Development and validation of an ultrasonography and clinicopathological features-based nomogram for non-sentinel lymph node metastasis.

Background: With the development of precise treatment for breast cancer, the current trend of clinical treatment aims to limit axillary surgery as much as possible. At present, there is an unmet need to predict the probability of patients with a low risk of non-sentinel lymph node (SLN) metastasis and determine whether the omission of axillary lymph node dissection (ALND) is appropriate.

Methods: We retrospectively analyzed the data of patients with breast cancer who underwent sentinel lymph node biopsy (SLNB) and ALND. The patients were randomly assigned to training and validation sets. The associations between non-SLN metastasis (NSLNM) and ultrasonography and clinicopathological characteristics were assessed by multivariate logistic regression. Then, a nomogram model was constructed and validated using the calibration curve and the receiver operating characteristic curve.

Results: Vascular infiltration, positive SLN number, negative SLN number, human epidermal growth factor receptor 2 (HER2) status, and lymph node shape were identified as independent predictive factors for positive NSLNM. The areas under the curve of the nomogram model to predict NSLNM were 0.793 and 0.780 in the training and validation sets, respectively, and P=0.161 and P=0.768 in the Hosmer-Lemeshow goodness of fit test, respectively.

Conclusions: A nomogram model based on ultrasonography and clinicopathological features predicting NSLNM was established in our study, which is helpful for accurately assessing the risk of NSLNM in invasive breast cancer and providing evidence for individual surgical procedures involving axillary lymph nodes.