Evaluation of Prognosis and Duration of Survival in Breast Cancer Patients Using the Cox PH Model - Dela Meliza; Tessy Octvia Mukhti; Riza Sasmita; Celsy Aprotama; Rahmat Kurniawan (UNP Journal of Statistics and Data Science, 2025)
Breast cancer is the leading cause of cancer-related deaths among women in Indonesia. Late detection and delayed treatment contribute significantly to this high mortality rate, as many patients seek medical care only after reaching advanced stages. Early detection through Breast Self Examination (BSE) and timely intervention can improve survival rates and quality of life. This study aims to evaluate the survival duration and influencing factors for breast cancer patients using clinical and genomic data from the METABRIC dataset, encompassing 1.980 primary breast cancer cases. The study employs survival analysis using Kaplan-Meier curves, Log-rank tests, and Cox proportional hazards regression to analyze the data. Results indicate significant differences in survival rates based on type of surgery and chemotherapy, while age at diagnosis shows no significant effect. The Cox proportional hazards model reveals that patients undergoing mastectomy have a 0.725 lower risk of death compared to those not undergoing the procedure, and patients receiving chemotherapy have a 1.869 higher risk of death. The findings underscore the importance of early and appropriate treatment in improving survival outcomes. This study contributes to the understanding of factors influencing breast cancer survival, aiding in better clinical decision-making and patient management strategies. Keywords: Breast Cancer, Cox Regression, Kaplan-Meier, Survival Analysis, Treatment Factors.