Biomarkers in the assessment of oral mucositis in head and neck cancer patients: a systematic review and meta-analysis.

PURPOSE: The aim of this study was to evaluate the capability of biomarkers to predict the risk of oral mucositis in head and neck cancer patients, as well as to assess the correlation between these biomarkers and the severity of mucositis.

METHODS: The search was performed at LILACS, PubMed, Science Direct, Scopus, and Web of Science. A search of the gray literature was performed on Google Scholar, OpenGrey, and ProQuest. The methodological quality of the included studies was assessed using the Meta-Analysis of Statistics Assessment and Review Instrument (MAStARI) tool, and the evidence quality was assessed by the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) system.

RESULTS: After a two-step selection process, 26 studies met the eligibility criteria. In total, 27 biomarkers were evaluated, and the most frequent were the epidermal growth factor (EGF), C-reactive protein (CRP), genetic polymorphisms, tumor necrosis factor alpha (TNF-α), and erythrocyte sedimentation rate (ESR). The meta-analysis showed an expression of polymorphisms in XRCC1 (32.66%), XRCC3 (31.00%), and RAD51 (39.16%) genes, as well as an expression of protein biomarkers (39.57%), in patients with an increased risk of developing oral mucositis.

CONCLUSIONS: Dosing biomarkers before starting radiation therapy may be a promising method to predict the risk of developing mucositis and allow radiosensitive patients to have a customized treatment. Although there is currently limited evidence to confirm the putative implementation of serum and salivary biomarkers to assess the correlation between them and the severity of mucositis, this current review provides new research directions.