Risk Factors Associated with Mortality of Breast Cancer Patients After Surgery: The Case of Zambia

Justin Mulope; Banda Amos

doi:10.53974/unza.jabs.7.3.1199

Justin Mulope UNZA postgraduate student
Banda Amos

DOI: https://doi.org/10.53974/unza.jabs.7.3.1199

Keywords: Breast cancer, mortality, logistic regression, prognostic, retrospective study

Abstract

Breast cancer (BC) has become a public health problem world-wide due to its high mortality rate among women in both developed and developing countries. The association between BC mortality and patients care and personal factors have been widely studied in developed countries. However, in Zambia, scarce data is available regarding BC mortality and its prognostic factors. We aimed at identifying the factors affecting survival rates and to estimate a 5-year mortality of BC patients after surgery. Retrospective data were collected from medical records of patients from the Cancer Disease Hospital (CDH) in Lusaka, Zambia, that encompassed 233 women who had undergone BC surgery between 2013 and 2018, who were followed-up to the end of 2019. Prognostic factors of BC mortality after surgery using Logistic regression model were determined. The most commonly used statistic of comparison was the odds ratio (OR). Further, 5-year mortality rates for various age groups were estimated using the fitted model. Age at surgery, marital status, HIV status, BMI, BC stage, histologic grade, PR status were significantly associated with mortality of BC patients after surgery. The odds of death increased with the degree of severity across the levels of the factors such as tumor size, lymph node status, BC stage and histologic grade. Also, the odds ratio for mortality increased with an increase in age of patients. Additionally, the odds of death were higher for HIV positive and the unmarried patients compared to the HIV negative and married ones. Further, the odds of death for obese or overweight patients were more than twice of those classified as not obese. Furthermore, the 5-year mortality of different age groups using multiple logistic regression stood at 75.4% for the younger group (≤ 35 years) and 99% for the older group (50 <= age).

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