ArticleBMC women's health2024
Assessing the survival time of women with breast cancer in Northwestern Ethiopia: using the Bayesian approach.
Article in BMC women's health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 4 of them syntheses that pooled it.
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Who cites it
7 citing papers in PubMed, 4 syntheses or guidelines pooled it, 6 citations in OpenAlex.
- 5-year survival rate and determinants of decreased survival among patients with breast cancer in Africa: a systematic review and meta-analysis.BMJ global health · 2026Pooled it
- Breast cancer survival rates and determinants in Ethiopia: a systematic review and meta-analysis of longitudinal studies.BMC cancer · 2025Pooled it
- Breast cancer survival in Ethiopia: a systematic review and meta-analysis of rates and predictors.Cancer causes & control : CCC · 2025Pooled it
- Survival status and predictors of mortality among patients with breast cancer in Ethiopia: a systematic review and meta-analysis.BMJ open · 2025Pooled it
- Bayesian Model Prediction for Breast Cancer Survival: A Retrospective Analysis.European journal of breast health · 2025Article
- Predictors of survival rates among breast cancer patients in Ethiopia: a systematic review and meta-analysis 2024.Archives of public health = Archives belges de sante publique · 2025Article
- Correction to: Assessing the survival time of women with breast cancer in Northwestern Ethiopia: using the Bayesian approach.BMC women's health · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite the significant weight of difficulty, Ethiopia's survival rate and mortality predictors have not yet been identified. Finding out what influences outpatient breast cancer patients' survival time was the major goal of this study.
methodsA retrospective study was conducted on outpatients with breast cancer. In order to accomplish the goal, 382 outpatients with breast cancer were included in the study using information obtained from the medical records of patients registered at the University of Gondar referral hospital in Gondar, Ethiopia, between May 15, 2016, and May 15, 2020. In order to compare survival functions, Kaplan-Meier plots and the log-rank test were used. The Cox-PH model and Bayesian parametric survival models were then used to examine the survival time of breast cancer outpatients. The use of integrated layered Laplace approximation techniques has been made.
resultsThe study included 382 outpatients with breast cancer in total, and 148 (38.7%) patients died. 42 months was the estimated median patient survival time. The Bayesian Weibull accelerated failure time model was determined to be suitable using model selection criteria. Stage, grade 2, 3, and 4, co-morbid, histological type, FIGO stage, chemotherapy, metastatic number 1, 2, and >=3, and tumour size all have a sizable impact on the survival time of outpatients with breast cancer, according to the results of this model. The breast cancer outpatient survival time was correctly predicted by the Bayesian Weibull accelerated failure time model.
conclusionsCompared to high- and middle-income countries, the overall survival rate was lower. Notable variables influencing the length of survival following a breast cancer diagnosis were weight loss, invasive medullar histology, comorbid disease, a large tumour size, an increase in metastases, an increase in the International Federation of Gynaecologists and Obstetricians stage, an increase in grade, lymphatic vascular space invasion, positive regional nodes, and late stages of cancer. The authors advise that it is preferable to increase the number of early screening programmes and treatment centres for breast cancer and to work with the public media to raise knowledge of the disease's prevention, screening, and treatment choices.
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