Risk Prediction of Severe Radiation-induced Oral Mucositis in Locally Advanced Nasopharyngeal Carcinoma

Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Observational
SUMMARY

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.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Maximum Age: 75
Healthy Volunteers: f
View:

• Confirmed as nasopharyngeal carcinoma through pathological tissue biopsy, AJCC 8th edition bed staging is I-Iva stage, with no distant metastasis

• First time receiving radical radiation therapy and receiving RTOM observation and treatment throughout the entire process in the Department of Stomatology

• Complete information on anti-tumor treatment materials

• No oral mucosal diseases that have not been effectively controlled in the past or still require long-term medication treatment

• Other diseases that do not affect the treatment of nasopharyngeal carcinoma

Locations
Other Locations
China
Yu Zeng
RECRUITING
Guangzhou
Time Frame
Start Date: 2022-09-22
Estimated Completion Date: 2024-12-31
Participants
Target number of participants: 700
Treatments
Development and Validation of severe RIOM prediction model
This group aims to develop an artificial intelligence model using a retrospective cohort to predict severe RIOM in patients diagnosed with LA-NPC and evaluate 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 model.The oral evaluation of all patients was conducted by the same senior dentist, who evaluated the oral mucosal radiation toxicity weekly at baseline (before RT) and after RT, and performed RIOM scores.RIOM is classified using the National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (CTCAE v5.0) .
Sponsors
Leads: Affiliated Cancer Hospital & Institute of Guangzhou Medical University

This content was sourced from clinicaltrials.gov