Survival Status and Predictors of Mortality Among Women With Breast Cancer in Southern Ethiopia: A Retrospective Cohort Study.

Authors

Bitsiet Desta, Tsion Zebdiwos Chema, Sophonias Sisay, Mulualeme Nigusie, Bargude Balta

Published in

Cancer reports (Hoboken, N.J.). Volume 9. Issue 10. Pages e70722.

Abstract

Breast cancer continues to be a leading cause of morbidity and mortality worldwide, with an especially severe impact in low-resource settings. In such contexts, delayed diagnosis, limited diagnostic capacity, and inadequate access to treatment contribute to poor survival outcomes. However, little is known about how these factors influence survival patterns specifically in southern Ethiopia, highlighting the need for locally generated data to guide interventions.
A hospital-based retrospective cohort study was conducted among 507 breast cancer patients attending selected hospitals in southern Ethiopia. Data were collected by two trained BSc nurses using an Open Data Kit (ODK) tool. Descriptive statistics were presented using tables and graphs, while bivariable, and multivariable Cox regression models were used to identify independent predictors of survival.
A total of 507 medical records were reviewed, of which 492 eligible women were included in the final analysis. The overall survival rates were 54.5% at 2 years and 23.9% at 3 years. In multivariable Cox regression analysis, advanced stage had a higher hazard of death (AHR = 1.73, 95% CI: 1.19-2.51). Poor NPI was also associated with increased mortality (AHR = 2.30, 95% CI: 1.50-5.10). Patients with an NLR < 3 had a lower hazard of death (AHR = 0.68, 95% CI: 0.47-0.97), as did those who received hormonal therapy (AHR = 0.64, 95% CI: 0.44-0.92).
Advanced-stage disease and poorer NPI were associated with a higher hazard of death from any cause, while lower NLR and hormonal therapy were associated with better overall survival. Strengthening early diagnosis and ensuring appropriate treatment may improve overall survival among women with breast cancer in resource-constrained settings.

PMID:
42888498
Bibliographic data and abstract were imported from PubMed on 17 Oct 2026.

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