A Model to Predict the Risk of Lymph Node Metastasis in Breast Cancer Based on Clinicopathological Characteristics

BACKGROUND: Sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) may cause lymphatic and nervous system side effects in patients with breast cancer. It is imperative to develop a model to evaluate the risk of sentinel lymph node metastasis to avoid unnecessary operation. PATIENTS AND METHODS: A total of 2705 cases of female breast cancer patients enrolled in this retrospective study. We divided into the training group (SLNB group) and the validation group (ALND group) to analyze the relathionship between lymph node metastasis and clinical-pathological factors. Logistic regression analysis was performed to verify the variables which involved in ALN metastasis and established a prediction model. ROC curves were employed to evaluate the predictive ability of the model. RESULTS: In the SLNB group, 9 variables, including pathological type, histological grade, tumor size, hormone receptor, HER-2, Ki-67, multifocality, and molecular subtypes, were related to breast cancer ALN metastasis. Clinically negative lymph nodes, favorable histologic type, tumor size <2 cm, and Ki-67 <15% were at very low risk for lymph node metastasis. The AUC of the validation group was 0.786. CONCLUSION: We successfully establish a mathematics model to predict lymph node metastasis of breast cancer. Axillary surgery should be individual with preoperative clinical characteristics, especially for patients with a longer life expectancy.