Neoplasms

Mouth and Tooth Diseases

Ear, Nose, and Throat Diseases

All Conditions

Digestive System Diseases

Rare Diseases

Nasopharyngeal Carcinoma

Carcinoma

Stomatitis

Mucositis

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

Nasopharyngeal Neoplasms

Pharyngeal Neoplasms

Otorhinolaryngologic Neoplasms

Head and Neck Neoplasms

Nasopharyngeal Diseases

Pharyngeal Diseases

Stomatognathic Diseases

Otorhinolaryngologic Diseases

Gastroenteritis

Gastrointestinal Diseases

Mouth Diseases

Acute Graft Versus Host Disease

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) .

Intervention based on key factors identified by the severe RIOM prediction model

Yu Zeng, Dr.

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.

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

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

According to the Clinical oral dryness score(CODS),A total of 10 features were used to obtain the total CODS. A high total score indicates increased oral dryness.

Evaluation of salivary PH using pH indicator paper

The evaluation of pain is based on the Numerical Rating Scale (NRS), with a numerical score of 0-10. A score of less than 5 is considered mild pain, a score of 5-7 is moderate pain, and a score of 8 or above is severe pain.

According to the CTCAE V5.0 ，Grade 3 and Grade 4 is considered severe RTOM

Patient factors, disease factors, and treatment related factors

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization	Link
Predictive Study on Acute Radiation Induced Oral Mucositis in Nasopharyngeal Carcinoma Patients	NCT05858385	Nasopharyngeal ... Radiation Induc...	Intervention ba...	18 Years - 75 Years	Affiliated Cancer Hospital & Institute of Guangzhou Medical University
Predictive Study on Acute Radiation Induced Oral Mucositis in Nasopharyngeal Carcinoma Patients	NCT05858385	Nasopharyngeal ... Radiation Induc...	Intervention ba...	18 Years - 75 Years	Affiliated Cancer Hospital & Institute of Guangzhou Medical University

Spots Global Cancer Trial Database for intervention based on key factors identified by the severe riom prediction model