Non-sentinel node metastasis prediction during surgery in breast cancer patients with one to three positive sentinel node(s) following neoadjuvant chemotherapy.

Our aim was to develop a tool to accurately predict the possibility of non-sentinel lymph node metastasis (NSLNM) during surgery so that a surgeon might decide the extent of further axillary lymph node dissection intraoperatively for patients with 1-3 positive sentinel lymph node(s) (SLN) after neoadjuvant chemotherapy. After retrospective analysis of Asan Medical Center (AMC) database, we included 558 patients' records who were treated between 2005 and 2019. 13 factors were assessed for their utility to predict NSLNM with chi-square and logistic regression with a bootstrapped, backward elimination method. Based on the result of the univariate analysis for statistical significance, number of positive SLN(s), number of frozen nodes, Progesterone Receptor (PR) positivity, clinical N stage were selected for the multivariate analysis and were utilized to generate a nomogram for prediction of residual nodal disease. The resulting nomogram was tested for validation by using a patient group of more recent, different time window at AMC. We designed a nomogram to be predictive of the NSLNM which consisted of 4 components: number of SLN(s), number of frozen nodes, PR positivity, and clinical N stage before neoadjuvant chemotherapy. The Area under the receiver operating characteristics curve (AUC) value of this formula was 0.709 (95% CI, 0.658-0.761) for development set and 0.715 (95% CI, 0.634-0.796) for validation set, respectively. This newly created AMC nomogram may provide a useful information to a surgeon for intraoperative guidance to decide the extent of further axillary surgery.