Prospective application of a prediction model for lateral lymph node metastasis in papillary thyroid cancer patients with central lymph node metastasis.

Objective: This study aimed to develop and apply a prediction model to estimate the probability of lateral lymph node metastasis (LLNM) in patients with cN0 unilateral papillary thyroid carcinoma (PTC) with central lymph node metastasis (CLNM). Setting: All study data were collected from a single tertiary hospital. Methods: Univariable and multivariable logistic regression analyses were used to explore independent predictors of LLNM in the derivation and internal validation cohorts, which were used to construct and validate a nomogram. Another 96 patients were included prospectively to evaluate the efficacy of this nomogram. Results: Maximum tumor diameter greater than 1.0 cm (OR, 2.712; 95% CI, 1.412-5.210), multifocality (OR, 2.758; 95% CI, 1.120-6.789), the number of CLNM ≥3 (OR, 2.579; 95% CI, 1.315-5.789), CLNM ratio ≥0.297 (OR, 2.905; 95% CI, 1.396-6.043), and tumors located in the upper portion (OR 2.846, 95% CI 1.151-7.039) were independent predictors associated with LLNM. The prediction model showed excellent discrimination with an AUC of 0.731 (95% CI, 0.635-0.827). Novel risk stratification for LLNM was constructed based on this nomogram. In the prospective cohort, we stratified these patients into three risk subgroups: low-, moderate-, and high-risk subgroups and we found that the probability of LLNM was positively correlated with the total points from the nomogram. Conclusion: This nomogram was applied in prospective clinical practice and distinguished PTC patients with a genuinely high risk of LLNM. Surgeons can use our nomogram to tailor the surgical plan and to credibly determine further postoperative therapy.