Prediction of Gastric Cancer in Intestinal Metaplasia and Atrophic Gastritis
NCT ID: NCT04840056
Last Updated: 2024-08-29
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
1300 participants
OBSERVATIONAL
2021-04-15
2025-12-31
Brief Summary
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* To identify clinical or histological factors associated with gastric cancer development in patients with IM and AG
* To establish a machine learning algorithm for prediction of future gastric cancer risks and individual risk stratification in patient with IM and AG
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Detailed Description
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Clinical data will be collected retrospectively using the Clinical Data Analysis and Reporting System (CDARS) and Clinical management System (CMS). A cluster-wide cohort (New Territories East Cluster, NTEC) consisting of patients with history of histologically-proven gastric IM and AG will be identified and included for subsequent analysis. The data collection period for the retrospective data will be 2000-2020.
Histology slides will be retrieved retrospectively when available (within NTEC). Whole slide imaging technique will be utilized for the development of training and validation cohorts with machine learning algorithms in the pathology part.
Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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Intestinal Metaplasia
patient with history of histologically proven gastric intestinal metaplasia
No interventions assigned to this group
Atrophic gastritis
patient with history of histologically proven atrophic gastritis
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Histologically proven atrophic gastritis or intestinal metaplasia (at antrum and/or body and/or angular of stomach)
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Chinese University of Hong Kong
OTHER
Responsible Party
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Louis Ho Shing Lau
Principal Investigator
Locations
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Prince of Wales Hospital
Shatin, New Territories, Hong Kong
Countries
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Central Contacts
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Other Identifiers
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2021.082
Identifier Type: -
Identifier Source: org_study_id
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