Construction and Validation of a Nomogram Prediction Model for Individualized Prediction of the Risk of Oral Infection in Patients with Nasopharyngeal Carcinoma Undergoing Radiotherapy and Chemotherapy.

Authors

Jinfeng Wang, Qiang Ye, Chunyu Liu, Kui Zhong, Wenting Zhou

Published in

Cancer management and research. Volume 18. Pages 603294. Epub Jul 10, 2026.

Abstract

To establish and validate a nomogram prediction model for individualized prediction of the risk of oral infection in patients with nasopharyngeal carcinoma (NPC) undergoing radiotherapy and chemotherapy.
The clinical data of 379 NPC patients admitted to our hospital from March 2021 to March 2024 were retrospectively collected (as the training set), and the clinical data of 226 NPC patients admitted to other hospitals from April 2024 to December 2025 were also collected (as the validation set). The patients were separated into the infection group and the non-infection group based on whether they had oral infections. The clinical data of the patients were collected. LASSO-logistic regression analysis was used to identify the factors influencing the occurrence of oral infection in patients with NPC undergoing chemoradiotherapy. R software was used to construct a nomogram prediction model for the occurrence of oral infection in these patients. Bootstrap resampling was performed for internal validation. ROC curves and calibration curves were used to evaluate the discrimination and consistency of the model, respectively, while DCA was used to assess its clinical application value.
The Lasso-Logistic analysis showed that age, diabetes, smoking history, oral pH value, chemotherapy cycles, history of oral infection, and ALB were the influencing factors for the occurrence of oral infections in NPC patients undergoing radiotherapy and chemotherapy (P < 0.05). The AUC of the internal validation was 0.833. The Bootstrap method indicated a C-index of 0.833. The H-L test showed χ² = 7.638, P = 0.734. The DCA curve indicated that the model had a good positive net benefit within the probability range of 0.21~0.93. The external validation AUC was 0.886. The Bootstrap method validation showed a C-index of 0.886. The H-L test yielded χ² = 7.764, P = 0.728. The DCA curve indicated that the model had a good positive net benefit within the probability range of 0.21~0.95.
Age, diabetes, smoking history, oral pH value, chemotherapy cycles, history of oral infection, and ALB are the influencing factors for the occurrence of oral infections in NPC patients undergoing radiotherapy and chemotherapy. The constructed nomogram model based on these factors is conducive to individualized prediction of oral infections in patients, and can facilitate the early identification of high-risk populations. However, as this was a retrospective study, the sample size selection and study design may have introduced potential bias.

PMID:
42453700
Bibliographic data and abstract were imported from PubMed on 15 Jul 2026.

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