Abstract P3-01-14: A model incorporating axillary tail position on mammography for preoperative prediction of non-sentinel lymph node metastasis in patients with initial cN+ breast cancer after neoadjuvant chemotherapy

Abstract

Abstract Background and Objectives: Few models with good discriminative power have been constructed to predict the risk of non-sentinel lymph node (NSLN) metastasis in breast cancer prior to breast surgery after neoadjuvant chemotherapy (NAC). This study aimed to develop a new model for the prediction of NSLN metastasis in patients with initial clinical node positivity (cN+).Methods: The present study reviewed a total of 257 patients (179 in the training set and 78 in the testing set) with cN+ breast cancer who underwent both sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) following NAC. Univariate and multivariate analyses were used to select clinical factors affecting NSLN metastasis prior to breast surgery. A logistic regression model was developed based on these factors and the results of post-NAC axillary tail position on mammography (AT) and ultrasound (AUS).Results: Four factors with p<0.05 in the univariate analysis, including ycT0 (odds ratio [OR]: 4.84, 95% confidence interval [CI]: 2.13-11.91, p<0.001), clinical stage before NAC (OR: 2.68, 95% CI: 1.15-6.58, p=0.025), estrogen receptor (ER) expression (OR: 3.29, 95% CI: 1.39-8.39, p=0.009), and Her2 status (OR: 0.21, 95% CI: 0.08-0.50, p=0.001), were independent predictors of NSLN metastases. The clinical model based on the above data resulted in an AUC of 0.82 (95% confidence interval [CI]: 0.76-0.88) in the training set and 0.83 (95% CI: 0.74-0.92) in the validation set. The results of the post-NAC AUS and. AT were added to the clinical model to construct a clinical imaging model for the prediction of NSLN metastasis with an area under the curve of 0.87 (95% confidence interval [CI]: 0.81-0.93) in the training set and 0.89 (95% CI: 0.82-0.96) in the validation set.Conclusions: The present study incorporated the results of post-NAC AT and AUS with other clinal factors to develop a new model for the prediction of NSLN metastasis in patients with initial cN+ prior to breast surgery. This model performed excellently, allowing physicians to select patients for whom unnecessary ALND could be omitted after NAC. Citation Format: Kun Wang, Teng Zhu, Tingfeng Zhang. A model incorporating axillary tail position on mammography for preoperative prediction of non-sentinel lymph node metastasis in patients with initial cN+ breast cancer after neoadjuvant chemotherapy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-01-14.