Ignite Creation Date:
2025-12-24 @ 11:33 PM
Ignite Modification Date:
2026-01-01 @ 6:20 PM
Study NCT ID:
NCT04840056
Status:
RECRUITING
Last Update Posted:
2024-08-29
First Post:
2021-03-23
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Prediction of Gastric Cancer in Intestinal Metaplasia and Atrophic Gastritis
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D013274', 'term': 'Stomach Neoplasms'}, {'id': 'D005757', 'term': 'Gastritis, Atrophic'}], 'ancestors': [{'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}, {'id': 'D013272', 'term': 'Stomach Diseases'}, {'id': 'D005756', 'term': 'Gastritis'}, {'id': 'D005759', 'term': 'Gastroenteritis'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 1300}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2021-04-15', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-08', 'completionDateStruct': {'date': '2025-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-08-28', 'studyFirstSubmitDate': '2021-03-23', 'studyFirstSubmitQcDate': '2021-04-07', 'lastUpdatePostDateStruct': {'date': '2024-08-29', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-04-09', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-12-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Gastric cancer and gastric dysplasia', 'timeFrame': '20 years', 'description': 'The primary endpoint is the incidence of gastric cancer (intestinal-type) and gastric dysplasia (low grade and high grade dysplasia).'}], 'secondaryOutcomes': [{'measure': 'Overall accuracy of machine learning model', 'timeFrame': '20 years', 'description': 'Overall accuracy of machine learning models will be evaluated'}, {'measure': 'Sensitivity of machine learning model', 'timeFrame': '20 years', 'description': 'Sensitivity of machine learning model will be evaluated'}, {'measure': 'Specificity of machine learning model', 'timeFrame': '20 years', 'description': 'Specificity of machine learning model will be evaluated'}, {'measure': 'Positive predictive value of machine learning model', 'timeFrame': '20 years', 'description': 'Positive predictive value of machine learning model will be evaluated'}, {'measure': 'Negative predictive value of machine learning model', 'timeFrame': '20 years', 'description': 'Negative predictive value of machine learning model will be evaluated'}, {'measure': 'Area under the receiver operating characteristic curve of machine learning model', 'timeFrame': '20 years', 'description': 'Area under the receiver operating characteristic curve of machine learning model will be evaluated'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['artificial intelligence'], 'conditions': ['Gastric Cancer', 'Intestinal Metaplasia', 'Atrophic Gastritis']}, 'descriptionModule': {'briefSummary': 'The primary objectives of this study are:\n\n* To identify clinical or histological factors associated with gastric cancer development in patients with IM and AG\n* To establish a machine learning algorithm for prediction of future gastric cancer risks and individual risk stratification in patient with IM and AG', 'detailedDescription': 'This is a two-part retrospective study including a clinical data part and a pathology part. A training cohort will be developed from approximately 70% of included cases. It will be followed by a validation cohort with the remaining cases.\n\nClinical 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.\n\nHistology 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.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': '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.\n\nHistology 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.', 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Adults \\>= 18 years of age\n* Histologically proven atrophic gastritis or intestinal metaplasia (at antrum and/or body and/or angular of stomach)\n\nExclusion Criteria:\n\n\\- none'}, 'identificationModule': {'nctId': 'NCT04840056', 'acronym': 'GIMA', 'briefTitle': 'Prediction of Gastric Cancer in Intestinal Metaplasia and Atrophic Gastritis', 'organization': {'class': 'OTHER', 'fullName': 'Chinese University of Hong Kong'}, 'officialTitle': 'Prediction of Gastric Cancer in Intestinal Metaplasia and Atrophic Gastritis - Application of Artificial Intelligence in Histology and Clinical Data', 'orgStudyIdInfo': {'id': '2021.082'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Intestinal Metaplasia', 'description': 'patient with history of histologically proven gastric intestinal metaplasia'}, {'label': 'Atrophic gastritis', 'description': 'patient with history of histologically proven atrophic gastritis'}]}, 'contactsLocationsModule': {'locations': [{'city': 'Shatin', 'state': 'New Territories', 'status': 'RECRUITING', 'country': 'Hong Kong', 'facility': 'Prince of Wales Hospital', 'geoPoint': {'lat': 22.38333, 'lon': 114.18333}}], 'centralContacts': [{'name': 'Felix Sia', 'role': 'CONTACT', 'email': 'felix.sia@cuhk.edu.hk', 'phone': '+85226370428'}, {'name': 'Thomas Lam', 'role': 'CONTACT', 'email': 'thomas.lam@cuhk.edu.hk', 'phone': '+85226370428'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'There is no plan to share IPD with other researchers'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Chinese University of Hong Kong', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Louis Ho Shing Lau', 'investigatorAffiliation': 'Chinese University of Hong Kong'}}}}