Prognostic Model and Influencing Factors for Breast Cancer Patients

Abstract

Breast cancer is a common disease that affects women's life and health. Survival analysis of breast cancer patients can help doctors and patients understand the prognosis of patients and provide guidance for clinical treatment. In this study, experiments were conducted based on SEER breast cancer patient data, and feature selection was performed first, followed by the construction of prognostic models using four survival analysis methods. the C-Index, BS, and IBS indexes of the RSF model were 0.8535, 0.0853, and 0.0512, respectively, which had the best predictive effect in the prognostic model for breast cancer patients. Based on the SHAP method to analyze the important factors affecting the prognosis of breast cancer patients, the results showed that tumor stage, TNM stage, grade and age have a great impact on the prognosis of breast cancer patients.