埃塞俄比亚提格雷Ayder综合专科医院乳腺癌患者至死亡时间的生存分析

Bsrat Tesfay, T. Getinet, E. A. Derso
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引用次数: 3

摘要

乳腺癌是世界范围内最主要的死亡原因,在所有类型癌症的死亡原因中排名第五;这是发展中国家和发达国家妇女癌症死亡的最常见原因。乳腺癌在埃塞俄比亚妇女最常见的癌症中排名第一。尽管发病率高,但埃塞俄比亚乳腺癌患者的死亡率和生存状况尚未确定。本研究的目的是确定2015年9月至2018年12月在艾德尔综合专科医院接受抗癌治疗的乳腺癌患者死亡时间的影响因素。方法:以医院为基础,对乳腺癌患者进行回顾性队列研究。采用Kaplan-Meier生存曲线和log-rank检验来检验预测变量间的生存差异。采用5%显著性水平的Cox回归来确定每个自变量对乳腺癌患者死亡时间的净影响。结果:Cox比例模型显示,年龄、文化程度、居住地、基线肿瘤大小及病理类型(LIC)对乳腺癌死亡风险有显著影响(p < 0.05),乳腺癌患者中位生存时间为34.50个月。结论:年龄、文化程度、居住地、基线肿瘤大小及病理类型(LIC)是影响乳腺癌患者住院至死亡时间的因素。建议根据这些危险因素进行干预。
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Survival analysis of Time to Death of Breast Cancer Patients: in case of Ayder Comprehensive Specialized Hospital Tigray, Ethiopia.
Abstract Breast cancer is a foremost cause of death worldwide, ranks fifth among causes of death from all types of cancers; this is the most common cause of cancer death in women among both developing and developed countries. Breast cancer ranks first among the most frequent cancers in women of Ethiopia. In spite of the high incidence, mortality rate, and survival status among breast cancer patients was not determined in Ethiopia. The purpose of this study was to identify factors affecting the time to death among breast cancer patients attending anti-cancer treatment from September 2015 till December 2018 at Ayder Comprehensive Specialized Hospital. Methods: Hospital-based retrospective cohort study was conducted among breast cancer patients. Kaplan-Meier survival curve together with log-rank test was deployed to test for variations in the survival among predictor variables. Cox regression was used at a 5% level of significance to determine the net effect of each independent variable on the time to death of breast cancer clients. Results: From the Cox proportional model, patients with age, educational status, residence, Baseline Tumor size &Pathology type (LIC) were found to be a statistically significant effect (p < 0.05) on the risk of mortality due to breast cancer and the median survival time of breast cancer patient was 34.50 months. Conclusion: the finding of this study showed that age, educational status, residence, Baseline Tumor size &Pathology type (LIC) were influential affecting time to death of breast cancer patient at the Hospital. It is recommended to make interventions based on these risk factors.
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