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Published on: April 18, 2025
Prognostic impact of N staging in 715 medullary thyroid cancer patients: proposal for a revised staging system
Andreas Machens1, Henning Dralle
1Department of General, Visceral and Vascular Surgery, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany. andreasmachens@aol.com
Objective:
This institutional study aimed at quantifying a medullary thyroid cancer (MTC) patient's risk of lung, liver, or bone metastasis.
Background:
Without quantitative information regarding risk factors for lung, liver, and bone metastasis, risk stratification is liable to be haphazard, resulting in poor cost-effectiveness of screening programs.
Methods:
Included in this study were 715 patients with MTC for whom histopathologic information was available for each lymph node removed.
Results:
Seventy-two patients (10.1%) were diagnosed with lung metastasis, 58 patients (8.1%) with liver metastasis, and 34 patients (4.8%) with bone metastasis. Multivariate analyses were limited to patients revealing no more than 1 type of distant metastasis to avoid confounding by other distant metastasis. Extrathyroidal extension and 1 to 10 involved nodes indicated a small risk of lung metastasis [3%-4%; odds ratio (OR) 3-4], tumors greater than 40 mm and 11 to 20 involved nodes implied an intermediate risk (13%; OR 6), and more than 20 involved nodes entailed a high risk (26%-30%; OR 14-16). In the multivariate logistic regressions on liver and bone metastasis, in which the number of involved nodes was omitted on statistic grounds, extrathyroidal extension signified a strong risk of liver metastasis (19%, OR 23), whereas no clinical-pathologic variables were significantly associated with bone metastasis. Cumulative rates of lung, liver, and bone metastasis, plotted against the number of lymph node metastases, were similar.
Discussion:
N categories encompassing 1 to 10 (N1), 11 to 20 (N2), and more than 20 (N3) lymph node metastases are important prognostic classifiers that should be incorporated into MTC staging systems for better risk stratification.

