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C-TIRADS、ACR-TIRADS和ATA指南在甲状腺结节恶性风险分层中的比较。

Comparison of the C-TIRADS, ACR-TIRADS, and ATA guidelines in malignancy risk stratification of thyroid nodules.

作者信息

Cai Yifeng, Yang Ruixuan, Yang Shuhui, Lu Laishun, Ma Rui, Xiao Zidong, Lin Nie, Huang Yuhan, Chen Liwen

机构信息

Department of Endocrinology, Shantou Central Hospital, Shantou, China.

Department of Laboratory Medicine, Shantou Central Hospital, Shantou, China.

出版信息

Quant Imaging Med Surg. 2023 Jul 1;13(7):4514-4525. doi: 10.21037/qims-22-826. Epub 2023 May 15.

DOI:10.21037/qims-22-826
PMID:37456322
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10347339/
Abstract

BACKGROUND

To compare the diagnostic performance in determining the malignancy of thyroid nodules and the fine needle aspiration (FNA) recommendations of the guidelines set forth by the Superficial Organ and Vascular Ultrasound Group of the Society of Ultrasound in Medicine of the Chinese Medical Association in 2020 [2020 Chinese Thyroid Imaging Reporting and Data System (C-TIRADS)], the American College of Radiology in 2017 (2017 ACR-TIRADS) and the American Thyroid Association in 2015 (2015 ATA guidelines).

METHODS

From January 2021 to December 2021, 1,228 thyroid nodules with definitive postoperative histopathology and ultrasound (US) examination within 3 months before surgery in Shantou Central Hospital were enrolled in this study. We collected the data in 2022. The participants formed a consecutive series. The clinical and US features of the nodules were retrospectively reviewed and categorized according to the 2020 C-TIRADS, the 2017 ACR-TIRADS and the 2015 ATA guidelines. The diagnostic performance and unnecessary FNA rates of the three guidelines were calculated.

RESULTS

The 2017 ACR-TIRADS had the highest diagnostic performance [area under the receiver operating characteristic curve (AUROC) 0.938], followed by the 2020 C-TIRADS (AUROC 0.933) and the 2015 ATA guidelines (AUROC 0.928). The ATA guidelines had the highest specificity (93.38%), accuracy (92.10%) and positive predictive value (PPV) (80.56%) among the three guidelines. There were no significant differences in the sensitivity and negative predictive value (NPV) among the three guidelines. The sensitivity, specificity, PPV, NPV and accuracy of the FNA recommendations based on the C-TIRADS were 84.25%, 58.76%, 38.92%, 92.28% and 64.82%, respectively, which were higher than those of the ACR-TIRADS (57.53%, 42.94%, 23.93%, 76.43% and 46.42%, respectively) and the ATA guidelines (62.67%, 13.25%, 18.39%, 53.22% and 25.00%, respectively). Compared with the ACR-TIRADS (76.07%) and the ATA guidelines (81.61%), the C-TIRADS showed advantages in the unnecessary FNA rate (61.08%), especially in nodules larger than 20 mm.

CONCLUSIONS

The 2020 C-TIRADS, the 2017 ACR-TIRADS and the 2015 ATA guidelines can effectively predict the malignancy risk of thyroid nodules. Compared with the 2017 ACR-TIRADS and the 2015 ATA guidelines, the 2020 C-TIRADS may offer a meaningful reduction in FNA recommendations with the highest efficacy in distinguishing thyroid carcinoma.

摘要

背景

比较中华医学会超声医学分会浅表器官及血管超声学组2020年制定的指南[2020年中国甲状腺影像报告和数据系统(C-TIRADS)]、美国放射学会2017年(2017 ACR-TIRADS)和美国甲状腺协会2015年(2015 ATA指南)在判定甲状腺结节恶性程度方面的诊断性能以及细针穿刺抽吸(FNA)建议。

方法

2021年1月至2021年12月,纳入汕头市中心医院1228例术前3个月内有明确术后组织病理学检查及超声(US)检查结果的甲状腺结节患者进行研究。于2022年收集数据。研究对象为连续纳入的病例系列。回顾性分析结节的临床及超声特征,并根据2020 C-TIRADS、2017 ACR-TIRADS和2015 ATA指南进行分类。计算三种指南的诊断性能及不必要FNA率。

结果

2017 ACR-TIRADS诊断性能最高[受试者操作特征曲线下面积(AUROC)为0.938],其次是2020 C-TIRADS(AUROC为0.933)和2015 ATA指南(AUROC为0.928)。ATA指南在三种指南中特异性最高(93.38%)、准确性最高(92.10%)和阳性预测值(PPV)最高(80.56%)。三种指南的敏感性和阴性预测值(NPV)无显著差异。基于C-TIRADS的FNA建议的敏感性、特异性、PPV、NPV和准确性分别为84.25%、58.76%、38.93%、92.28%和64.82%,高于ACR-TIRADS(分别为57.53%、42.94%、23.93%、76.43%和46.42%)和ATA指南(分别为62.67%、13.25%、18.39%、53.22%和25.00%)。与ACR-TIRADS(76.07%)和ATA指南(81.61%)相比,C-TIRADS在不必要FNA率方面具有优势(61.08%),尤其是在直径大于20 mm的结节中。

结论

2020 C-TIRADS、2017 ACR-TIRADS和2015 ATA指南均可有效预测甲状腺结节的恶性风险。与2017 ACR-TIRADS和2015 ATA指南相比,2020 C-TIRADS可能在减少FNA建议方面具有意义,且在鉴别甲状腺癌方面具有最高的效能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3d4/10347339/17771a03c3ea/qims-13-07-4514-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3d4/10347339/23594fd24a00/qims-13-07-4514-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3d4/10347339/17771a03c3ea/qims-13-07-4514-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3d4/10347339/23594fd24a00/qims-13-07-4514-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3d4/10347339/17771a03c3ea/qims-13-07-4514-f2.jpg

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