Literature DB >> 33635830

Clinical utility of sonographic features in indeterminate pediatric thyroid nodules.

Danielle M Richman1, Christine E Cherella2,3, Jessica R Smith2,3, Biren P Modi2,4, Benjamin Zendejas2,4, Mary C Frates1, Ari J Wassner2,3.   

Abstract

OBJECTIVE: Surgical resection is recommended for cytologically indeterminate pediatric thyroid nodules due to their intermediate malignancy risk. We evaluated the utility of ultrasound characteristics for refining malignancy risk to inform the management of these nodules.
DESIGN: Retrospective cohort study (2004-2019).
METHODS: We analyzed consecutive thyroid nodules with indeterminate fine-needle aspiration cytology (Bethesda category III, IV, or V) in pediatric patients (<19 years). We assessed the association of demographic and sonographic characteristics with malignancy risk among all indeterminate nodules and within each Bethesda category.
RESULTS: Eighty-seven cytologically indeterminate nodules were identified in 78 patients. Bethesda category was III in 56 nodules (64%), IV in 12 (14%), and V in 19 (22%). The malignancy rate was 46/87 (53%) overall, and 23/56 (41%), 8/12 (75%), and 15/19 (79%) in Bethesda III, IV, and V nodules, respectively. Malignancy rate was higher in solitary nodules (67% vs 37%, P = 0.004) and nodules with irregular margins (100% vs 44%, P < 0.001) or calcifications (82% vs 43%, P = 0.002). American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) risk level TR5 was associated with a higher rate of malignancy than lower TI-RADS risk levels (80% vs 42%, P = 0.002). Within individual Bethesda categories, TI-RADS risk level was not associated with malignancy. No sonographic feature had a negative predictive value for malignancy greater than 80%.
CONCLUSIONS: In pediatric thyroid nodules with indeterminate cytology, some sonographic features - including higher ACR TI-RADS risk level - are associated with malignancy, but these associations are unlikely to alter clinical management in most cases.

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Year:  2021        PMID: 33635830     DOI: 10.1530/EJE-20-1480

Source DB:  PubMed          Journal:  Eur J Endocrinol        ISSN: 0804-4643            Impact factor:   6.664


  1 in total

1.  Predicting Malignancy in Pediatric Thyroid Nodules: Early Experience With Machine Learning for Clinical Decision Support.

Authors:  Lebohang Radebe; Daniëlle C M van der Kaay; Jonathan D Wasserman; Anna Goldenberg
Journal:  J Clin Endocrinol Metab       Date:  2021-11-19       Impact factor: 5.958

  1 in total

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