THE HONG KONG ORAL CANCER EDUCATION AND SCREENING (HOCES) PROGRAM: REFINING DISEASE PREVENTION, RISK STRATIFICATION AND EARLY DETECTION
试验速览
- 阶段
- 不适用
- 入组人数
- 3,190
- 主要终点
- Accuracy of machine learning algorithms for predicting high-risk persons
研究概览
简要总结
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
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 45 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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.
排除标准
- •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.
结局指标
主要结局
Accuracy of machine learning algorithms for predicting high-risk persons
时间窗: 24 months
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.
Accuracy of machine learning algorithms for discriminating high-risk and low-risk lesions
时间窗: 24 months
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.
次要结局
未报告次要终点
研究者
Professor Peter James Thomson
Professor
The University of Hong Kong