Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Department of Ultrasound, Second Affiliated Hospital of Chongqing Medical University and Chongqing Key Laboratory of Ultrasound Molecular Imaging, Chongqing, China.
Front Endocrinol (Lausanne). 2022 Jan 27;12:789310. doi: 10.3389/fendo.2021.789310. eCollection 2021.
To screen out the predictors of central cervical lymph node metastasis (CLNM) for papillary thyroid carcinoma (PTC) and establish a prediction model to guide the operation of PTC patients (cN0).
Data from 296 PTC patients (cN0) who underwent thyroid operation at the Second Affiliated Hospital of Chongqing Medical University were collected and retrospectively analyzed. They were divided into two groups in accordance with central CLNM or not. Their information, including ultrasound (US) features, BRAF status, and other characteristics of the two groups, was analyzed and compared using univariate and multivariate logistic regression analyses, and the independent predictors were selected to construct a nomogram. The calibration plot, C-index, and decision curve analysis were used to assess the prediction model's calibration, discrimination, and clinical usefulness.
A total of 37.8% (112/296) of PTC patients had central CLNM, and 62.2% (184/296) did not. The two groups were compared using a univariate logistic regression analysis, and there were no significant differences between the two groups in sex, aspect ratio, boundary, morphology, hypoechoic nodule, thyroid peroxidase antibody, or tumor location (P>0.05), and there were significant differences between age, tumor size, capsule contact, microcalcifications, blood flow signal, thyroglobulin antibodies (TgAb), and BRAF gene status (P<0.05). A multivariate logistic regression analysis was performed to further clarify the correlation of these indices. However, only tumor size (OR=2.814, 95% Cl=1.6344.848, P<0.001), microcalcifications (OR=2.839, 95% Cl=1,6844.787, P<0.001) and TgAb (OR=1.964, 95% Cl=1.039~3,711, P=0.038) were independent predictors of central CLNM and were incorporated and used to construct the prediction nomogram. The model had good discrimination with a C-index of 0.715. An ROC curve analysis was performed to evaluate the accuracy of this model. The decision curve analysis showed that the model was clinically useful when intervention was decided in the threshold range of 16% to 80%.
In conclusion, three independent predictors of central CLNM, including tumor size (> 1.0 cm), US features (microcalcifications), and TgAb (positive), were screened out. A visualized nomogram model was established based on the three predictors in this study, which could be used as a basis of central cervical lymph node dissection (CLND) for PTC patients (cN0).
筛选甲状腺乳头状癌（PTC）中央颈部淋巴结转移（CLNM）的预测因子，并建立预测模型以指导 PTC 患者（cN0）的手术。
回顾性分析 296 例在重庆医科大学第二附属医院接受甲状腺手术的 PTC 患者（cN0）的临床资料，根据是否存在中央 CLNM 将患者分为两组。使用单因素和多因素逻辑回归分析比较两组患者的超声（US）特征、BRAF 状态和其他特征，并选择独立预测因子构建列线图。使用校准图、C 指数和决策曲线分析评估预测模型的校准、区分度和临床实用性。
共有 37.8%（112/296）的 PTC 患者存在中央 CLNM，62.2%（184/296）患者不存在中央 CLNM。使用单因素逻辑回归分析比较两组患者的临床特征，结果显示两组患者在性别、纵横比、边界、形态、低回声结节、甲状腺过氧化物酶抗体或肿瘤位置方面无统计学差异（P＞0.05），而在年龄、肿瘤大小、包膜接触、微钙化、血流信号、甲状腺球蛋白抗体和 BRAF 基因状态方面有统计学差异（P＜0.05）。进一步进行多因素逻辑回归分析以明确这些指标的相关性。然而，只有肿瘤大小（OR=2.814，95%Cl=1.6344.848，P＜0.001）、微钙化（OR=2.839，95%Cl=1.6844.787，P＜0.001）和甲状腺球蛋白抗体（OR=1.964，95%Cl=1.039~3.711，P=0.038）是中央 CLNM 的独立预测因子，纳入并用于构建预测列线图。该模型具有良好的区分度，C 指数为 0.715。进行 ROC 曲线分析以评估该模型的准确性。决策曲线分析显示，当干预决策的阈值范围为 16%至 80%时，该模型具有临床实用性。
本研究筛选出三个独立的中央 CLNM 预测因子，包括肿瘤大小（＞1.0cm）、US 特征（微钙化）和甲状腺球蛋白抗体（阳性），并建立了基于这三个预测因子的可视化列线图模型，可作为 PTC 患者（cN0）中央颈淋巴结清扫（CLND）的依据。
