Risk stratification of indeterminate thyroid fine-needle aspiration biopsy specimens based on mutation analysis

Filippo Filicori, Xavier M. Keutgen, Daniel Buitrago, Hasan Aldailami, Michael Crowley, Thomas J. Fahey, Rasa Zarnegar

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


Background: Mutation analysis is potentially a powerful tool to enhance the diagnostic accuracy of thyroid fine-needle aspiration (FNA) biopsy specimens. However, some clinicians may rely on a negative mutation panel to exclude malignancy. We aimed to determine the malignancy rate in indeterminate lesions with negative mutation analysis. Methods: A literature review established a mutation analysis model using the prevalence of BRAF, RET, RAS, and PAX8/peroxisome proliferator-activated receptor-γ mutations in indeterminate lesions. This model was applied retrospectively to a study cohort of 466 consecutive indeterminate lesions that underwent hemi- or total thyroidectomy for definitive diagnosis, to evaluate its accuracy for identifying malignancy. Results: Of 466 indeterminate lesions in the study, 30% (139) were malignant. These included 66 cases of papillary thyroid cancer, 45 cases of follicular variant of papillary thyroid cancer, 18 cases of follicular thyroid cancer, and 10 others. The risk of malignancy was 42% when cytologic atypia was present vs 17% without. The mutation analysis model would correctly identify only 48 of 139 (34%) of malignant indeterminate lesions. Therefore, when mutation analysis is negative, the overall risk of malignancy would be 23%. When atypia is present, the risk of malignancy would be 31% vs 13% in lesions without. Conclusion: Indeterminate lesions with a negative mutation analysis still carry a significant risk of malignancy, especially in the presence of atypia, requiring surgery for definitive diagnosis.

Original languageEnglish (US)
Pages (from-to)1085-1091
Number of pages7
Issue number6
StatePublished - Dec 2011
Externally publishedYes

ASJC Scopus subject areas

  • Surgery


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