title: Risk stratification of indeterminate thyroid fine-needle aspiration biopsy specimens based on mutation analysis.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Division of Endocrine and Minimally Invasive Surgery, Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA. fif2003@med.cornell.edu
authors.forename: Filippo
authors.initials: F
authors.lastname: Filicori
authors.forename: Xavier M
authors.initials: XM
authors.lastname: Keutgen
authors.forename: Daniel
authors.initials: D
authors.lastname: Buitrago
authors.forename: Hasan
authors.initials: H
authors.lastname: AlDailami
authors.forename: Michael
authors.initials: M
authors.lastname: Crowley
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Fahey
authors.forename: Rasa
authors.initials: R
authors.lastname: Zarnegar
mesh_terms: D018263:Adenocarcinoma, Follicular; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000235:genetics; D044963:Biopsy, Fine-Needle; D002277:Carcinoma; D002291:Carcinoma, Papillary; D015331:Cohort Studies; D004252:DNA Mutational Analysis; D005260:Female; D011905:Genes, ras; D005820:Genetic Testing; D006801:Humans; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D000072636:PAX8 Transcription Factor; D051761:Paired Box Transcription Factors / Q000235:genetics; D048493:Proto-Oncogene Proteins B-raf / Q000235:genetics; D051096:Proto-Oncogene Proteins c-ret / Q000235:genetics; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods; D012680:Sensitivity and Specificity; D000077273:Thyroid Cancer, Papillary; D013961:Thyroid Gland / Q000473:pathology / Q000601:surgery; D013964:Thyroid Neoplasms / Q000235:genetics* / Q000473:pathology / Q000601:surgery; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor; D000072636:PAX8 Transcription Factor; C083325:PAX8 protein, human; D051761:Paired Box Transcription Factors; D051096:Proto-Oncogene Proteins c-ret; C099282:RET protein, human; C482119:BRAF protein, human; D048493:Proto-Oncogene Proteins B-raf