Investigating the Risk Factors Affecting the Survival Rate of Breast Cancer Patients Using Cured Model Based on Defective Distribution

Abstract

Background: The analysis methods for breast cancer (BC) data have also advanced alongside medical advancements in the treatment of the disease. Objectives: This study tried to investigate the factors affecting the survival rate of BC patients using the cured model based on Kumaraswamy's defective distribution. Methods: A retrospective study collected data on 2 574 BC patients between September 2013 and September 2020, including demographic, clinicopathological, and biological characteristics. The best model for predicting cure was chosen based on AIC. Results: The selected cure model revealed that age (P = 0.046), tumor histologic grade (P = 0.0.38), tumor size (P = 0.0.41), HER2 status (P = 0.001), KI67 levels (P = 0.027), P53 status (P = 0.029), and hormone therapy (P = 0.039) were significant variables. The estimated cured rate of this data was 0.82. Conclusions: Considering that the advanced cured model has the highest accuracy in identifying the factors affecting the survival rate of BC patients and more risk factors have become significant in this model, it is recommended to pay special attention to patients aged over 60 with poorly differentiated historical grade, T3 tumor size, HER2 positive status, KI67 levels below 20%, negative P53 status, and no hormone therapy received in the process of disease prognosis.