ArticleFrontiers in endocrinology2025
Development and validation of a novel nomogram for predicting lateral lymph node metastasis in medullary thyroid carcinoma.
Article in Frontiers in endocrinology, 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.
- Beyond Tumor Diameter: Exploratory Cohort-Derived Calcitonin Secretory Categories and Invasive Pathology in Medullary Thyroid Carcinoma.Current oncology (Toronto, Ont.) · 2026Article
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Abstract
Background: Medullary thyroid carcinoma (MTC) frequently presents with lateral lymph node metastasis (LLNM), a critical determinant of postoperative recurrence. While surgery remains the cornerstone of MTC treatment, the indications for lateral lymph node dissection (LLND) remain contentious. This study aimed to develop and validate a predictive nomogram for assessing LLNM risk in patients with MTC. Methods: We retrospectively analyzed 87 treatment-naïve MTC patients who underwent primary surgical resection at our institution. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for LLNM. A nomogram was constructed and internally validated, with its clinical utility evaluated through discrimination, calibration, and decision curve analyses. Results: Univariate analysis identified multifocality, intrathyroidal lymphovascular invasion (IT-LVI), extrathyroidal extension (ETE), central lymph node metastasis (CLNM), maximum tumor diameter (MTD), serum calcitonin (Ctn), and carcinoembryonic antigen (CEA) as significantly associated with LLNM (P < 0.05). Multivariate logistic regression analysis revealed ETE (OR = 14.37; 95% CI: 2.11-100.24; P = 0.007), CLNM (OR = 4.97; 95% CI: 1.06-23.26; P = 0.042), and natural log-transformed Ctn (Ln_Ctn) (OR = 2.72; 95% CI: 1.49-4.99; P<0.001) as independent predictors. The resulting nomogram demonstrated excellent discriminative ability (AUC = 0.941), good calibration, and strong clinical utility. Conclusion: We developed a novel nomogram incorporating ETE, CLNM, and Ln_Ctn to accurately estimate LLNM probability in MTC patients. This predictive model significantly improves risk stratification, provides valuable guidance for surgical decision-making regarding LLND, and supports personalized surgical planning.
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