Predictive Factors for Chemoradiation-Induced Oral Mucositis and Dysphagia in Head and Neck Cancer: A Scoping Review

Author:

Nicol Alexander J.1ORCID,Ching Jerry C. F.1ORCID,Tam Victor C. W.1,Liu Kelvin C. K.1,Leung Vincent W. S.1ORCID,Cai Jing12ORCID,Lee Shara W. Y.1ORCID

Affiliation:

1. Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China

2. The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen 518000, China

Abstract

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.

Funder

Shenzhen Basic Research Program

Project of Strategic Importance Fund

Projects of RISA

The Hong Kong Polytechnic University

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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