Journal of stomatology, oral and maxillofacial surgery · 2026
A web-based dynamic nomogram for preoperative identification of Warthin tumor among parotid tumors: Development and external validation.
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Dong Jianghui, Zhao Hengshuai, Shao Xiannian, Ma Keyi, Teng Xuetan, Zhou Hui, Wang Liping
Аннотация
BACKGROUND: Preoperative identification of Warthin tumor (WT) can inform surgical planning and patient counseling. This study aimed to develop and externally validate a simple clinical prediction model based on routinely available preoperative variables.
METHODS: This two-center retrospective study included 230 patients in the development cohort and 245 in the external validation cohort. Nine routinely available preoperative variables were assessed using LASSO-penalized logistic regression with stratified five-fold cross-validation. Model performance was evaluated using discrimination, calibration, overall prediction error, 1000-resample bootstrap internal validation, decision curve analysis, and clinical impact curves.
RESULTS: Among 475 patients, 81 (17.1%) had histopathologically confirmed WT. The final model included age (OR = 1.037, 95% CI: 1.008-1.067), male sex (OR = 3.828, 95% CI: 1.146-12.783), and smoking history (OR = 3.591, 95% CI: 1.550-8.316). The AUC was 0.791 (95% CI: 0.721-0.862) in the development cohort and 0.868 (95% CI: 0.816-0.919) in external validation. After bootstrap correction, the AUC was 0.785, the calibration intercept was -0.048, the calibration slope was 0.942, the Brier score was 0.129, and Emax was 0.088. In the external cohort, the calibration intercept and slope were 0.379 and 1.503, respectively; the Brier score was 0.101 and Emax was 0.139. Decision curve analysis suggested potential net benefit across selected threshold ranges.
CONCLUSIONS: A model based on age, sex, and smoking history showed useful preoperative discrimination between WT and other parotid tumors. The web-based dynamic nomogram may support initial assessment and patient counseling, although further prospective and geographically diverse validation is needed.
METHODS: This two-center retrospective study included 230 patients in the development cohort and 245 in the external validation cohort. Nine routinely available preoperative variables were assessed using LASSO-penalized logistic regression with stratified five-fold cross-validation. Model performance was evaluated using discrimination, calibration, overall prediction error, 1000-resample bootstrap internal validation, decision curve analysis, and clinical impact curves.
RESULTS: Among 475 patients, 81 (17.1%) had histopathologically confirmed WT. The final model included age (OR = 1.037, 95% CI: 1.008-1.067), male sex (OR = 3.828, 95% CI: 1.146-12.783), and smoking history (OR = 3.591, 95% CI: 1.550-8.316). The AUC was 0.791 (95% CI: 0.721-0.862) in the development cohort and 0.868 (95% CI: 0.816-0.919) in external validation. After bootstrap correction, the AUC was 0.785, the calibration intercept was -0.048, the calibration slope was 0.942, the Brier score was 0.129, and Emax was 0.088. In the external cohort, the calibration intercept and slope were 0.379 and 1.503, respectively; the Brier score was 0.101 and Emax was 0.139. Decision curve analysis suggested potential net benefit across selected threshold ranges.
CONCLUSIONS: A model based on age, sex, and smoking history showed useful preoperative discrimination between WT and other parotid tumors. The web-based dynamic nomogram may support initial assessment and patient counseling, although further prospective and geographically diverse validation is needed.