Oral Cancer Clinical Trial
Official title:
THE HONG KONG ORAL CANCER EDUCATION AND SCREENING (HOCES) PROGRAM: REFINING DISEASE PREVENTION, RISK STRATIFICATION AND EARLY DETECTION
Verified date | July 2020 |
Source | The University of Hong Kong |
Contact | John Adeoye |
Phone | 56441784 |
jaadeoye[@]hku.hk | |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
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
Status | Not yet recruiting |
Enrollment | 3190 |
Est. completion date | July 31, 2024 |
Est. primary completion date | July 31, 2023 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 45 Years and older |
Eligibility |
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. |
Country | Name | City | State |
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n/a |
Lead Sponsor | Collaborator |
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The University of Hong Kong |
Adeoye J, Brennan PA, Thomson P. "Search less, verify more"-Reviewing salivary biomarkers in oral cancer detection. J Oral Pathol Med. 2020 Feb 6. doi: 10.1111/jop.13003. [Epub ahead of print] Review. — View Citation
Adeoye J, Choi SW, Thomson P. Bayesian disease mapping and the 'High-Risk' oral cancer population in Hong Kong. J Oral Pathol Med. 2020 May 25. doi: 10.1111/jop.13045. [Epub ahead of print] — View Citation
Adeoye J, Chu CS, Choi SW, Thomson P. Oral cancer awareness and individuals' inclination to its screening and risk prediction in Hong Kong. J Cancer Educ. 2020.
Adeoye J, Thomson P. Strategies to improve diagnosis and risk assessment for oral cancer patients. Faculty Dental Journal. 2020;11(3):122-7.
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | 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. | 24 months | |
Primary | 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. | 24 months |
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