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预测甲状腺乳头状癌中央淋巴结转移:基于临床、超声及增强计算机断层扫描特征的列线图

Predicting central lymph node metastasis in papillary thyroid cancer: A nomogram based on clinical, ultrasound and contrast‑enhanced computed tomography characteristics.

作者信息

Zhang Qianru, Xu Shangyan, Song Qi, Ma Yuanyuan, Hu Yan, Yao Jiejie, Zhan Weiwei

机构信息

Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, P.R. China.

Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, P.R. China.

出版信息

Oncol Lett. 2024 Aug 5;28(4):478. doi: 10.3892/ol.2024.14611. eCollection 2024 Oct.

Abstract

Central lymph node (CLN) status is considered to be an important risk factor in patients with papillary thyroid carcinoma (PTC). The aim of the present study was to identify risk factors associated with CLN metastasis (CLNM) for patients with PTC based on preoperative clinical, ultrasound (US) and contrast-enhanced computed tomography (CT) characteristics, and establish a prediction model for treatment plans. A total of 786 patients with a confirmed pathological diagnosis of PTC between January 2021 to December 2022 were included in the present retrospective study, with 550 patients included in the training group and 236 patients enrolled in the validation group (ratio of 7:3). Based on the preoperative clinical, US and contrast-enhanced CT features, univariate and multivariate logistic regression analyses were used to determine the independent predictive factors of CLNM, and a personalized nomogram was constructed. Calibration curve, receiver operating characteristic (ROC) curve and decision curve analyses were used to assess discrimination, calibration and clinical application of the prediction model. As a result, 38.9% (306/786) of patients with PTC and CLNM(-) status before surgery had confirmed CLNM using postoperative pathology. In multivariate analysis, a young age (≤45 years), the male sex, no presence of Hashimoto thyroiditis, isthmic location, microcalcification, inhomogeneous enhancement and capsule invasion were independent predictors of CLNM in patients with PTC. The nomogram integrating these 7 factors exhibited strong discrimination in both the training group [Area under the curve (AUC)=0.826] and the validation group (AUC=0.818). Furthermore, the area under the ROC curve for predicting CLNM based on clinical, US and contrast-enhanced CT features was higher than that without contrast-enhanced CT features (AUC=0.818 and AUC=0.712, respectively). In addition, the calibration curve was appropriately fitted and decision curve analysis confirmed the clinical utility of the nomogram. In conclusion, the present study developed a novel nomogram for preoperative prediction of CLNM, which could provide a basis for prophylactic central lymph node dissection in patients with PTC.

摘要

中央淋巴结(CLN)状态被认为是甲状腺乳头状癌(PTC)患者的一个重要风险因素。本研究的目的是基于术前临床、超声(US)和增强计算机断层扫描(CT)特征,确定PTC患者CLN转移(CLNM)的相关风险因素,并建立治疗方案的预测模型。本回顾性研究纳入了2021年1月至2022年12月期间共786例经病理确诊为PTC的患者,其中550例患者纳入训练组,236例患者纳入验证组(比例为7:3)。基于术前临床、US和增强CT特征,采用单因素和多因素逻辑回归分析确定CLNM的独立预测因素,并构建个性化列线图。采用校准曲线、受试者操作特征(ROC)曲线和决策曲线分析来评估预测模型的辨别力、校准度和临床应用。结果显示,术前CLNM(-)状态的PTC患者中,38.9%(306/786)术后病理证实存在CLNM。在多因素分析中,年轻(≤45岁)、男性、无桥本甲状腺炎、峡部位置、微钙化、不均匀强化和包膜侵犯是PTC患者CLNM的独立预测因素。整合这7个因素的列线图在训练组[曲线下面积(AUC)=0.826]和验证组(AUC=0.818)中均表现出较强的辨别力。此外,基于临床、US和增强CT特征预测CLNM的ROC曲线下面积高于不使用增强CT特征时的曲线下面积(分别为AUC=0.818和AUC=0.712)。此外,校准曲线拟合良好,决策曲线分析证实了列线图的临床实用性。总之,本研究开发了一种用于术前预测CLNM的新型列线图,可为PTC患者预防性中央淋巴结清扫提供依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecc6/11332582/4d86cc611003/ol-28-04-14611-g00.jpg

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