ArticleInternational journal of general medicine2025
Ultrasound and Clinicopathological Characteristics of Papillary Thyroid Carcinoma Predict the Coexistence of TERT Promoter and BRAF
Article in International journal of general medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Preoperative Co-Mutation of BRAFCancer medicine · 2026Article
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10 authors.
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Abstract
Purpose: The coexistence of TERT promoter and BRAFV600E mutations is strongly linked to aggressive behavior and poor prognosis in papillary thyroid carcinoma (PTC). This study aimed to develop preoperative and postoperative predictive models for coexisting mutations based on ultrasound and clinicopathological characteristics to stratify prognostic risks and guide clinical decision-making. Methods: Retrospective analysis of the ultrasound and clinicopathological characteristics of 120 patients with a surgical pathology of PTC with TERT promoter and BRAF Results: Age (OR: 1.24; 95% CI 1.12-1.37, P<0.001), tumor size (OR: 5.51; 95% CI 2.26-13.46, P<0.001), lateral lymph node metastasis (OR: 7.36; 95% CI 1.48-36.48, P=0.015), and irregular/ill-defined margins (OR: 6.06; 95% CI 1.19-30.75, P=0.030) were independent predictors of coexisting mutations. The cutoff values for age and tumor size were 44.5 years and 1.55 cm, respectively. Two models incorporating the four independent predictors were established to predict coexisting mutations in the preoperative and postoperative periods, achieving AUCs of 0.95 and 0.96, respectively, with both models demonstrating good calibration ability and clinical practicability through calibration and decision curve analyses. Conclusion: The predictive models enable clinicians to identify high-risk patients with coexisting mutations both preoperatively and postoperatively, supporting the development of individualized treatment strategies and potentially improving patient outcomes. However, the study is limited by its single-center design, and further external validation is needed to confirm the generalizability of the model.
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