Clinical features combined with ultrasound characteristics to predict TERT promoter mutations in papillary thyroid carcinoma: a single-center study over the past 5 years.

Abstract

Telomerase reverse transcriptase (TERT) has been reported in papillary thyroid carcinoma (PTC). This study aimed to investigate the correlation of TERT promoter mutations with clinical and ultrasound (US) features in PTC and to develop a model to predict TERT promoter mutations. Preoperative US images, postoperative pathological features, and TERT promoter mutation information were evaluated in 365 PTC patients confirmed by surgery. Univariate and multivariate factor analyses were performed to identify risk factors for TERT promoter mutations. A predictive model was established to assess the clinical predictive value. Of the 365 patients with PTC (498 nodules), the number of those with TERT promoter mutations was 67 cases (75 nodules), and the number of those without mutations was 298 cases (423 nodules). The median age was 40 years in the wild-type group and 60 years in the mutant group. Male patients made up 35.82% of the mutant group and 22.82% of the wild-type group. Multivariate analysis revealed that the independent risk factors associated with the occurrence of TERT promoter mutation in PTC were as follows: older age (odds ratio (OR) = 1.07; p = 0.002), maximum diameter of ≥ 10 mm (OR = 3.94; p < 0.0001), unilateral (OR = 4.15; p < 0.0001), multifocal (OR = 7.69; p < 0.0001), adjacent to the thyroid capsule (OR = 1.94; p = 0.044), and accompanied by other benign nodules (OR = 1.94, p = 0.039). A predictive model was established, and the area under the curve (AUC) of the receiver operating characteristic was 0.839. TERT promoter mutations were associated with high-risk US and clinical features compared with the wild-type group. TERT promoter mutations were associated with older ages. They were also found to be multifocal, with a maximum diameter of ≥ 10 mm, unilateral, adjacent to the thyroid capsule, and accompanied by other benign nodules. The predictive model was of high diagnostic value.