ArticleCancers2023
Multimodal Data Integration to Predict Severe Acute Oral Mucositis of Nasopharyngeal Carcinoma Patients Following Radiation Therapy.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.
- Prediction models of severe radiation-induced oral mucositis: a systematic review and meta-analysis.BMC oral health · 2025Pooled it
- Prognostic models for radiation-induced complications after radiotherapy in head and neck cancer patients.The Cochrane database of systematic reviews · 2025Pooled it
- Evaluation of mid-treatmentQuantitative imaging in medicine and surgery · 2026Article
- A new perspective on radiotherapy in the comprehensive treatment of cancer.Precision radiation oncology · 2026Review
- Article
- Pain Control in Oral Mucositis According to the Severity Scale: A Narrative Literature Review.Journal of clinical medicine · 2025Review
- Development and verification of a radiomics model to forecast Ki67 index and prognosis in advanced gastric tubular adenocarcinoma.BMC gastroenterology · 2025Article
- A multi-center, multi-organ, multi-omic prediction model for treatment-induced severe oral mucositis in nasopharyngeal carcinoma.La Radiologia medica · 2025Article
- [Performance of multi-modality and multi-classifier fusion models for predicting radiation-induced oral mucositis in patients with nasopharyngeal carcinoma].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- Predictive Factors for Chemoradiation-Induced Oral Mucositis and Dysphagia in Head and Neck Cancer: A Scoping Review.Cancers · 2023Article
Corrections and comments
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Authors and funding
14 authors at 4 institutions in 2 countries.
Funding
Abstract
(1) Background: Acute oral mucositis is the most common side effect for nasopharyngeal carcinoma patients receiving radiotherapy. Improper or delayed intervention to severe AOM could degrade the quality of life or survival for NPC patients. An effective prediction method for severe AOM is needed for the individualized management of NPC patients in the era of personalized medicine. (2) Methods: A total of 242 biopsy-proven NPC patients were retrospectively recruited in this study. Radiomics features were extracted from contrast-enhanced CT (CECT), contrast-enhanced T1-weighted (cT1WI), and T2-weighted (T2WI) images in the primary tumor and tumor-related area. Dosiomics features were extracted from 2D or 3D dose-volume histograms (DVH). Multiple models were established with single and integrated data. The dataset was randomized into training and test sets at a ratio of 7:3 with 10-fold cross-validation. (3) Results: The best-performing model using Gaussian Naive Bayes (GNB) (mean validation AUC = 0.81 ± 0.10) was established with integrated radiomics and dosiomics data. The GNB radiomics and dosiomics models yielded mean validation AUC of 0.6 ± 0.20 and 0.69 ± 0.14, respectively. (4) Conclusions: Integrating radiomics and dosiomics data from the primary tumor area could generate the best-performing model for severe AOM prediction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.