Objective:To investigate the predictive value of multimodal ultrasound features combined with serum carcinoembryonic antigen (CEA) and cytokeratin (CK)19 levels for axillary lymph node metastasis in breast cancer.MethodsA retrospective analysis was conducted on breast cancer patients in The First Hospital of Qinhuangdao from February 2023 to August 2024, assessing their multimodal ultrasound features and serum CEA and CK19 levels at initial diagnosis. According to the pathological results of axillary lymph nodes, patients were categorized into a metastasis-negative group and a metastasis-positive group. Comparative analyses were performed between the two groups regarding the maximum diameter of the primary breast lesion, margin characteristics, presence of microcalcifications, orientation (parallel or non-parallel based on the length-to-width ratio), Adler classification of blood flow imaging, and shear wave elastography parameters (E_max and E_min values). Additionally, serum CEA and CK19 levels were evaluated. The predictive value of combining multimodal ultrasound features with serum CEA and CK19 levels for axillary lymph node metastasis was explored.ResultsThis study included a total of 136 breast cancer patients, including 63 cases in the axillary lymph node metastasis-negative group and 73 cases in the metastasis-positive group. Univariate analysis and logistic regression identified the presence of microcalcifications in the primary breast lesion, Adler grade Ⅱ-Ⅲ blood flow, elevated E_max values, and increased serum CEA levels as independent predictors of axillary lymph node metastasis in breast cancer. A predictive model was constructed based on these four factors, achieving an area under the curve (AUC) of 0.910 (95% CI 0.862–0.957).ConclusionThe presence of microcalcifications in the primary breast lesion, Adler grade Ⅱ-Ⅲ blood flow, elevated E_max values, and increased serum CEA levels indicate a higher likelihood of axillary lymph node metastasis in breast cancer. A logistic regression model constructed with these four predictive factors demonstrates potential for predicting axillary lymph node metastasis in breast cancer.