Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.
J Ultrasound Med. 2024 Dec;43(12):2311-2324. doi: 10.1002/jum.16564. Epub 2024 Sep 4.
To explore the clinical value of the nomogram based on spectral Doppler ultrasound combined with clinical pathological parameter in predicting axillary lymph node metastasis in breast cancer.
We prospectively gathered clinicopathologic and ultrasonic data from 240 patients confirmed breast cancer. The risk factors of axillary lymph node metastasis were analyzed by univariate and multivariate logistic regression, and the prediction model was established. The model calibration, predictive ability, and diagnostic efficiency in the training set and the testing set were analyzed by receiver operating characteristic curve and calibration curve analysis, respectively.
Univariate analysis showed that lymph node metastasis was related with tumor size, Ki-67, axillary ultrasound, ultrasound spectral quantitative parameter, internal echo, and calcification (P < .05). Multivariate logistic regression analysis showed that the Ki-67, axillary ultrasound, quantitative parameter (the mean of the mid-band fit in tumor and posterior tumor) were independent risk factors of axillary lymph node metastasis (P < .05). The models developed using Ki-67, axillary ultrasound, and quantitative parameters for predicting axillary lymph node metastasis demonstrated an area under the receiver operating characteristic curve of 0.83. Additionally, the prediction model exhibited outstanding predictability for axillary lymph node metastasis, as evidenced by a Harrell C-index of 0.83 (95% confidence interval 0.73-0.93).
Axillary ultrasound combined with Ki-67 and spectral ultrasound parameters has the potential to predict axillary lymph node metastasis in breast cancer, which is superior to axillary ultrasound alone.
探讨基于超声光谱多谱勒联合临床病理参数的列线图预测乳腺癌腋窝淋巴结转移的临床价值。
前瞻性收集 240 例经病理证实的乳腺癌患者的临床病理及超声资料，采用单因素和多因素逻辑回归分析腋窝淋巴结转移的危险因素，建立预测模型。分别采用受试者工作特征曲线和校准曲线分析，评估模型在训练集和验证集的校准度、预测能力和诊断效率。
单因素分析显示，淋巴结转移与肿瘤大小、Ki-67、腋窝超声、超声光谱定量参数、内部回声和钙化有关（P < .05）。多因素逻辑回归分析显示，Ki-67、腋窝超声、定量参数（肿瘤和肿瘤后段的中带拟合均值）是腋窝淋巴结转移的独立危险因素（P < .05）。基于 Ki-67、腋窝超声和定量参数建立的预测模型预测腋窝淋巴结转移的受试者工作特征曲线下面积为 0.83。此外，预测模型对腋窝淋巴结转移具有出色的预测能力，哈雷尔 C 指数为 0.83（95%置信区间 0.73-0.93）。
联合 Ki-67 和超声光谱参数的腋窝超声检查有可能预测乳腺癌腋窝淋巴结转移，优于单纯的腋窝超声检查。
