<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04487938</url>
  </required_header>
  <id_info>
    <org_study_id>thomsonp@hku.hk</org_study_id>
    <nct_id>NCT04487938</nct_id>
  </id_info>
  <brief_title>Oral Cancer Screening and Education in Hong Kong</brief_title>
  <official_title>THE HONG KONG ORAL CANCER EDUCATION AND SCREENING (HOCES) PROGRAM: REFINING DISEASE PREVENTION, RISK STRATIFICATION AND EARLY DETECTION</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>The University of Hong Kong</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>The University of Hong Kong</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This study will be conducted to obtain data on oral cancer risk factors to generate machine&#xD;
      learning models with good predictive accuracy for stratifying individuals with high-oral&#xD;
      cancer risk and delineating high-risk and low-risk oral lesions. Likewise, this study will&#xD;
      seek to provide oral cancer-related health education and training on oral-self-examination&#xD;
      for beneficiaries&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Not yet recruiting</overall_status>
  <start_date type="Anticipated">August 1, 2021</start_date>
  <completion_date type="Anticipated">July 31, 2024</completion_date>
  <primary_completion_date type="Anticipated">July 31, 2023</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Accuracy of machine learning algorithms for predicting high-risk persons</measure>
    <time_frame>24 months</time_frame>
    <description>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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Accuracy of machine learning algorithms for discriminating high-risk and low-risk lesions</measure>
    <time_frame>24 months</time_frame>
    <description>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.</description>
  </primary_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Anticipated">3190</enrollment>
  <condition>Oral Cancer</condition>
  <condition>Oral Leukoplakia</condition>
  <condition>Oral Submucous Fibrosis</condition>
  <condition>Proliferative Verrucous Leukoplakia</condition>
  <condition>Oral Erythroplakia</condition>
  <condition>Erosive Lichen Planus</condition>
  <arm_group>
    <arm_group_label>Tobacco use and/or alcohol consumption</arm_group_label>
  </arm_group>
  <arm_group>
    <arm_group_label>No tobacco use and/or alcohol consumption</arm_group_label>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>No intervention utilised</intervention_name>
    <description>No intervention utilised</description>
    <arm_group_label>No tobacco use and/or alcohol consumption</arm_group_label>
    <arm_group_label>Tobacco use and/or alcohol consumption</arm_group_label>
  </intervention>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      Oral rinse samples obtained via drooling in 50cc tubes.&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        Hong Kong residents aged 45 years and above residing in Southern and Central and Western&#xD;
        district council districts (DCD).&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Healthy individuals satisfying age and residential area criteria with no previous&#xD;
             history of oral cancer. Individuals with a history of other cancers will be included&#xD;
             in the study provided they have been in remission for more than three years.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Participants with reduced mouth opening (irrespective of the cause) to permit proper&#xD;
             administration of VOE or photosensitive epilepsy will be excluded. Likewise, those who&#xD;
             decline the provision of written consent or participation in any part of the study.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>45 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Peter Thomson</last_name>
    <role>Principal Investigator</role>
    <affiliation>The University of Hong Kong</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>John Adeoye</last_name>
    <phone>56441784</phone>
    <email>jaadeoye@hku.hk</email>
  </overall_contact>
  <reference>
    <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 Oct;49(9):907-913. doi: 10.1111/jop.13045. Epub 2020 Jun 10.</citation>
    <PMID>32450000</PMID>
  </reference>
  <reference>
    <citation>Adeoye J, Brennan PA, Thomson P. &quot;Search less, verify more&quot;-Reviewing salivary biomarkers in oral cancer detection. J Oral Pathol Med. 2020 Sep;49(8):711-719. doi: 10.1111/jop.13003. Epub 2020 Mar 5.</citation>
    <PMID>32027406</PMID>
  </reference>
  <reference>
    <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. 2022 Apr;37(2):439-448. doi: 10.1007/s13187-020-01834-x.</citation>
    <PMID>32705524</PMID>
  </reference>
  <reference>
    <citation>Adeoye J, Thomson P. Strategies to improve diagnosis and risk assessment for oral cancer patients. Faculty Dental Journal. 2020;11(3):122-7.</citation>
  </reference>
  <verification_date>July 2020</verification_date>
  <study_first_submitted>July 22, 2020</study_first_submitted>
  <study_first_submitted_qc>July 22, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 27, 2020</study_first_posted>
  <last_update_submitted>July 22, 2020</last_update_submitted>
  <last_update_submitted_qc>July 22, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">July 27, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>The University of Hong Kong</investigator_affiliation>
    <investigator_full_name>Professor Peter James Thomson</investigator_full_name>
    <investigator_title>Professor</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Mouth Neoplasms</mesh_term>
    <mesh_term>Lip Neoplasms</mesh_term>
    <mesh_term>Leukoplakia</mesh_term>
    <mesh_term>Leukoplakia, Oral</mesh_term>
    <mesh_term>Oral Submucous Fibrosis</mesh_term>
    <mesh_term>Lichen Planus</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04487938
org study id: thomsonp@hku.hk
nct id: NCT04487938
lead sponsor: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
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
observational model: Cohort
time perspective: Prospective
measure: Accuracy of machine learning algorithms for predicting high-risk persons
time frame: 24 months
description: 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.
measure: Accuracy of machine learning algorithms for discriminating high-risk and low-risk lesions
time frame: 24 months
description: 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.
arm group label: Tobacco use and/or alcohol consumption
arm group label: No tobacco use and/or alcohol consumption
intervention type: Other
intervention name: No intervention utilised
description: No intervention utilised
arm group label: No tobacco use and/or alcohol consumption
arm group label: Tobacco use and/or alcohol consumption
Oral rinse samples obtained via drooling in 50cc tubes.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 45 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Peter Thomson
role: Principal Investigator
affiliation: The University of Hong Kong
last name: John Adeoye
phone: 56441784
email: jaadeoye@hku.hk
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 Oct;49(9):907-913. doi: 10.1111/jop.13045. Epub 2020 Jun 10.
PMID: 32450000
citation: Adeoye J, Brennan PA, Thomson P. "Search less, verify more"-Reviewing salivary biomarkers in oral cancer detection. J Oral Pathol Med. 2020 Sep;49(8):711-719. doi: 10.1111/jop.13003. Epub 2020 Mar 5.
PMID: 32027406
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. 2022 Apr;37(2):439-448. doi: 10.1007/s13187-020-01834-x.
PMID: 32705524
citation: Adeoye J, Thomson P. Strategies to improve diagnosis and risk assessment for oral cancer patients. Faculty Dental Journal. 2020;11(3):122-7.
responsible party type: Principal Investigator
investigator affiliation: The University of Hong Kong
investigator full name: Professor Peter James Thomson
investigator title: Professor
mesh term: Mouth Neoplasms
mesh term: Lip Neoplasms
mesh term: Leukoplakia
mesh term: Leukoplakia, Oral
mesh term: Oral Submucous Fibrosis
mesh term: Lichen Planus
sharing ipd: No