Nomogram based on multiparametric analysis of early‐stage breast cancer: Prediction of high burden metastatic axillary lymph nodes

Abstract

Abstract Background The Z0011 and AMAROS trials found that axillary lymph node dissection (ALND) was no longer mandatory for early‐stage breast cancer patients who had one or two metastatic axillary lymph nodes (mALNs). The aim of our study was to establish a nomogram which could be used to quantitatively predict the individual likelihood of high burden mALN (≥3 mALN). Methods We retrospectively analyzed 564 women with early breast cancer who had all undergone both ultrasound (US) and magnetic resonance imaging (MRI) to examine axillary lymph nodes before radical surgery. All the patients were divided into training (n = 452) and validation (n = 112) cohorts by computer‐generated random numbers. Their clinicopathological features and preoperative imaging associated with high burden mALNs were evaluated by logistic regression analysis to develop a nomogram for predicting the probability of high burden mALNs. Results Multivariate analysis showed that high burden mALNs were significantly associated with replaced hilum and the shortest diameter >10 mm on MRI, with cortex thickness >3 mm on US (p < 0.05 each). These imaging criteria plus higher grade (grades II and III) and quadrant of breast tumor were used to develop a nomogram calculating the probability of high burden mALNs. The AUC of the nomogram was 0.853 (95% CI: 0.790–0.908) for the training set and 0.783 (95% CI: 0.638–0.929) for the validation set. Both internal and external validation evaluated the accuracy of nomogram to be good. Conclusion A well‐discriminated nomogram was developed to predict the high burden mALN in early‐stage breast patients, which may assist the breast surgeon in choosing the appropriate surgical approach.

Keywords

• axillary lymph node
• breast cancer
• clinicopathological features
• magnetic resonance imaging
• ultrasound