Development of a predictive nomogram for perioperative lower extremity deep vein thrombosis in patients with breast cancer and the efficacy of dextran 40 prophylaxis.

Deep vein thrombosis (DVT) is a significant postoperative complication in patients with breast cancer; however, validated risk-prediction models specific to this population remain scarce. This study aimed to develop a nomogram model to predict postoperative DVT and evaluate the preventive efficacy of dextran 40. Clinical data from 594 patients undergoing breast cancer surgery without prophylactic anticoagulation (May-November 2024) were retrospectively analyzed as a derivation cohort. Univariate and multivariate logistic regression analyses were used to identify independent risk factors, and a nomogram prediction model was constructed. Model performance was assessed using receiver operating characteristic curves, decision curve analysis, and calibration curves. A clinical validation cohort was prospectively collected (April-August 2025), where patients were stratified into high- and low-risk groups based on nomogram-derived scores. DVT rates between the two groups were compared to evaluate the model's discriminative ability. The prophylactic effect of dextran 40 was also analyzed. Multivariate regression analysis identified elevated D-dimer levels, age >50 years, body mass index (BMI) ≥28 kg/m