Investigating Factors Affecting the Survival of Breast Cancer Patients Using the Mixture Cure Model

Abstract

Background and Objective: Breast cancer is the second leading cause of death in women. Prognostic factors for cancer using appropriate statistical models with data structure not only help in choosing a more appropriate treatment method in the short term but can also play a significant role in identifying high-risk patients in the long term. This study aimed to determine the factors associated with survival in breast cancer patients using a Mixture Cure model. Materials and Methods: This retrospective cohort study was conducted from 2011 to 2021. A total of 767 breast cancer patients were referred to the Mahdieh Medical Diagnostic Center in Hamadan, Iran. Clinical and demographic information was collected by contacting the individuals through telephone calls. A Mixture Cure model was used to analyze the collected data. Data analysis was performed using smcure in R.4.0.5 software. Results: Of the 767 breast cancer patients followed up for 10 years, 58(6.7%) individuals died. The mean (standard deviation) age at diagnosis was 49.23(10.85) years. In univariate analysis, clinical and demographic features, including age, first treatment, marital status, disease recurrence, type of pathology, invasion of lymphatic vessels, and in multivariate analysis, first treatment and disease recurrence had a significant association with patient survival (P<0.05). Conclusion: According to the findings of this study, first treatment and disease recurrence were identified as factors associated with the survival of breast cancer patients. The impact of first treatment and disease recurrence on survival highlights the importance of early diagnosis, appropriate diagnostic and therapeutic services, and improving the quality of life of patients. On the other hand, the relatively high survival rate in patients referred to the Mahdieh Medical Center may indicate the importance of creating such centers for various diseases.