A novel nomogram and risk classification system for predicting lymph node metastasis of breast mucinous carcinoma: A SEER‐based study

BACKGROUND: Mucinous breast cancer (MBC) is a rare disease, and patients with lymph node metastasis (LNM) have a poor prognosis. We aimed to explore the predictive factors of LNM and to construct a nomogram for predicting the risk of LNM and to identify the suitable axillary surgery for patients with diverse risks. PATIENTS AND METHODS: Data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Chi‐square and rank‐sum tests were used to analyze the differences between groups. Survival analysis was performed with Kaplan–Meier curves and log‐rank tests. Independent factor identification and nomogram construction were performed with logistic regression analysis. The nomogram was qualified with a discrimination and calibration plot. Propensity score matching was performed to balance the disparities between groups. RESULTS: Patients with metastatic lymph nodes have a worse prognosis. Univariate and multivariate analyses indicated that tumor size, grade, and age were independent risk factors for LNM. The nomogram constructed with these three factors can predict the risk of LNM with high accuracy (AUC: 0.767, 95% CI: 0.697–0.838) and good calibration. Based on the nomogram, a risk classification system satisfactorily stratified the patients into 3 groups with diverse risks of LNM. In the low‐risk group, there were no significant differences between sentinel lymph node biopsy and no axillary surgery. In the middle‐ and high‐risk groups, both SLNB and axillary lymph node dissection were superior to no axillary surgery, with similar survival benefits. CONCLUSIONS: The nomogram based on tumor size, grade, and age could conveniently and accurately predict the risk of LNM in MBC and assist clinicians in optimizing surgical strategies.