Development and evaluation of a clinical-biochemical nomogram for differentiating pleomorphic adenoma and Warthin’s tumor in the parotid gland - Huang, Xiaoying; Zhao, Feng; He, Junkun; Su, Jiping; Zhang, Zhe (Frontiers in Oncology, 2025)
ObjectivesThis study aims to construct and evaluate an integrated nomogram model that combines clinical characteristics and biochemical blood markers to enable accurate and cost-effective differentiation between PA and WT.MethodsA retrospective analysis was carried out on patients diagnosed with PA and WT at the First Affiliated Hospital of Guangxi Medical University between 2013 and 2022. The participants were randomly allocated to the training set or validation set in a 3:1 ratio. Independent predictors were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression. Based on these predictor variables, a nomogram model was developed. The study systematically evaluated the diagnostic performance, calibration effects, and clinical utility of the model through the application of receiver operating characteristic curves (ROC), calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC).ResultsThe study cohort included 249 patients with PA and 173 with WT. The participants were split into a training set of 316 and a validation set of 106. Six independent predictors were identified: sex, age, smoking history, bilateral parotid involvement, white blood cell (WBC) count, and postprandial blood glucose at 2 hours (PBG2h). The AUC of the nomogram on the training set was 0.951, and the sensitivity, specificity and accuracy were 0.91, 0.906 and 0.908, respectively; on the validation set, these metrics were 0.934, 0.918, 0.844 and 0.887, respectively. The calibration curves were in close alignment with the ideal diagonals, indicating that the model has excellent calibration performance. Significant net clinical benefit was observed in the DCA and CIC analyses when the threshold probabilities were in the range of 0.05 to 0.97 for the training set and 0.07 to 0.96 for the validation set.ConclusionThis study presents the first nomogram model integrating clinical features and biochemical indicators for preoperative differentiation between PA and WT. The model offers an accurate, cost-effective tool to support personalized treatment decisions.