Development and validation of a clinical prediction model to diagnose Warthin tumor based on non-contrast computed tomography features and clinical characteristics

ElsevierVolume 47, Issue 1, January–February 2026, 104767American Journal of OtolaryngologyAuthor links open overlay panel, , , Highlights•

We developed a nomogram using clinical and non-contrast CT features that accurately identifies Warthin tumor in the parotid.

External validation further confirmed the model's robustness, indicating strong generalizability and clinical potential.

The five independent predictors, all readily obtainable, facilitate clinical application.

AbstractObjectives

This study aims to develop and validate a clinical prediction model that integrates clinical features with non-contrast CT imaging characteristics to identify Warthin tumor (WT) in the parotid gland.

Methods

A total of 289 patients who underwent surgical resection of parotid tumors at the Affiliated hospital of Jiangnan University from June 2018 to December 2024 were consecutively and randomly divided into training (n = 202) and validation (n = 87) cohorts at a 7:3 ratio. Demographic and non-contrast CT imaging variables were collected. Logistic regression identified predictors, and a nomogram was constructed. To further validate the model, an independent dataset comprising 84 patients from a second hospital was used. The model's performance was evaluated through receiver operating characteristic (ROC) curves, calibration curves, the Hosmer-Lemeshow test, and decision curve analysis (DCA).

Results

Age, smoking history, tumor distribution, earlobe position, and longitudinal-to-transverse ratio (LTR) were identified as independent predictors for differentiating WT from other parotid gland tumors. The nomogram showed high diagnostic accuracy, with the area under the curve (AUC) values of 0.942 (training), 0.937 (validation), and 0.953 (external validation). Calibration curves indicated good agreement with ideal predictions, supported by the Hosmer-Lemeshow test (P > 0.05). DCA further demonstrated the superior clinical utility of the nomogram model.

Conclusion

The nomogram model incorporating clinical and non-contrast CT features demonstrates high accuracy for differentiating WT from other parotid gland tumors in clinical practice.

Keywords

Warthin tumor

Clinical features

Non-contrast CT

Prediction model

Parotid gland

© 2025 The Authors. Published by Elsevier Inc.

Comments (0)

No login
gif