The Combined Use of Fine-Needle Aspiration (FNA) and BRAF V600E Gene Testing: Can it Increase the Definitive Diagnosis Rate of Nodules Categorized as Bethesda III for Papillary Thyroid Carcinoma?

ABSTRACT

OBJECTIVE: This study aimed to analyze the malignant probability of thyroid nodules diagnosed as indeterminate cytology, including atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS), and investigate the diagnostic value of combining BRAF V600E gene testing within this classification. METHODS: We conducted a retrospective analysis of 126 patients who underwent fine-needle aspiration (FNA) examination of thyroid nodules and subsequent surgical treatment at Beijing Haidian Hospital between October 2021 and November 2022. Among them, there were 22 male and 104 female patients, aged between 18 and 75 years old. Surgical pathology results were considered the gold standard for diagnosing the nature of thyroid nodules, evaluating the malignant incidence of cytological results categorized as AUS/FLUS. Fisher's exact test and diagnostic test evaluation methods were used to analyze the discriminatory diagnostic efficacy of preoperative FNA combined with BRAF V600E gene testing for papillary thyroid carcinoma (PTC). Statistical analysis was performed using SPSS 22.0 software. RESULTS: In PTC patients, the BRAF V600E gene mutation rate was 87.93% (102/116). Within the category of FNA results as AUS/FLUS, the proportion of PTC was 60.00% (15/25). The specificity, sensitivity, positive predictive value, and negative predictive value of the BRAF V600E gene mutation in diagnosing PTC within the AUS/FLUS category were 10/10, 6/15, 6/6, and 10/19, respectively. The BRAF V600E gene mutation significantly increased the detection rate of PTC in patients classified under this cytology (P = 0.028, <0.05). CONCLUSION: Preoperative FNA combined with BRAF V600E gene mutation testing significantly enhances the malignant detection rate of thyroid nodules diagnosed cytologically as AUS/FLUS. This combined approach provides a potent tool to improve diagnostic accuracy in this indeterminate classification.