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Development and Validation of a Nomogram Model for Predicting Non-keratinizing Nasopharyngeal Carcinoma by Combining
Fu Xu1, Yuming Li1, Xuanli Zhong2
1Department of Otorhinolaryngology Head and Neck Surgery, The Affiliated Shunde Hospital of Jinan University, Foshan, China.
Abstract:
IntroductionEarly diagnosis of non-keratinizing nasopharyngeal carcinoma (NK-NPC) is a significant clinical challenge. This study assessed combined antibodies and built a nomogram for more accurate NK-NPC screening.MethodsClinical data of 1330 individuals at high risk of nasopharyngeal carcinoma (NPC) from June 2021 to December 2024 were collected retrospectively. They were randomly divided into a training set (n = 930) and a validation set (n = 400) at a ratio of 7:3. The training set was further divided into the NK-NPC group and the non-NK-NPC group. Univariate and multivariate analyses were used to screen for risk factors of cancer, based on which a risk prediction nomogram model was constructed. The predictive performance of the model was evaluated using indicators such as the area under the receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI), decision curve analysis (DCA), and Youden index. Additionally, an external validation set (cases from January-May 2025 at the same hospital) further assessed the model.ResultsSex, EBNA1-IgA, VCA-IgA, and Rta-IgG were independent risk factors for NK-NPC in high-risk populations (P < 0.05). The validation results of the nomogram model constructed based on the above factors showed that the AUC values of the receiver operating characteristic (ROC) curves in the training set and validation set were 0.898 and 0.963. Decision curve analysis showed that the net benefit value of this model was higher than that of the traditional model within the threshold probability range of 10% to 60%. The external validation results showed that the sensitivity of the model was 100% and the specificity was 87.8%.ConclusionThe NK-NPC prediction nomogram model constructed in this study has a high recognition rate and good calibration. It can serve as an effective prediction tool for NK-NPC in high-risk populations of nasopharyngeal carcinoma.
