Ignite Creation Date:
2025-12-24 @ 9:49 PM
Ignite Modification Date:
2025-12-28 @ 12:36 AM
Study NCT ID:
NCT05870332
Status:
RECRUITING
Last Update Posted:
2024-03-06
First Post:
2023-05-02
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Nationwide Study of Artificial Intelligence in Adenoma Detection for Colonoscopy
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003111', 'term': 'Colonic Polyps'}, {'id': 'D003110', 'term': 'Colonic Neoplasms'}, {'id': 'D015179', 'term': 'Colorectal Neoplasms'}], 'ancestors': [{'id': 'D007417', 'term': 'Intestinal Polyps'}, {'id': 'D011127', 'term': 'Polyps'}, {'id': 'D020763', 'term': 'Pathological Conditions, Anatomical'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D007414', 'term': 'Intestinal Neoplasms'}, {'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': 'D003108', 'term': 'Colonic Diseases'}, {'id': 'D007410', 'term': 'Intestinal Diseases'}, {'id': 'D012002', 'term': 'Rectal Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'CASE_CONTROL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 4000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2023-10-16', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-03', 'completionDateStruct': {'date': '2025-05-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-03-04', 'studyFirstSubmitDate': '2023-05-02', 'studyFirstSubmitQcDate': '2023-05-11', 'lastUpdatePostDateStruct': {'date': '2024-03-06', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-05-23', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-01-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'CADe-ADR in real world practice', 'timeFrame': '24 months', 'description': 'The primary outcome measure will be adenoma detection rate. This will be studied across three phases: prior to use of CADe (baseline practice), while using CADe (study period) and finally after CADe (without the device in situ: "washout" phase).'}], 'secondaryOutcomes': [{'measure': 'APC', 'timeFrame': '24 months', 'description': 'Mean adenomas per colonoscopy (APC)'}, {'measure': 'Polyp characteristics', 'timeFrame': '24 months', 'description': 'Polyp size (mm) and location (in colonic segments)'}, {'measure': 'Procedure time', 'timeFrame': '24 months', 'description': 'Total procedure (insertion+withdrawal) and withdrawal time'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': True}, 'conditionsModule': {'keywords': ['Artificial Intelligence', 'Computer assisted detection (CADe)', 'Colorectal cancer', 'Adenoma Detection Rate (ADR)'], 'conditions': ['Colonic Polyp', 'Colonic Adenoma', 'Colo-rectal Cancer']}, 'descriptionModule': {'briefSummary': 'The goal of this trial is to determine whether use of a Computer Assisted Detection (CADe) programme leads to an increase in ADR for either units or individual colonoscopists, independent of setting or expertise', 'detailedDescription': "This is a case-control study comparing adenoma detection rate (ADR) in hospitals (and individual colonoscopists), before, during and after use with an artificial intelligence unit called GI Genius™ (GIG). GIG is a Computer-assisted detection (CADe) module that assists the human colonoscopist in real-time, by detecting and marking out polyps during colonoscopy. It has been shown to be effective in expert colonoscopists, but the effect in non-expert, general, colonoscopists is not known.\n\nThe investigator wish to deploy GIG into colonoscopy through the UK using a step-wedge design. Sites will be randomly allocated a start date for GIG deployment, collecting data for four months prior to this. In this way, all sites will have the active intervention and will provide their own case-control data. (4 months collection prior to activating GIG, 4 months with GIG, 4 months afterwards without GIG)\n\nThe study will concentrate on non-expert colonoscopists, to determine whether GIG can increase ADR. Patients will undergo the same colonoscopy that they would have had in any case, with no additional trial visits or interventions. There will be no alteration to the usual care pathway from the patient's perspective.\n\nIf the investigator can prove GIG increases ADR in this way, it will provide support to roll out this technology routinely to improve the quality of colonoscopy nationwide."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '85 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Unselected patients scheduled for diagnostic colonoscopy', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Any patient aged 18-85 scheduled for colonoscopy by current NHSE / British Society of Gastroenterology criteria\n\nExclusion Criteria:\n\n* Colonoscopy being performed for polyp surveillance\n* Unable to provide informed, written consent'}, 'identificationModule': {'nctId': 'NCT05870332', 'acronym': 'NAIAD', 'briefTitle': 'Nationwide Study of Artificial Intelligence in Adenoma Detection for Colonoscopy', 'organization': {'class': 'OTHER', 'fullName': "King's College Hospital NHS Trust"}, 'officialTitle': 'Nationwide Study of Artificial Intelligence in Adenoma Detection for Colonoscopy', 'orgStudyIdInfo': {'id': '292323'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'All patients', 'description': 'Patient ≥18 years old, with capacity to consent, scheduled for diagnostic colonoscopy', 'interventionNames': ['Device: GI Genius (GIG)']}], 'interventions': [{'name': 'GI Genius (GIG)', 'type': 'DEVICE', 'otherNames': ['CADe'], 'description': 'GIG is an artificial intelligence unit that assists human colonoscopist in real-time to detect polyps during colonoscopy.\n\nFour months collection period prior to activating GIG, then four months with GIG, and Four months afterwards without GIG', 'armGroupLabels': ['All patients']}]}, 'contactsLocationsModule': {'locations': [{'zip': 'SE5 9RS', 'city': 'London', 'status': 'RECRUITING', 'country': 'United Kingdom', 'contacts': [{'name': 'Alena B Marynina', 'role': 'CONTACT', 'email': 'alena.marynina@nhs.net', 'phone': '+442032996044'}, {'name': 'Olaolu Olabintan', 'role': 'CONTACT', 'email': 'olaolu.olabintan@nhs.net', 'phone': '07939 056819'}, {'name': "Bu'Hussain B Hayee, MBBS, PhD", 'role': 'PRINCIPAL_INVESTIGATOR'}], 'facility': "King's College Hospital NHS Foundation Trust", 'geoPoint': {'lat': 51.50853, 'lon': -0.12574}}], 'centralContacts': [{'name': "Prof Bu'Hussain B Hayee, PHD FRCP", 'role': 'CONTACT', 'email': 'b.hayee@nhs.net', 'phone': '02032996044'}, {'name': 'Dr Olaolu Olabintan, MBBS MRCP', 'role': 'CONTACT', 'email': 'olaolu.olabintan@nhs.net', 'phone': '07939056819'}], 'overallOfficials': [{'name': "Prof Bu'Hussain B Hayee", 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': "King's College Hospital NHS Trust"}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': "King's College Hospital NHS Trust", 'class': 'OTHER'}, 'collaborators': [{'name': 'Medtronic', 'class': 'INDUSTRY'}, {'name': 'National Institute for Health Research, United Kingdom', 'class': 'OTHER_GOV'}], 'responsibleParty': {'type': 'SPONSOR'}}}}