Development and Validation of a Nomogram for Preoperative Prediction of Central Lymph Node Metastasis in Patients with cN0 Stage Papillary Thyroid Carcinoma and Tumor Capsule Contact

Background This study aimed to investigate factors associated with central lymph node metastasis (CLNM) in clinically lymph node-negative (cN0) papillary thyroid carcinoma (PTC) with tumor contact with the thyroid capsule. Additionally, we aimed to develop a predictive model using clinical data to enhance diagnostic and treatment strategies for this patient population. Methods This retrospective study reviewed 713 PTC (cN0) patients with tumor contact with the thyroid capsules from two institutions. Variables analyzed included sex, age, tumor characteristics (position, location, size, composition, echogenicity, aspect ratio, margin, and echogenic foci), capsular features (protrusion and interruption), distance from the tumor to the trachea, angle between the tumor and the trachea, and tumor contact with the tracheoesophageal groove (TEG). This group of patients was categorized into training and validation cohorts in a 7:3 ratio. A nomogram was developed using univariate and multivariate logistic regression analyses of the training cohort. Receiver operating characteristic curves were used to evaluate the diagnostic performance of the models. Internal validation was performed using a validation cohort. The Hosmer-Lemeshow test and decision curve analysis (DCA) were employed to assess the calibration and clinical utility of the model. Results Four variables associated with PTC were identified using multivariate logistic regression analysis and were used to establish a nomogram. The predictive model showed an area under the receiver operating characteristic curve (AUC) of 0.775 (95% confidence interval [CI] 0.733–0.818), and in internal validation, the AUC was 0.730 (95% CI 0.659–0.801). The calibration curve confirmed a good model fit, and the Hosmer-Lemeshow test indicated a high level of agreement between the predicted and observed values ( p  = 0.813). DCA revealed that applying the nomogram to predict the risk of CLNM would benefit patients with PTC (cN0) whose tumors were in contact with the capsule when the threshold probability ranged from 15–74%. Conclusion Four independent predictors of CLNM were identified: irregular or lobulated margins, echogenic foci, capsular interruption, and contact with the TEG. A nomogram model was established based on these four predictors, which could serve as a basis for central cervical lymph node dissection in patients with PTC (cN0).