Application of Logistics Regression on the Risk Factor of Breast Cancer ( a Case Study of St Gerard's Catholic Hospital Kakuri, Kaduna)

The project work “Application of logistic regression on the risk factor of breast cancer”, a case study of St Gerard’s Catholic Hospital Kakuri, Kaduna. This study aimed to quantify the association between various risk factors and breast cancer and to develop a predictive model estimating an individual's risk of developing the disease. Logistic regression analysis was employed to assess five risk factors: Age, Family History, Hormonal Factor, Reproductive History, and Obesity. Although the model did not achieve overall statistical significance (χ2 = 7.111, df = 5, p = .213), it showed a reasonably good fit (-2 Log likelihood = 26.540) and moderate explanatory power (Cox & Snell R Square = 0.248, Nagelkerke R Square = 0.335). The classification table indicated a 76.0% correct classification rate, with higher accuracy in predicting breast cancer cases (86.7%) compared to non-cancer cases (60.0%). Individual predictors varied in significance, with Age and Reproductive History showing borderline significance. The study suggests that while the model is moderately effective, further refinement is needed. This includes adding variables like genetic markers and lifestyle factors, validating with independent datasets, and integrating with clinical tools. Enhancing educational and preventive strategies based on these insights can improve breast cancer prevention and early detection efforts. We therefore recommend that government should provide functional breast cancer facilities in different parts of Nigeria and also subsidize then breast cancer treatment, this will enable patient to report to the hospital for orthodox treatment.