Development and validation of a risk prediction model for postoperative frailty in breast cancer patients

Abstract

Background Patients who have undergone breast cancer (BC) surgery are a high-risk population for frailty. This study aims to analyze risk factors for frailty in these patients, develop a risk prediction model, and validate its predictive performance, thereby providing a reference for frailty prevention in postoperative breast cancer patients. Methods A total of 286 BC patients who underwent surgical treatment at the Department of Breast Surgery, the First Affiliated Hospital of University of Science and Technology of China (USTC), between October 2024 and March 2025, participated in a cross-sectional study and were surveyed using a general information questionnaire, the Chinese version of the Tilburg Frailty Indicator (TFI), and the Pittsburgh Sleep Quality Index (PSQI). We used logistic regression to analyze factors influencing postoperative frailty in BC patients and constructed a risk prediction nomogram. We evaluated the model’s predictive performance using receiver operating characteristic (ROC) curves, calibration curves, the Hosmer-Lemeshow test, and decision curve analysis (DCA), with internal validation conducted via 10-fold cross-validation. Results The incidence of postoperative frailty among BC patients was 29.37%. Logistic regression analysis identified the following factors as significant influences on frailty in this population (P < 0.05): a history of diabetes, poor sleep quality, having children as the primary caregivers, urban employee basic medical insurance, higher cholesterol levels, higher body mass index (BMI), higher exercise frequency, and undergoing breast conserving surgery. The results of the Hosmer–Lemeshow test showed that χ2 = 4.436, P = 0.816. The model showed an area under the ROC curve was 0.813 after internal validation. Conclusion The created prediction model provided a precise, individualized evaluation of postoperative frailty risk in BC patients. It can be used to identify individuals at high risk of postoperative frailty in BC patients and to guide healthcare professionals in promptly implementing targeted interventions.