{"title":"Survival analysis of Time to Death of Breast Cancer Patients: in case of Ayder Comprehensive Specialized Hospital Tigray, Ethiopia.","authors":"Bsrat Tesfay, T. Getinet, E. A. Derso","doi":"10.1080/2331205X.2021.1908648","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":10470,"journal":{"name":"Cogent Medicine","volume":"30 1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cogent Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2331205X.2021.1908648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
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.