Ignite Creation Date:
2025-12-24 @ 3:04 PM
Ignite Modification Date:
2025-12-27 @ 1:22 AM
Study NCT ID:
NCT07110259
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-08-07
First Post:
2025-07-31
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
AI-Based DeepGEM Tool for Predicting Gene Mutations in NSCLC Patients: A Randomized Controlled Study
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'interventionBrowseModule': {'meshes': [{'id': 'D013812', 'term': 'Therapeutics'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['INVESTIGATOR']}, 'primaryPurpose': 'HEALTH_SERVICES_RESEARCH', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 950}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-07-31', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-07', 'completionDateStruct': {'date': '2028-07-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-07-31', 'studyFirstSubmitDate': '2025-07-31', 'studyFirstSubmitQcDate': '2025-07-31', 'lastUpdatePostDateStruct': {'date': '2025-08-07', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-08-07', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2028-07-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Overall Survival (OS)', 'timeFrame': 'From randomization to death from any cause, assessed up to 36 months', 'description': 'Comparison of OS between the DeepGEM-informed group and the standard care group.'}, {'measure': 'Targeted Therapy Utilization Rate', 'timeFrame': 'Up to 6 months post-randomization', 'description': 'Proportion of participants receiving molecularly matched targeted therapies based on standard genetic testing.'}], 'secondaryOutcomes': [{'measure': 'Molecular Testing Rate', 'timeFrame': 'Up to 3 months', 'description': 'Proportion of participants who undergo molecular testing after initial DeepGEM prediction.'}, {'measure': 'Prediction Concordance', 'timeFrame': 'Up to 3 months', 'description': 'Concordance between DeepGEM-predicted mutation status and results from PCR or NGS molecular testing.'}, {'measure': 'Cost-effectiveness of DeepGEM', 'timeFrame': 'Up to 12 months', 'description': 'Evaluation of cost per targeted therapy initiated and cost per life-year gained in the DeepGEM group versus standard care.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Artificial intelligence', 'gene mutations'], 'conditions': ['Non Small Cell Lung Caner']}, 'descriptionModule': {'briefSummary': 'This prospective, multicenter, randomized controlled trial aims to evaluate the clinical utility of DeepGEM, an artificial intelligence (AI)-based mutation prediction tool based on histopathological whole-slide images, in patients with non-small cell lung cancer (NSCLC). The study will assess whether DeepGEM can facilitate molecular testing, increase targeted therapy utilization, and improve survival outcomes in a real-world clinical setting. Patients with stage II-IV treatment-naïve NSCLC and qualified pathology slides for DeepGEM analysis will be enrolled. Eligible participants with AI-predicted EGFR, ALK, or ROS1 mutations will be randomized in a 4:1 ratio to either the DeepGEM-informed group (clinicians can access AI results to guide further testing and treatment) or the standard care group (clinicians are blinded to AI results and follow routine care).'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '75 Years', 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Age between 18 and 75 years, inclusive, at the time of enrollment.\n* Histologically or cytologically confirmed non-small cell lung cancer (NSCLC) with clinical stage II-IV as per the 8th edition of the AJCC staging system.\n* Availability of qualified histopathological whole-slide images that can be reviewed through the KindMED system(DeepGEM).\n* Successful mutation prediction of EGFR, ALK, or ROS1 by the DeepGEM AI tool.\n* No prior systemic anti-cancer therapy, including chemotherapy, targeted therapy, or immunotherapy.\n* Willing and able to comply with study requirements, including follow-up and treatment; written informed consent must be provided.\n\nExclusion Criteria:\n\n* Prior systemic anti-tumor therapy (chemotherapy, radiotherapy, targeted therapy-including but not limited to monoclonal antibodies or tyrosine kinase inhibitors) before enrollment.\n* Failure of DeepGEM analysis or unqualified histopathological image quality.\n* History of any other malignancy within the past 5 years, except for adequately treated basal cell carcinoma of the skin or in situ carcinoma (e.g., cervical carcinoma in situ).\n* Cognitive or psychological barriers to understanding or accepting AI-based prediction or molecular testing.\n* Pregnant or breastfeeding women, or women of childbearing potential who are not using effective contraception.\n* Any other clinical condition that, in the opinion of the investigators, may interfere with the study protocol or compromise participant safety, including poor compliance with study procedures.'}, 'identificationModule': {'nctId': 'NCT07110259', 'briefTitle': 'AI-Based DeepGEM Tool for Predicting Gene Mutations in NSCLC Patients: A Randomized Controlled Study', 'organization': {'class': 'OTHER', 'fullName': 'The First Affiliated Hospital of Guangzhou Medical University'}, 'officialTitle': 'Application of the Artificial Intelligence-Based Gene Mutation Prediction Tool DeepGEM in Patients With Non-Small Cell Lung Cancer (NSCLC): A Prospective, Multicenter, Randomized Controlled Trial', 'orgStudyIdInfo': {'id': 'NSCLC-DeepGEM-RCT-2025'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'DeepGEM-Informed Group', 'description': 'Participants whose clinicians are provided with DeepGEM-predicted mutation status (EGFR/ALK/ROS1). Physicians may choose to proceed with molecular testing and initiate targeted therapy based on AI predictions.', 'interventionNames': ['Other: DeepGEM-guided Molecular Testing and Treatment']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Standard Care Group', 'description': 'Participants whose clinicians do not receive DeepGEM prediction results and manage the case per standard diagnostic and treatment protocols without AI support.', 'interventionNames': ['Other: Standard Diagnostic Pathway']}], 'interventions': [{'name': 'DeepGEM-guided Molecular Testing and Treatment', 'type': 'OTHER', 'description': 'Artificial intelligence-based mutation prediction using DeepGEM to guide clinical decision-making for molecular testing and therapy selection.', 'armGroupLabels': ['DeepGEM-Informed Group']}, {'name': 'Standard Diagnostic Pathway', 'type': 'OTHER', 'description': 'DeepGEM is used for eligibility screening, but its results are withheld. Clinicians manage patients per standard diagnostic and treatment practices.', 'armGroupLabels': ['Standard Care Group']}]}, 'contactsLocationsModule': {'centralContacts': [{'name': 'Jianxing He, PhD', 'role': 'CONTACT', 'email': 'hejx@vip.163.com', 'phone': '13802777270'}, {'name': 'Wenhua Liang, PhD', 'role': 'CONTACT', 'email': '550627660@qq.com', 'phone': '13710249454'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Jianxing He', 'class': 'OTHER'}, 'collaborators': [{'name': 'Guangzhou Kingmed Diagnostics Co., Ltd.', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'SPONSOR_INVESTIGATOR', 'investigatorTitle': 'Clinical Professor', 'investigatorFullName': 'Jianxing He', 'investigatorAffiliation': 'The First Affiliated Hospital of Guangzhou Medical University'}}}}