Predictive Study on Acute Radiation Induced Oral Mucositis in Nasopharyngeal Carcinoma Patients

Overview

Exploring effective risk prediction models for severe Radiation-Induced Oral Mucositis (RIOM/RTOM), providing a research basis for mitigating oral radiation toxicity, and effectively improving the sensitivity of dentists in predicting the risk of severe RIOM in locally advanced nasopharyngeal carcinoma patients.Based on precise radiotherapy, it is proposed to extract OAR using the contour of local oral areas. Explore more accurate RIOM dose-response relationships.Exploring a new type of fusion classifier, by complementing the information between each base classifier, helps to maximize the utilization of the information contained in different factors to build a more objective, reliable, and efficient multi criteria decision-making based risk prediction model for severe RIOM. It use predictive models to identify key risk factors for severe RIOM and further validate the effectiveness of this risk factor in reducing the risk of severe RIOM on risk factors for severe RIOM identified by the predictive mode.

This study investigates the prediction and management of Radiation-Induced Oral Mucositis (RIOM/RTOM) in patients with locally advanced nasopharyngeal carcinoma undergoing radiotherapy. RIOM is a significant concern due to its impact on the quality of life for patients and its potential to disrupt radiotherapy courses, affecting local tumor control rates. We systematically analyzed multifaceted data, including dosimetric parameters, clinical factors, and oral variables, to develop a predictive model for severe RIOM. The effectiveness of key risk factors in mitigating the risk of severe RIOM was further validated to predict and potentially prevent severe RIOM.

Conditions