SAGE Open Medicine (Jan 2022)

Treatment outcomes and its associated factors among breast cancer patients at Kitui Referral Hospital

  • Mwendwa Dickson Wambua,
  • Amsalu Degu,
  • Gobezie T Tegegne

DOI
https://doi.org/10.1177/20503121211067857
Journal volume & issue
Vol. 10

Abstract

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Objectives: Despite breast cancer treatment outcomes being relatively poor or heterogeneous among breast cancer patients, there was a paucity of data in the African settings, especially in Kenya. Hence, this study aimed to determine treatment outcomes among breast cancer patients at Kitui Referral Hospital. Methods: A hospital-based retrospective cohort study design was conducted among adult patients with breast cancer. All eligible breast cancer patients undergoing treatment from January 2015 to June 2020 in the study setting were included. Hence, a total of 116 breast cancer patients’ medical records were involved in the study. Patients’ medical records were retrospectively reviewed using a predesigned data abstraction tool. The data were entered, cleaned, and analyzed using SPSS (Statistical Package for Social Sciences) version 26 software. Descriptive analysis—such as percentage, frequency, mean, and figures—was used to present the data. Kaplan–Meier survival analysis was used to estimate the mean survival estimate across different variables. A Cox regression analysis was employed to determine factors associated with mortality. Results: The study showed that the overall survival and mortality rate was 62.9% (73) and 37.1% (43), respectively. The regression analysis showed that patients who had an advanced stage of disease had a 3.82 times risk of dying (crude hazard ratio= 3.82, 95% confidence interval = 1.5–9.8) than an early stage of the disease. Besides, patients with distant metastasis had 4.4 times more hazards of dying than (crude hazard ratio = 4.4, 95% confidence interval = 2.1–9.4) their counterparts. Conclusion: The treatment outcome of breast cancer patients was poor, and its overall mortality among breast cancer patients was higher in the study setting. In the multivariate Cox regression analysis, the tumor size was the only statistically significant predictor of mortality among breast cancer patients. Stakeholders at each stage should, therefore, prepare a relevant strategy to improve treatment outcomes.