Abstract P1-04-04: Development and validation of a nomogram for axillary lymph node metastasis risk in breast cancer

Abstract Purpose: Preoperative assessment of axillary lymph node (ALN) status is essential for breast cancer treatment planning. To prospectively analyze risk factors for ALN metastasis in breast cancer patients, comparing high-resolution computed tomography (HRCT) imaging with pathology, and to develop and validate a nomogram predicting the status of each node. Methods: From April 2023 to May 2024, patients with pathologically proven breast cancer were enrolled in the study. All patients underwent a chest HRCT examination within one week prior to surgery. ALN specimens were subjected to pathological examination and anatomically matched to HRCT imaging. The least absolute shrinkage and selection operator (LASSO) regression was employed to refine the features for the metastasis lymph node (MLN). Subsequently, the final selected features were determined through multivariate logistic regression analysis and utilized to construct a nomogram. The discrimination, calibration, and clinical utility of the predicting model were evaluated using the concordance index (C-index), area under the curve (AUC), receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis. Internal validation was conducted through bootstrapping validation. Results: A total of 302 ALN from 98 patients were included in this study. The patients were divided into two groups based on pathology: a MLN group (71 nodes) and a non-metastasis lymph node (NMLN) group (231 nodes). The predictors included in the prediction nomogram encompassed the mean CT value, short diameter, border, and shape of ALN, as well as the Ki-67 status and histological grade of the primary tumor. The model exhibited satisfactory discrimination, with a C-index of 0.869 [95% confidence interval (CI): 0.826-0.912] and an AUC of 0.862 (95% CI, 0.815-0.909). Moreover, in the interval validation, the model demonstrated its high performance, achieving a C-index of 0.845 and an AUC of 0.857. The calibration curve demonstrated a high degree of concordance between the predicted and actual probabilities. The decision curve analysis demonstrated that the prediction nomogram was clinically useful when the threshold for intervention was set at the metastasis possibility range of 1% to 86%. Conclusion: The prediction nomogram combined with preoperative pathology and HRCT imaging have the potential to improve the evaluation of ALN status. This integrated approach can serve as a valuable reference for the management of breast cancer patients. Citation Format: Xiaoyun Mao, Shijing Wang. Development and validation of a nomogram for axillary lymph node metastasis risk in breast cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr P1-04-04.