Predictive Factors for Chemoradiation-Induced Oral Mucositis and Dysphagia in Head and Neck Cancer: A Scoping Review.
Alexander James NicolJerry Chi Fung ChingVictor C W TamKelvin C K LiuVincent W S LeungJing CaiShara Wee-Yee LeePublished in: Cancers (2023)
Despite advances in head and neck cancer treatment, virtually all patients experience chemoradiation-induced toxicities. Oral mucositis (OM) and dysphagia are among the most prevalent and have a systemic impact on patients, hampering treatment outcome and harming quality of life. Accurate prediction of severe cases is crucial for improving management strategies and, ultimately, patient outcomes. This scoping review comprehensively maps the reported predictors and critically evaluates the performance, methodology, and reporting of predictive models for these conditions. A total of 174 studies were identified from database searches, with 73 reporting OM predictors, 97 reporting dysphagia predictors, and 4 reporting both OM and dysphagia predictors. These predictors included patient demographics, tumor classification, chemoradiotherapy regimen, radiation dose to organs-at-risk, genetic factors, and results of clinical laboratory tests. Notably, many studies only conducted univariate analysis or focused exclusively on certain predictor types. Among the included studies, numerous predictive models were reported: eight for acute OM, five for acute dysphagia, and nine for late dysphagia. The area under the receiver operating characteristic curve (AUC) ranged between 0.65 and 0.81, 0.60 and 0.82, and 0.70 and 0.85 for acute oral mucositis, acute dysphagia, and late dysphagia predictive models, respectively. Several areas for improvement were identified, including the need for external validation with sufficiently large sample sizes, further standardization of predictor and outcome definitions, and more comprehensive reporting to facilitate reproducibility.
Keyphrases
- drug induced
- liver failure
- adverse drug
- end stage renal disease
- respiratory failure
- newly diagnosed
- chronic kidney disease
- rectal cancer
- radiation induced
- aortic dissection
- locally advanced
- prognostic factors
- deep learning
- intensive care unit
- dna methylation
- machine learning
- extracorporeal membrane oxygenation
- case report
- mass spectrometry
- high resolution
- diabetic rats
- patient reported
- oxidative stress
- patient reported outcomes