title: Diagnostic accuracy of Thyroid Imaging Reporting and Data System in the prediction of malignancy in nodules with atypia and follicular lesion of undetermined significance cytologies.
abstract: OBJECTIVE
  Thyroid Imaging Reporting and Data System (TIRADS) is a simple and reliable reporting system for the prediction of malignancy. We aimed to determine the role of TIRADS in the prediction of malignancy in subcategories of Bethesda Category III, atypia of undetermined significance (AUS) and follicular lesion of undetermined significance (FLUS).
  
  
  METHODS
  A total of 461 nodules with AUS cytology in 450 patients and 179 nodules with FLUS cytology in 168 patients were included. Ultrasonography (US) features and postoperative histopathology results were documented. Every suspicious US feature was scored as 1 and 0 according to the presence or not, respectively. TIRADS category of each nodule was determined.
  
  
  RESULTS
  In AUS subcategory, histopathologically malignant nodules had significantly different TIRADS categories compared to benign nodules (P = 0·001), but this was not the case in FLUS subcategory (P = 0·121). In AUS group, malignant nodules had significantly higher prevalance of microcalcification, hypoechogenicity and anteroposterior/transverse ratio than benign ones (P < 0·001, P < 0·001 and P = 0·003, respectively) and TIRADS categories of 4c and 5 were more frequent in malignant nodules (P < 0·05). Microcalcification, hypoechogenicity and TIRADS were found to be associated with malignancy in multivariate logistic regression analysis in this subcategory. TIRADS category ≥4c was associated with malignancy (AUC ± SE: 0·584 ± 0·028). In FLUS subcategory, there was no significant difference between histopathologically malignant and benign nodules with respect to suspicious US features (P > 0·05, all).
  
  
  CONCLUSIONS
  TIRADS seems to be useful in predicting malignancy and planning further management in the AUS subcategory, but not quite so in the FLUS subcategory.
authors.affiliation: Department of Endocrinology and Metabolism, Ataturk Education and Research Hospital, Ankara, Turkey.
authors.forename: Husniye
authors.initials: H
authors.lastname: Baser
authors.affiliation: Department of Endocrinology and Metabolism, Faculty of Medicine, Yildirim Beyazit University, Ankara, Turkey.
authors.forename: Bekir
authors.initials: B
authors.lastname: Cakir
authors.affiliation: Department of Endocrinology and Metabolism, Faculty of Medicine, Yildirim Beyazit University, Ankara, Turkey.
authors.forename: Oya
authors.initials: O
authors.lastname: Topaloglu
authors.affiliation: Department of Biostatistics, Faculty of Medicine, Yildirim Beyazit University, Ankara, Turkey.
authors.forename: Afra
authors.initials: A
authors.lastname: Alkan
authors.affiliation: Department of Endocrinology and Metabolism, Faculty of Medicine, Yildirim Beyazit University, Ankara, Turkey.
authors.forename: Sefika Burcak
authors.initials: SB
authors.lastname: Polat
authors.affiliation: Department of Pathology, Faculty of Medicine, Yildirim Beyazit University, Ankara, Turkey.
authors.forename: Hayriye Tatli
authors.initials: HT
authors.lastname: Dogan
authors.affiliation: Department of General Surgery, Ataturk Education and Research Hospital, Ankara, Turkey.
authors.forename: Mustafa Omer
authors.initials: MO
authors.lastname: Yazicioğlu
authors.affiliation: Department of Endocrinology and Metabolism, Faculty of Medicine, Yildirim Beyazit University, Ankara, Turkey.
authors.forename: Cevdet
authors.initials: C
authors.lastname: Aydin
authors.affiliation: Department of Endocrinology and Metabolism, Faculty of Medicine, Yildirim Beyazit University, Ankara, Turkey.
authors.forename: Reyhan
authors.initials: R
authors.lastname: Ersoy
mesh_terms: D018263:Adenocarcinoma, Follicular / Q000000981:diagnostic imaging; D000328:Adult; D003581:Cytodiagnosis; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D013964:Thyroid Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000473:pathology; D016606:Thyroid Nodule / Q000145:classification / Q000000981:diagnostic imaging / Q000473:pathology*; D014463:Ultrasonography