Development and Validation of an Ultrasound and Clinicopathological Features-Based Nomogram for Predicting Non-Sentinel Lymph Node Metastasis in Breast Cancer Patients: A Single-Center Observational Study.

Abstract

Objectives: The objective of this study was to develop a nomogram based on ultrasound and clinicopathological variables to evaluate the risk of non-sentinel lymph node metastasis (NSLNM) in early breast cancer patients with positive sentinel lymph nodes (SLNs).

Methods: A retrospective analysis was conducted on 438 breast cancer patients treated at the First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's Hospital) between June 2017 and August 2024. Patients were randomly divided into training and testing sets in a 7:3 ratio for the development and validation of the nomogram, respectively. Multivariable logistic regression analysis was performed to determine independent predictors of non-sentinel lymph node status, and a nomogram was created to assess the probability of NSLNM.

Results: SLN%, lesions, longest diameter of the mass, number of suspicious axillary lymph nodes (ALNs) on US, and level of suspicious ALNs were identified as the final independent predictors of NSLNM in multivariate logistic regression analysis. The nomogram predicting NSLNM was accurately calibrated, with an area under the curve of 0.84 for the training set and 0.82 for the testing set.

Conclusion: In this study, we developed a nomogram model for predicting NSLNM based on ultrasound and clinicopathological features, which is useful for accurately assessing the risk of NSLNM in breast cancer patients and serves as a reference for clinicians when deciding how to treat ALNs.