Prediction Model of Pathologic Central Lymph Node Negativity in cN0 Papillary Thyroid Carcinoma.

Background: Most patients with papillary thyroid carcinoma (PTC) have an excellent prognosis. Although central lymph node invasion is frequent, management central lymph node dissection (CLND) remains controversial. The present study retrospectively investigated independent predictors of pathologic central lymph node negativity (pCLN-) and established a prediction model for pCLN- in clinical lymph node negativity (cN0) PTC.

Methods: A total of 2,687 patients underwent thyroid surgery for cN0 PTC from 2013 to 2018 at the First Affiliated Hospital of Chongqing Medical University, and lobectomy plus ipsilateral CLND was the basic surgical extent. Clinicopathological characteristics were reviewed and analyzed. Univariate and multivariate analyses were performed to identify factors related to pCLN-. A prediction model was established based on the results of multivariate analyses.

Results: The pCLN- rate was 51.5% (1,383/2,687). Multivariate analysis revealed that sex, age, thyroid stimulating hormone (TSH), size, location, laterality, unifocality and extrathyroidal extension negativity (ETE-) were independent predictors of pCLN-. The nomogram showed good discriminative ability (C-index: 0.784 and 0.787 in derivation and validation groups, respectively) and was well calibrated. We quantified the clinical usefulness of the nomogram by decision curve analysis. The median length of follow-up was 30 (range 12- 83) months, and 190 cases were lost, with a follow-up rate of 92.9% (2,497/2,687). Of the 2,687 patients included, 21 (0.8%) experienced recurrence.

Conclusion: This nomogram, which integrates available preoperative clinicopathological features and intraoperative frozen biopsy outcomes, is a reliable tool with high accuracy to predict pCLN- in cN0 PTC.