The correlation study between greyscale ultrasonography of invasive breast cancer and axillary lymph node involvement
Zhaoting Shi, Jian Le, Yaling Chen, Jiawei Li, Wenxiang Zhi
Abstract
Zhaoting Shi, Jian Le, Yaling Chen, Jiawei Li, Wenxiang Zhi
Abstract
Objective To investigate the relationship of greyscale ultrasonographic signs and clinical pathological characteristics with axillary lymph node metastasis in invasive breast cancer. Methods Three hundred and thirty-five patients with pathologically confirmed breast cancer were retrospectively analyzed, which categorized into 2 groups, including lymph node metastasis group and lymph node non-metastasis group. The clinical and pathological characteristics included age, primary tumor size, histological grade, and molecular subtypes. The ultrasonographic features were examined including orientation, shape, margin, echo pattern, posterior acoustic feature, and calcification. Chi-Square test and Logistic regression analysis were performed to analyze the relationship of clinical pathological characteristics and greyscale ultrasonographic signs with axillary lymph node metastasis. Results Age ( 10) contributed to axillary lymph node metastasis in 335 cases, according to univariate analysis (P<0.05). Multivariate Logistic regression analysis showed age (OR=0.573, P=0.019), the primary tumor size (OR=2.359, P=0.001), histological grade (OR=0.529, P=0.008), and number of margin angulation (OR=1.889, P=0.031) were risk factors of axillary lymph node metastasis in breast cancer. Conclusions Univariate and multivariate analyses show the correlation between ultrasonographic features and axillary lymph node involvement. Combining with clinical pathological data, it can provide a predictor of axillary lymph node metastasis. Key words: Ultrasonography; Invasive breast cancer; Lymph node metastasis; Clinical pathology
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Objective To investigate the relationship of greyscale ultrasonographic signs and clinical pathological characteristics with axillary lymph node metastasis in invasive breast cancer. Methods Three hundred and thirty-five patients with pathologically confirmed breast cancer were retrospectively analyzed, which categorized into 2 groups, including lymph node metastasis group and lymph node non-metastasis group. The clinical and pathological characteristics included age, primary tumor size, histological grade, and molecular subtypes. The ultrasonographic features were examined including orientation, shape, margin, echo pattern, posterior acoustic feature, and calcification. Chi-Square test and Logistic regression analysis were performed to analyze the relationship of clinical pathological characteristics and greyscale ultrasonographic signs with axillary lymph node metastasis. Results Age ( 10) contributed to axillary lymph node metastasis in 335 cases, according to univariate analysis (P<0.05). Multivariate Logistic regression analysis showed age (OR=0.573, P=0.019), the primary tumor size (OR=2.359, P=0.001), histological grade (OR=0.529, P=0.008), and number of margin angulation (OR=1.889, P=0.031) were risk factors of axillary lymph node metastasis in breast cancer. Conclusions Univariate and multivariate analyses show the correlation between ultrasonographic features and axillary lymph node involvement. Combining with clinical pathological data, it can provide a predictor of axillary lymph node metastasis. Key words: Ultrasonography; Invasive breast cancer; Lymph node metastasis; Clinical pathology
Key concepts: Medicine, Breast cancer, Univariate analysis, Lymph node, Pathological, Metastasis, Axillary lymph nodes, Radiology