Department of Statistics, College of Computing and Informatics, Haramaya University, Dire Dhawa, Ethiopia.
Sci Rep. 2024 Oct 15;14(1):24141. doi: 10.1038/s41598-024-73451-3.
Breast cancer is the most common cause of cancer death and is a frequently diagnosed cancer among women worldwide. It is becoming a challenging health condition in Ethiopia with a high rate of morbidity and mortality. The main aim of this study was to model the time to death in breast cancer patients at Hiwot Fana Specialized University Hospital. A retrospective cohort study was carried out from April 1st, 2020, to April 1st, 2023, and 296 women were included in the study. We used nonparametric methods and Bayesian accelerated failure time models (with Laplace approximation) to identify risk factors and choose a model fitting breast cancer patient data. Model comparison was performed using the marginal likelihood, deviance information criterion and Watanabe Akaike information criterion. From the total of 296 patients in the study, 56 (18.9%) died. The estimated median survival time was 33 months. The log-rank test showed that age group, stage, alcohol consumption, smoking habit, and comorbidity were potential risk factors associated with the time to death in breast cancer patients at the 5% level of significance. The Bayesian Weibull accelerated failure time model was found to be the best fitted model for predicting the survival time of patients with minimum DIC (520.39) and WAIC (521.59) values. The final Bayesian Weibull AFT model with the integrated nested Laplace approximation estimation technique revealed that age group, stage, alcohol consumption, smoking habit, and comorbidity were significantly associated with the time to death in breast cancer patients. Individuals older than 65 years, with stage IV disease, drinking alcohol, smoking cigarettes and having comorbidities had shortened survival times in patients with breast cancer. Hence, Hiwot Fana Specialized University Hospital and related bodies should work on awareness creation to reduce smoking habits and alcohol use as well as give due attention to elderly and stage IV breast cancer patients during intervention.
乳腺癌是癌症死亡的最常见原因，也是全球女性中经常诊断出的癌症。在埃塞俄比亚，乳腺癌的发病率和死亡率都很高，这使其成为一个具有挑战性的健康问题。本研究的主要目的是建立 Hiwot Fana 专科医院乳腺癌患者的死亡时间模型。这是一项回顾性队列研究，从 2020 年 4 月 1 日至 2023 年 4 月 1 日进行，共纳入 296 名女性。我们使用非参数方法和贝叶斯加速失效时间模型（采用拉普拉斯近似）来识别风险因素，并选择适合乳腺癌患者数据的模型。使用边缘似然、偏差信息准则和 Watanabe-Akaike 信息准则来进行模型比较。在研究的 296 名患者中，有 56 名（18.9%）死亡。估计的中位生存时间为 33 个月。对数秩检验显示，年龄组、分期、饮酒、吸烟习惯和合并症是与乳腺癌患者死亡时间相关的潜在风险因素，在 5%的水平上具有统计学意义。贝叶斯 Weibull 加速失效时间模型被发现是预测患者生存时间的最佳拟合模型，其 DIC（520.39）和 WAIC（521.59）值最小。最终的贝叶斯 Weibull AFT 模型与集成嵌套 Laplace 近似估计技术相结合，揭示了年龄组、分期、饮酒、吸烟习惯和合并症与乳腺癌患者的死亡时间显著相关。年龄大于 65 岁、患有 IV 期疾病、饮酒、吸烟和合并症的个体，乳腺癌患者的生存时间缩短。因此，Hiwot Fana 专科医院及相关机构应致力于开展宣传活动，减少吸烟和饮酒习惯，并在干预过程中给予老年和 IV 期乳腺癌患者应有的关注。
