Improving the diagnosis of AUS/FLUS thyroid nodules using an algorithm with combination of BRAFV600E mutation analysis and ultrasound pattern-based risk stratification

Abstract

PURPOSE: To propose a diagnostic algorithm for improving the diagnosis of atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS) thyroid nodules. METHODS: This study retrospectively enrolled 77 consecutive patients with 81 AUS/FLUS nodules who underwent preoperative BRAFV600E mutation analysis. A new diagnostic algorithm was proposed that BRAFV600E mutation analysis for the Fine-needle aspiration cytology specimen was firstly carried out, in which positive BRAFV600E mutation indicated malignancy and classification of the nodules with negative BRAFV600E mutation was further performed based on ultrasound pattern-based risk stratification of American Thyroid Association Guidelines. The diagnostic performance of the new diagnostic algorithm was evaluated. RESULTS: The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the receiver operating characteristic curve (AUROC) of new diagnostic algorithm were 94.6%, 84.0%, 91.4%, 86.9%, 90.1%, and 0.893, respectively. The proposed diagnostic algorithm significantly increased the diagnostic performances (AUROC: 0.893 vs. 0.837 and 0.795), sensitivity (94.6% vs. 71.4% and 75.0%), and accuracy (90.1% vs. 79.0% and 77.8%) compared with BRAFV600E mutation analysis alone and ultrasound pattern-based risk stratification alone (all P < 0.05). CONCLUSION: The proposed diagnostic algorithm is helpful for improving the diagnosis of AUS/FLUS nodules, which might be as a routine approach.