AUTHOR=Hu Jun , Du Xian , Jiang Yongbin , Wang Yunle , Yang Lijuan 

TITLE=Incorporation of clinical features into a multivariate logistic regression model for the differential diagnosis of benign and malignant TI-RADS 4 thyroid nodules

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2025.1550034

DOI=10.3389/fendo.2025.1550034

ISSN=1664-2392

ABSTRACT=ObjectiveThis 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.MethodsA 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.ResultsPatient 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.ConclusionsThe 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.