Laboratory Indicators Predict Axillary Nodal Pathologic Complete Response After Neoadjuvant Therapy in Breast Cancer

The purpose was to integrate clinicopathological and laboratory indicators to predict axillary nodal pathologic complete response (apCR) after neoadjuvant therapy (NAT). The pretreatment clinicopathological and laboratory indicators of 416 clinical nodal-positive breast cancer patients who underwent surgery after NAT were analyzed from April 2015 to 2020. Predictive factors of apCR were examined by logistic analysis. A nomogram was built according to logistic analysis. Among the 416 patients, 37.3% achieved apCR. Multivariate analysis showed that age, pathological grading, molecular subtype and neutrophil-to-lymphocyte ratio were independent predictors of apCR. A nomogram was established based on these four factors. The area under the curve (AUC) was 0.758 in the training set. The validation set showed good discrimination, with AUC of 0.732. In subtype analysis, apCR was 23.8, 47.1 and 50.8% in hormone receptor-positive/HER2-, HER2+ and triple-negative subgroups, respectively. According to the results of the multivariate analysis, pathological grade and fibrinogen level were independent predictors of apCR after NAT in HER2+ patients. Except for traditional clinicopathological factors, laboratory indicators could also be identified as predictive factors of apCR after NAT. The nomogram integrating pretreatment indicators demonstrated its distinguishing capability, with a high AUC, and could help to guide individualized treatment options.Lay abstract The purpose of this study was to integrate more pretreatment indicators, including clinicopathological factors and simple laboratory indicators, to predict axillary nodal pathologic complete response (apCR) after neoadjuvant therapy for breast cancer. The authors collected the pretreatment clinicopathological factors and laboratory indexes of 416 nodal-positive patients with breast cancer. The authors then built a nomogram to predict the therapeutic effect in axillary lymph nodes. Among 416 patients, 37.3% (155 of 416) achieved apCR. The results showed that age, pathological grading, molecular subtype and neutrophil-to-lymphocyte ratio were independent predictors of apCR. Based on these four factors, a nomogram was then built. This nomogram helped to predict apCR. In addition to traditional clinicopathological factors, laboratory indicators were also identified as predictive factors of apCR after neoadjuvant therapy. Integrating pretreatment indicators might help to predict apCR and guide individualized treatment options.