: The results of the present study demonstrated that the Bayesian nonmixture cure model, with type I Dagum distribution, can be a good model to determine factors affecting the survival of patients when there is the possibility of a fraction of cure. In this study, it was found that adapting a healthy lifestyle (eg, avoiding canned foods and smoking) can improve the survival of breast cancer patients.
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机译：背景：乳腺癌是最大的生物医学研究优先权，这是一个重大的健康问题。因此，本研究旨在使用固化模型确定乳腺癌存活的预后因素。方法：在此回顾性队列分析研究中，从伊朗东南部的rafsanjan rafsanjan的Ali Ibn Abi Taleb医院收集了140例乳腺癌患者的数据。自本研究以来，一部分人口具有长期存活，使用并使用DIC指数进行治愈模型。使用OpenBugs软件分析数据。结果：在本研究中，140例乳腺癌患者，23例（16.4％）病例死于乳腺癌。基于调查结果，贝叶斯非增生固化模型，具有I型Dagum分布，是最适合的拟合模型。 BMI的变量，儿童数量，自然递送数，肿瘤大小，转移，罐头食品，烟草使用的消耗，以及母乳喂养，以及基于I型Dagum分布的患者的生存。结论：本研究结果表明，贝叶斯非增生固化模型，具有I型Dagum分布，可以是确定影响患者存活的因素的良好模型，当时有可能是一种治疗方法。在这项研究中，发现适应健康的生活方式（例如，避免罐头食品和吸烟）可以改善乳腺癌患者的存活。
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