Prediction of axillary response after neoadjuvant chemotherapy in clinical node positive breast cancer

BACKGROUND: For clinical lymph node positive (cN+) breast cancer, the false negative rate of sentinel lymph node biopsy (SLNB) after neoadjuvant chemotherapy (NAC) is high. Prediction of axillary response after NAC may provide a better way of patient selection. Our study was designed to evaluate factors associated with axillary pathologic complete response (ypN0) after NAC, and to assess the accuracy of the published Olga Kantor predictive model. METHODS: A total of 406 patients with cN+ breast cancer were enrolled in this study. All patients had received full courses of NAC before undergoing axillary lymph node dissection (ALND). Univariate analyses and multivariate analysis were performed to explore independent predictors of ypN0. Then the Olga Kantor model were validated by the data of patients enrolled. The Olga Kantor model is not ideal because the pathological breast tumor response was not available before surgery, the clinical breast tumor response was assessed in our study as a modification. The accuracy of the validation and modification of Olga Kantor model were assessed by the area under receiver operating characteristic (ROC) curve (AUC). RESULTS: Age (P=0.004), molecular subtype (P=0.000), tumor grade (P=0.006), clinical tumor response (P=0.000) and Ki-67 (P=0.009) were correlated with ypN0. Age, molecular subtype and the clinical tumor response were independent predictors of ypN0 (P<0.05). In validation and modification model, the AUC values were 0.795 and 0.789, respectively, there were no significant differences between the two models (P=0.536). For model score ≤3, 4–7 and ≥8 in the modification model, the ypN0 rate were 3.9% (2/51), 22.5% (59/262) and 67.7% (63/93), respectively. CONCLUSIONS: The Olga Kantor predictive model had high accuracy predicting ypN0 after NAC. Our modification model achieved the same predictive efficiency but is more feasible for clinical practice. Patients with higher scores were more likely to achieve ypN0, so SLNB might be a better way than ALND. However, more patient data and multicenter cohort trials are needed to verify the study.