Oral Cancer Screening and Education in Hong Kong

The University of Hong Kong3,190 enrolled

Overview

This study will be conducted to obtain data on oral cancer risk factors to generate machine learning models with good predictive accuracy for stratifying individuals with high-oral cancer risk and delineating high-risk and low-risk oral lesions. Likewise, this study will seek to provide oral cancer-related health education and training on oral-self-examination for beneficiaries

Study Type

OBSERVATIONAL

Enrollment

3,190

Conditions

Oral Cancer Oral Leukoplakia Oral Submucous Fibrosis Proliferative Verrucous Leukoplakia Oral Erythroplakia Erosive Lichen Planus

Interventions

Eligibility

Sex: ALLMin age: 45 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Healthy individuals satisfying age and residential area criteria with no previous history of oral cancer. Individuals with a history of other cancers will be included in the study provided they have been in remission for more than three years. Exclusion Criteria: * Participants with reduced mouth opening (irrespective of the cause) to permit proper administration of VOE or photosensitive epilepsy will be excluded. Likewise, those who decline the provision of written consent or participation in any part of the study.

Outcomes

Primary Outcomes

Accuracy of machine learning algorithms for predicting high-risk persons

Predictive accuracy of the ML classifiers for forecasting individuals with or likely to develop high-risk lesions within 24 months of first screening encounter based on demographic and lifestyle information.

Time frame: 24 months

Accuracy of machine learning algorithms for discriminating high-risk and low-risk lesions

Predictive accuracy of ML classifiers for classifying high-risk and low-risk lesions based on demographic and lifestyle risk factors, oral high-risk HPV status, and salivary DNA hypermethylation levels.