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

The relevance of dental management prior to radiation therapy with severe oral mucositis in head and neck cancer patients

Background/purpose

Dental management prior to radiotherapy is often time-critical, and there are no studies on whether manipulations such as tooth extraction influence the risk of severe radiation-induced oral mucositis (ROM) during radiotherapy. Therefore, the aim of this study was to describe the relationship between dental management and the incidence of severe ROM.

Materials and methods

A retrospective analysis was conducted on 144 head and neck cancer (HNC) patients who received dental management before radiotherapy at Peking University Cancer Hospital, from January 2016 to December 2017. Demographic characteristics, primary tumor features, cancer treatment characteristics, and severity of oral mucositis during radiotherapy were recorded. Univariate analysis and logistic regression analysis were used to explore factors associated with severe radiation-induced oral mucositis.

Results

The incidence of grade 3 mucositis was 14.5% (22/144); univariate analysis showed that the number of extracted teeth (OR = 1.313; 95%CI = 1.012-1.702; P = 0.040) and patients with primary oral cancer had a higher risk of developing grade 3 mucositis (OR = 3.848; 95% CI = 1.508-9.822; P = 0.005). No statistical correlation was found between pre-radiation therapy prophylaxis, dental restoration, endodontic treatment, and grade 3 mucositis (P > 0.05). Logistic regression analysis showed that the number of extracted teeth (OR = 1.421, 95%CI = 1.071-1.885, P = 0.015) and primary tumor location in the oral cavity (compared with other head and neck cancers) (OR = 5.165, 95%CI = 1.636-16.311, P = 0.005) were significantly associated with grade 3 mucositis.

Conclusion

In HNC patients undergoing radiotherapy, the primary site located in the oral cavity and a higher number of teeth extracted are independent risk factors for the development of severe mucositis.

A multi-center, multi-organ, multi-omic prediction model for treatment-induced severe oral mucositis in nasopharyngeal carcinoma

PURPOSE

Oral mucositis (OM) is one of the most prevalent and crippling treatment-related toxicities experienced by nasopharyngeal carcinoma (NPC) patients receiving radiotherapy (RT), posing a tremendous adverse impact on quality of life. This multi-center study aimed to develop and externally validate a multi-omic prediction model for severe OM.

METHODS

Four hundred and sixty-four histologically confirmed NPC patients were retrospectively recruited from two public hospitals in Hong Kong. Model development was conducted on one institution (n = 363), and the other was reserved for external validation (n = 101). Severe OM was defined as the occurrence of CTCAE grade 3 or higher OM during RT. Two predictive models were constructed: 1) conventional clinical and DVH features and 2) a multi-omic approach including clinical, radiomic and dosiomic features.

RESULTS

The multi-omic model, consisting of chemotherapy status and radiomic and dosiomic features, outperformed the conventional model in internal and external validation, achieving AUC scores of 0.67 [95% CI: (0.61, 0.73)] and 0.65 [95% CI: (0.53, 0.77)], respectively, compared to the conventional model with 0.63 [95% CI: (0.56, 0.69)] and 0.56 [95% CI: (0.44, 0.67)], respectively. In multivariate analysis, only the multi-omic model signature was significantly correlated with severe OM in external validation (p = 0.017), demonstrating the independent predictive value of the multi-omic approach.

CONCLUSION

A multi-omic model with combined clinical, radiomic and dosiomic features achieved superior pre-treatment prediction of severe OM. Further exploration is warranted to facilitate improved clinical decision-making and enable more effective and personalized care for the prevention and management of OM in NPC patients.