Literature DB >> 31740569

A Multidisciplinary Head-to-Head Comparison of American College of Radiology Thyroid Imaging and Reporting Data System and American Thyroid Association Ultrasound Risk Stratification Systems.

Bernice L Huang1, Susana A Ebner2, Jasnit S Makkar3, Stuart Bentley-Hibbert3, Robert J McConnell2,4, James A Lee4,5, Elizabeth M Hecht3, Jennifer H Kuo4,5.   

Abstract

BACKGROUND: Ultrasound plays a critical role in evaluating thyroid nodules. We compared the performance of the two most popular ultrasound malignancy risk stratification systems, the 2015 American Thyroid Association (ATA) guidelines and the American College of Radiology Thyroid Imaging and Reporting Data System (ACR TI-RADS).
MATERIALS AND METHODS: We retrospectively identified 250 thyroid nodules that were surgically removed from 137 patients. Their ultrasound images were independently rated using both ATA and ACR TI-RADS by six raters with expertise in ultrasound interpretation. For each system, we generated a receiver operating characteristic curve and calculated the area under the curve (AUC).
RESULTS: Sixty-five (26%) nodules were malignant. There was "fair agreement" among raters for both ATA and ACR TI-RADS. Our observed malignancy risks for ATA and ACR TI-RADS categories were similar to expected risk thresholds with a few notable exceptions including the intermediate ATA risk category and the three highest risk categories for ACR TI-RADS. Biopsy of 226 of the 250 nodules would be indicated by ATA guidelines based on nodule size and mean ATA rating. One hundred forty-six nodules would be biopsied based on ACR TI-RADS. The sensitivity, specificity, and negative and positive predictive values were 92%, 10%, 79%, and 27%, respectively, for ATA and 74%, 47%, 84%, and 33%, respectively, for ACR TI-RADS. The AUC for ATA was 0.734 and for ACR TI-RADS was 0.718.
CONCLUSION: Although both systems demonstrated good diagnostic performance, ATA guidelines resulted in a greater number of thyroid biopsies and exhibited more consistent malignancy risk prediction for higher risk categories. IMPLICATIONS FOR PRACTICE: With the rising incidence of thyroid nodules, the need for accurate detection of malignancy is important to avoid the overtreatment of benign nodules. Ultrasonography is one of the key tools for the evaluation of thyroid nodules, although the use of many different ultrasound risk stratification systems is a hindrance to clinical collaboration in everyday practice and the comparison of data in research. The first step toward the development of a universal thyroid nodule ultrasound malignancy risk stratification system is to better understand the strengths and weaknesses of the current systems in use. © AlphaMed Press 2019.

Entities:  

Keywords:  Interobserver variability; Thyroid cancer; Thyroid nodule; Ultrasonography

Mesh:

Year:  2019        PMID: 31740569      PMCID: PMC7216459          DOI: 10.1634/theoncologist.2019-0362

Source DB:  PubMed          Journal:  Oncologist        ISSN: 1083-7159


  28 in total

1.  Gross and microscopic findings in clinically normal thyroid glands.

Authors:  J D MORTENSEN; L B WOOLNER; W A BENNETT
Journal:  J Clin Endocrinol Metab       Date:  1955-10       Impact factor: 5.958

2.  AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS, AMERICAN COLLEGE OF ENDOCRINOLOGY, AND ASSOCIAZIONE MEDICI ENDOCRINOLOGI MEDICAL GUIDELINES FOR CLINICAL PRACTICE FOR THE DIAGNOSIS AND MANAGEMENT OF THYROID NODULES--2016 UPDATE.

Authors:  Hossein Gharib; Enrico Papini; Jeffrey R Garber; Daniel S Duick; R Mack Harrell; Laszlo Hegedüs; Ralf Paschke; Roberto Valcavi; Paolo Vitti
Journal:  Endocr Pract       Date:  2016-05       Impact factor: 3.443

3.  Diagnostic performance of ATA, BTA and TIRADS sonographic patterns in the prediction of malignancy in histologically proven thyroid nodules.

Authors:  Chiaw Ling Chng; Hong Chang Tan; Chow Wei Too; Wei Ying Lim; Priscilla Pei Sze Chiam; Ling Zhu; Nivedita Vikas Nadkarni; Adoree Yi Ying Lim
Journal:  Singapore Med J       Date:  2018-05-18       Impact factor: 1.858

4.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

Authors:  J A Hanley; B J McNeil
Journal:  Radiology       Date:  1983-09       Impact factor: 11.105

5.  Validation of American Thyroid Association Ultrasound Risk Assessment of Thyroid Nodules Selected for Ultrasound Fine-Needle Aspiration.

Authors:  Alice L Tang; Mercedes Falciglia; Huaitao Yang; Jonathan R Mark; David L Steward
Journal:  Thyroid       Date:  2017-07-18       Impact factor: 6.568

6.  Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk.

Authors:  Jin Young Kwak; Kyung Hwa Han; Jung Hyun Yoon; Hee Jung Moon; Eun Ju Son; So Hee Park; Hyun Kyung Jung; Ji Soo Choi; Bo Mi Kim; Eun-Kyung Kim
Journal:  Radiology       Date:  2011-07-19       Impact factor: 11.105

7.  Malignancy Risk Stratification of Thyroid Nodules: Comparison between the Thyroid Imaging Reporting and Data System and the 2014 American Thyroid Association Management Guidelines.

Authors:  Jung Hyun Yoon; Hye Sun Lee; Eun-Kyung Kim; Hee Jung Moon; Jin Young Kwak
Journal:  Radiology       Date:  2015-09-08       Impact factor: 11.105

Review 8.  The accuracy of thyroid nodule ultrasound to predict thyroid cancer: systematic review and meta-analysis.

Authors:  Juan P Brito; Michael R Gionfriddo; Alaa Al Nofal; Kasey R Boehmer; Aaron L Leppin; Carl Reading; Matthew Callstrom; Tarig A Elraiyah; Larry J Prokop; Marius N Stan; M Hassan Murad; John C Morris; Victor M Montori
Journal:  J Clin Endocrinol Metab       Date:  2013-11-25       Impact factor: 5.958

9.  Risk of thyroid cancer based on thyroid ultrasound imaging characteristics: results of a population-based study.

Authors:  Rebecca Smith-Bindman; Paulette Lebda; Vickie A Feldstein; Dorra Sellami; Ruth B Goldstein; Natasha Brasic; Chengshi Jin; John Kornak
Journal:  JAMA Intern Med       Date:  2013-10-28       Impact factor: 21.873

10.  Guidelines for the management of thyroid cancer.

Authors:  Petros Perros; Kristien Boelaert; Steve Colley; Carol Evans; Rhordi M Evans; Georgina Gerrard Ba; Jackie Gilbert; Barney Harrison; Sarah J Johnson; Thomas E Giles; Laura Moss; Val Lewington; Kate Newbold; Judith Taylor; Rajesh V Thakker; John Watkinson; Graham R Williams
Journal:  Clin Endocrinol (Oxf)       Date:  2014-07       Impact factor: 3.478

View more
  7 in total

1.  Assessment of diagnostic capacity and decision-making based on the 2015 American Thyroid Association ultrasound classification system.

Authors:  Luis-Mauricio Hurtado-Lopez; Alfredo Carrillo-Muñoz; Felipe-Rafael Zaldivar-Ramirez; Erich Otto Paul Basurto-Kuba; Blanca-Estela Monroy-Lozano
Journal:  World J Methodol       Date:  2022-05-20

2.  Approach to the Patient With Thyrotoxicosis Using Telemedicine.

Authors:  Michelle L Griffith; Lindsay A Bischoff; Howard B A Baum
Journal:  J Clin Endocrinol Metab       Date:  2020-08-01       Impact factor: 5.958

3.  Comparison of Diagnostic Performance of Five Different Ultrasound TI-RADS Classification Guidelines for Thyroid Nodules.

Authors:  Ruoning Yang; Xiuhe Zou; Hao Zeng; Yunuo Zhao; Xuelei Ma
Journal:  Front Oncol       Date:  2020-11-16       Impact factor: 6.244

4.  Comparison of Different Ultrasound Classification Systems of Thyroid Nodules for Identifying Malignant Potential: A Cross-sectional Study.

Authors:  Hua Chen; Jun Ye; Jianming Song; Yuguang You; Weihua Chen; Yanna Liu
Journal:  Clinics (Sao Paulo)       Date:  2021-01-20       Impact factor: 2.365

5.  The Diagnostic Efficacy of the American College of Radiology (ACR) Thyroid Imaging Report and Data System (TI-RADS) and the American Thyroid Association (ATA) Risk Stratification Systems for Thyroid Nodules.

Authors:  Fei Chen; Yungang Sun; Guanqi Chen; Yuqian Luo; Guifang Xue; Kongmei Luo; Haoyuan Ma; Jiaxin Yao; Zhangtian Zhu; Guanbin Li; Qiang Li
Journal:  Comput Math Methods Med       Date:  2022-01-15       Impact factor: 2.238

6.  External validation of AIBx, an artificial intelligence model for risk stratification, in thyroid nodules.

Authors:  Kristine Z Swan; Johnson Thomas; Viveque E Nielsen; Marie Louise Jespersen; Steen J Bonnema
Journal:  Eur Thyroid J       Date:  2022-03-08

7.  Radiomics Nomogram for Identifying Sub-1 cm Benign and Malignant Thyroid Lesions.

Authors:  Xinxin Wu; Jingjing Li; Yakui Mou; Yao Yao; Jingjing Cui; Ning Mao; Xicheng Song
Journal:  Front Oncol       Date:  2021-06-07       Impact factor: 6.244

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.