Abstract:
Breast cancer is a widespread and critical public health issue, with survival outcomes
influenced by various factors. It originates from uncontrolled cell growth in the breast tissue
and can present as both invasive and non-invasive forms. This study aimed to investigate the
factors affecting the survival time of breast cancer patients treated at Hawassa Referral
Hospital, Ethiopia. The study utilized a retrospective cohort design and employed survival
analysis through the Accelerated Failure Time (AFT) model. To achieve the study’s
objective, sub-models such as exponential, Weibull, log-logistic, and lognormal were
applied. The study sample included 384 adult women with breast cancer, selected through
simple random sampling. This finding identified key factors influencing survival time of
breast cancer patients using Accelerated Failure Time Models. Significant predictors
included age, marital status, residence, surgery, radiotherapy, lymph node involvement,
tumor differentiation, and baseline tumor size. Younger age, urban residence, and welldifferentiated tumors were linked to longer survival, while lymph node involvement,
metastatic disease, and larger tumors reduced survival time. Socio-demographic factors such
as being married and living in urban areas positively impacted survival, while rural residence
and unmarried status were associated with poorer outcomes. Clinical interventions, especially
surgery and radiotherapy, notably improved survival, while chemotherapy showed no
significant effect. The Lognormal model was found to be the best fit, providing reliable
estimates of survival predictors. Effective breast cancer management should focus on early
diagnosis, improving access to surgery and radiotherapy, and addressing socio-demographic
disparities. Future research should investigate the time-dependent effects of chemotherapy
and refine predictive models to improve patient care.
