Development and validation of a predictive nomogram for postoperative upper limb lymphedema in breast cancer patients: a retrospective cohort study.

Upper limb lymphedema is a common and debilitating complication following breast cancer surgery. Identifying patients at high risk for developing lymphedema is crucial for early intervention and improved outcomes. This study aimed to develop and validate a predictive nomogram for estimating the risk of postoperative upper limb lymphedema in breast cancer patients. A retrospective cohort of 724 breast cancer patients who underwent radical surgery was analyzed. Of these, 211 (29.1%) developed postoperative upper limb lymphedema. Baseline characteristics, including demographic, clinical, and treatment-related factors, were compared between patients with and without lymphedema. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors. A nomogram was then constructed using the significant predictors. The performance of the nomogram was evaluated through the receiver operating characteristic (ROC) curve and calibration curve analysis. In the multivariate analysis, age, body mass index (BMI), education level, hypertension, TNM stage, menopausal status, marital status, tumor diameter, number of lymph nodes dissected, postoperative radiotherapy, postoperative complications, and functional exercise were identified as independent predictors of lymphedema. The nomogram demonstrated excellent discrimination, with an area under the ROC curve of 0.944 (95% CI 0.926-0.962). The calibration curve showed good agreement between predicted and observed probabilities, indicating the model's reliability and accuracy. This study successfully developed a predictive nomogram for estimating the risk of postoperative upper limb lymphedema in breast cancer patients. The nomogram demonstrated strong predictive performance and calibration, making it a valuable tool for clinicians to identify high-risk patients and guide early interventions.