To analyze the factors affecting the axillary lymph node metastasis (ALNM) after neoadjuvant chemotherapy(NCT) for breast cancer and establish a model for predicting ALNM in order to provide a reference for screening the patients with ALNM after NCT.

We retrospectively analyzed the clinical data of 196 patients who received NCT in the Affiliated Hospital of Southwest Medical University between July 2014 and April 2018. Age, menstrual status, tumor stage after NCT, preoperative lymph node status, tumor location, chemotherapy regimen, times of chemotherapy, ER status, HER-2 status and Ki67 expression were used as evaluation parameters. The relationship between the clinicopathological characteristics and ALNM was analyzed by t test, χ² test and Fisher exact probability test. The above-mentioned factors were used as input variables to fit the equation, and the factors which met the minimum Akaike information criterion were included in the multivariate analysis. The predictive model was established and the nomogram was drawn. According to the clinicopathological characteristic of patients, the risk of ALNM was quantified in the nomogram. The predictive effect of the model was evaluated by the receiver operating characteristic (ROC) curve. Finally, the research data were divided into 10 groups by the ten-fold cross-validation method: nine groups for modeling and one group for verifying the reliability of this predictive model.

The following clinicopathological characteristics presented a significant difference between non-ALNM group and ALNM group after NCT: tumor staging after NCT, preoperative axillary lymph node staging, tumor location, ER status, and HER-2 status (χ² =20.876, P<0.001; χ² =57.342, P<0.001; χ² =13.800, P=0.008; χ² =15.041, P<0.001; χ² =5.770, P=0.016). Multivariate analysis results showed that preoperative ALNM, ER positive and low expression of Ki67 (OR=30.27, 95%CI: 10.57-108.28, P<0.001; OR=0.28, 95%CI: 0.11-0.69, P=0.007; OR=0.96, 95%CI: 0.93-1.00, P=0.032) were independent risk factors for ALNM after NCT. The area under the ROC curve of this model was 0.89 (95%CI: 0.84-0.94, P<0.001). The average accuracy and Kappa value of the ten-fold cross-validation predictive model were 84.9% and 0.611, respectively. If the probability of ALNM was 0.5 according to the nomogram predictive model, the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio and Yoden index were 91.2%(134/147), 73.5%(36/49), 86.7%(170/196), 91.2%(134/147), 73.5%(36/49), 3.44, 0.12 and 0.65, respectively.

This predictive model can predict the risk of ALNM after NCT, which provides more accurate decision-making basis for breast cancer patients.