Development and validation of a diagnostic model for predicting cervical lymph node metastasis in laryngeal and hypopharyngeal carcinoma.

Objectives: The lymph node status is crucial for guiding the surgical approach for patients with laryngeal and hypopharyngeal carcinoma (LHC). Nonetheless, occult lymph node metastasis presents challenges to assessment and treatment planning. This study seeks to develop and validate a diagnostic model for evaluating cervical lymph node status in LHC patients. Materials and methods: This study retrospectively analyzed a total of 285 LHC patients who were treated at the Department of Otolaryngology Head and Neck Surgery, Daping Hospital, Army Medical University, from January 2015 to December 2020. Univariate and multivariate logistic regression analyses were employed to construct the predictive model. Discrimination and calibration were used to assess the predictive performance of the model. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the model, and validation was conducted using 10-fold cross-validation, Leave-One-Out Cross Validation, and bootstrap methods. Results: This study identified significant predictors of lymph node metastasis in LHC. A diagnostic predictive model was developed and visualized using a nomogram. The model demonstrated excellent discrimination, with a C-index of 0.887 (95% CI: 0.835-0.933). DCA analysis indicated its practical applicability, and multiple validation methods confirmed its fitting and generalization ability. Conclusion: This study successfully established and validated a diagnostic predictive model for cervical lymph node metastasis in LHC. The visualized nomogram provides a convenient tool for personalized prediction of cervical lymph node status in patients, particularly in the context of occult cervical lymph node metastasis, offering valuable guidance for clinical treatment decisions.