Evidence map›Paper›PMID 42827601›Full record

ArticleFrontiers in oncology2026

A prediction model based on the prognostic nutritional index for grade 2 or higher radiation-induced oral mucositis in patients with nasopharyngeal carcinoma.

Deyue Jiang, Ruohan Wang, Jin Lu, Huanhuan Yu, Haoxuan Zhang

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Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Deyue JiangDepartment of Human Anatomy, Bengbu Medical University, Bengbu, China.
Ruohan WangDepartment of Human Anatomy, Bengbu Medical University, Bengbu, China.
Jin LuDepartment of Human Anatomy, Bengbu Medical University, Bengbu, China.
Huanhuan YuBengbu Hospital of Traditional Chinese Medicine, Bengbu, China.
Haoxuan ZhangDepartment of Human Anatomy, Bengbu Medical University, Bengbu, China.

Funding

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6 · The paper itself

Abstract

Introduction: To develop a prediction model based on the prognostic nutritional index for grade 2 or higher radiation-induced oral mucositis in patients with nasopharyngeal carcinoma, providing a basis for early identification of patients at high risk. Methods: We retrospectively included 192 patients with primary nasopharyngeal carcinoma who received chemoradiotherapy at the First Affiliated Hospital of Bengbu Medical University between May 2020 and December 2025. Patients were randomly assigned in a 7:3 ratio to a training set (n = 133) and an internal validation set (n = 59). Baseline characteristics were compared after tests of normality and homogeneity of variance. Candidate variables were selected jointly using LASSO, random forest, and support vector machine recursive feature elimination, followed by univariable and multivariable logistic regression to identify factors associated with grade 2 or higher radiation-induced oral mucositis. A nomogram was constructed, and Firth penalized likelihood regression was used to reduce small-sample bias. Model performance was assessed using receiver operating characteristic analysis and calibration curves, while clinical utility was evaluated by decision curve analysis. Propensity score matching was then used for sensitivity analysis. Results: The prognostic nutritional index was an independent protective factor of grade 2 or higher radiation-induced oral mucositis. The area under the curve was 0.842 in the training set and 0.725 in the validation set. Patients in the group with high prognostic nutritional index values had a markedly lower risk (OR = 0.067, P < 0.001), and the finding remained consistent in the Firth regression analysis. The association also remained significant after 1:1 propensity score matching (OR = 0.709, P < 0.001; AUC = 0.810). Conclusion: The prognostic nutritional index is an independent predictor of grade 2 or higher radiation-induced oral mucositis, and the model showed useful predictive performance for this outcome in patients with NPC receiving chemoradiotherapy.

Indexed as

machine learningnasopharyngeal carcinomaprediction modelprognostic nutritional indexradiation-induced oral mucositis

Identifiers

PMID42827601
PMCPMC13630615

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