Zhang S, Xu C, Yang B, Yan D
The Second Affiliated Hospital of Soochow University, Department of Medical Ultrasound, Suzhou, P.R. China.
The First Affiliated Hospital of Nanjing Medical University, Department of Ultrasound, Nanjing Jiangsu, P.R. China.
Acta Endocrinol (Buchar). 2022 Jul-Sep;18(3):333-342. doi: 10.4183/aeb.2022.333.
To establish a nomogram combining preoperative ultrasonic and clinical features for predicting lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN) metastasis in papillary thyroid carcinoma (PTC) patients.
Preoperative ultrasonic and clinical variables of patients with PTC from 2014 to 2021 were retrospectively analyzed. The risk factors associated with LN-prRLN metastasis were identified and validated through a developed nomogram model based on univariate and multivariate logistic regression analysis.
A total of 615 patients (690 lesions) were enrolled for the training dataset and 207 patients (226 lesions) for the validation dataset with 54 (6.57%) patients developing LN-prRLN metastasis. Multivariate logistic regression analysis demonstrated that the preoperative ultrasound measurement of larger tumors (≥20 mm), higher TI-RADS category (category 5), and higher thyroglobulin level (9.86 ng/mL) in patients with PTC were predictive factors for LN-prRLN metastasis. The nomogram model was established and verified yielding a relatively good predictive performance in the training and validation dataset (AUC: 0.868 . 0.851).
The nomogram combining preoperative ultrasonography with clinical features in this study is highly predictive of LN-prRLN metastasis in patients with PTC, which may provide more personalized recommendations for clinicians in preoperative decision-making for complete dissection of LN-prRLN.
建立一种结合术前超声和临床特征的列线图,用于预测甲状腺乳头状癌(PTC)患者右侧喉返神经后方淋巴结(LN-prRLN)转移情况。
回顾性分析2014年至2021年PTC患者的术前超声及临床变量。通过基于单因素和多因素逻辑回归分析建立的列线图模型,识别并验证与LN-prRLN转移相关的危险因素。
共纳入615例患者(690个病灶)作为训练数据集,207例患者(226个病灶)作为验证数据集,其中54例(6.57%)患者发生LN-prRLN转移。多因素逻辑回归分析表明,PTC患者术前超声测量较大肿瘤(≥20 mm)、较高的TI-RADS分类(5类)以及较高的甲状腺球蛋白水平(9.86 ng/mL)是LN-prRLN转移的预测因素。建立并验证了列线图模型,其在训练和验证数据集中具有相对较好的预测性能(AUC:0.868、0.851)。
本研究中结合术前超声检查与临床特征的列线图对PTC患者的LN-prRLN转移具有较高的预测性,可为临床医生在术前决策时对LN-prRLN进行彻底清扫提供更个性化的建议。