Hu Jun, Du Xian, Jiang Yongbin, Wang Yunle, Yang Lijuan
Health Examination Center, Shanghai Health and Medical Center (Huadong Sanatorium), Wuxi, China.
Front Endocrinol (Lausanne). 2025 May 29;16:1550034. doi: 10.3389/fendo.2025.1550034. eCollection 2025.
This study aimed to explore the diagnostic value of clinical features in the assessment of malignant thyroid Imaging Reporting and Data System (TIRADS) category 4 thyroid nodules and to provide a more effective reference for clinical diagnostic practices.
A total of 998 patients with 1,103 TIRADS 4 thyroid nodules underwent conventional ultrasound (US) and clinical information assessment at the Shanghai Health and Medical Center from January 1, 2012, to June 30, 2024. A qualitative assessment of clinical and US features was performed, followed by univariable and multivariable logistic regression analyses using a training cohort, which contributed to the construction of the clinical TIRADS model. A receiver-operating characteristic (ROC) curve, a Hosmer-Lemeshow (HL) test and a decision curve analysis (DCA) were employed to further validate this model in the validation cohort.
Patient age, body mass index, sex, family history of thyroid carcinoma, and US features-such as vertical orientation, ill-defined or irregular margins or extrathyroidal extensions, microcalcifications, blood flow signals of central or peripheral vessels, and swollen cervical lymph nodes-were identified as independent risk factors in the clinical scoring model for TI-RADS 4 nodules. This diagnostic model achieved an area under the curve (AUC) of 0.943 [0.928, 0.959], with a sensitivity of 82.33%, specificity of 94.44%, diagnostic threshold of 5 points, accuracy of 87.42%, positive predictive value of 95.34%, and negative predictive value of 79.48% in the validation cohort. The HL tests and DCA also demonstrated excellent predictive performances.
The integration of clinical and US features in the construction of the diagnostic model can significantly enhance the diagnosis of TIRADS 4 thyroid nodules and provide a reliable evaluation tool for clinical practice.
本研究旨在探讨临床特征在评估甲状腺影像报告和数据系统（TIRADS）4类甲状腺结节中的诊断价值，为临床诊断实践提供更有效的参考。
2012年1月1日至2024年6月30日，共有998例患有1103个TIRADS 4类甲状腺结节的患者在上海健康与医学中心接受了常规超声（US）检查和临床信息评估。对临床和超声特征进行了定性评估，随后使用训练队列进行单变量和多变量逻辑回归分析，这有助于构建临床TIRADS模型。采用受试者操作特征（ROC）曲线、Hosmer-Lemeshow（HL）检验和决策曲线分析（DCA）在验证队列中进一步验证该模型。
患者年龄、体重指数、性别、甲状腺癌家族史以及超声特征，如垂直方向、边界不清或不规则、甲状腺外侵犯、微钙化、中央或外周血管血流信号以及颈部淋巴结肿大，被确定为TI-RADS 4类结节临床评分模型中的独立危险因素。该诊断模型在验证队列中的曲线下面积（AUC）为0.943[0.928, 0.959]，灵敏度为82.33%，特异度为94.44%，诊断阈值为5分，准确率为87.42%，阳性预测值为95.34%，阴性预测值为79.48%。HL检验和DCA也显示出优异的预测性能。
在诊断模型构建中整合临床和超声特征可显著提高TIRADS 4类甲状腺结节的诊断水平，并为临床实践提供可靠的评估工具。
