Nomogram to differentiate benign and malignant thyroid nodules in the American College of Radiology Thyroid Imaging Reporting and Data System level 5

作者：Ting Hu, Zhengyi Li, Chuan Peng, Libing Huang, Huifang Li, Xu Han, Xingzhang Long, Wei Huang, Ruhai Zou · 发表于：Clinical Endocrinology · 年份：2022 · DOI：10.1111/cen.14824 · 被引用次数：8 · 研究领域：Thyroid Cancer Diagnosis and Treatment、Thyroid and Parathyroid Surgery、Thyroid Disorders and Treatments

OBJECTIVES: To develop and validate a nomogram for differentiating benign and malignant thyroid nodules of American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) level 5 (TR5) and improving the performance of the guideline. METHODS: From May 2018 to December 2019, 640 patients with TR5 nodules were retrospectively included in the primary cohort. Univariate and multivariable analyses were performed to determine the risk factors for thyroid cancer. A nomogram was established on the basis of multivariable analyses; the performance of the nomogram was evaluated with respect to discrimination, calibration, and clinical usefulness. The nomogram model was also compared to the ACR score model. External validation was performed and the independent validation cohort contained 201 patients from April 2021 to January 2022. RESULTS: Multivariable analyses showed that age, tumour location, multifocality, concomitant Hashimoto's disease, neck lymph node status reported by ultrasound (US) and ACR score were the independent risk factors for thyroid cancer (all p < .05). The nomogram showed good discrimination, with an area under the curve (AUC) of 0.786 (95% confidence interval [CI]: 0.742-0.830) and 0.712 (95% CI: 0.615-0.809) in the primary cohort and external validation cohort, respectively. Decision curve analysis demonstrated the clinical usefulness of the model. Compared to the ACR score model, the nomogram showed higher AUC (0.786 vs. 0.626, p < .001) a...