Ignite Creation Date:
2026-03-26 @ 3:14 PM
Ignite Modification Date:
2026-03-31 @ 2:11 AM
Study NCT ID:
NCT07354295
Status:
RECRUITING
Last Update Posted:
2026-03-10
First Post:
2026-01-12
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Integrating Multimodal AI to Predict Treatment Response and Refine Risk Stratification in Esophageal Cancer （Radiogenomics-Esophagus）
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2026-03-25'}, 'conditionBrowseModule': {'meshes': [{'id': 'D004938', 'term': 'Esophageal Neoplasms'}], 'ancestors': [{'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D006258', 'term': 'Head and Neck Neoplasms'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D004935', 'term': 'Esophageal Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITH_DNA', 'description': 'Blood samples will be obtained from residual specimens remaining after routine clinical laboratory testing, and tissue samples will be collected from specimens left over after pathologists have taken necessary sections for diagnostic purposes following surgical resection.'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'OTHER', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 1500}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-07-26', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2026-02', 'completionDateStruct': {'date': '2030-09-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2026-03-06', 'studyFirstSubmitDate': '2026-01-12', 'studyFirstSubmitQcDate': '2026-01-12', 'lastUpdatePostDateStruct': {'date': '2026-03-10', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2026-01-21', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2030-09-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'overall survival', 'timeFrame': 'From enrollment to the end of treatment at 3 years', 'description': 'overall survival rate in 3-years'}]}, 'oversightModule': {'oversightHasDmc': False}, 'conditionsModule': {'keywords': ['Esophageal Cancer; AI; prediction; prognosis'], 'conditions': ['Esophageal Cancer']}, 'referencesModule': {'references': [{'pmid': '41015514', 'type': 'RESULT', 'citation': 'Xia T, Peng S, Yang F, Wang X, Yao W. Data-driven models in locally advanced oesophageal cancer. Lancet. 2025 Sep 27;406(10510):1334-1335. doi: 10.1016/S0140-6736(25)01766-0. No abstract available.'}]}, 'descriptionModule': {'briefSummary': 'This AI-driven model leverages multimodal data-such as radiomics, pathomics, genomics, and broader multi-omics profiles-to capture complementary aspects of tumor biology and predict treatment response and prognosis.', 'detailedDescription': 'Built upon retrospective cohorts for model development and rigorously validated in prospective cohorts, the proposed AI predictive model integrates multimodal data (radiomics, pathomics, genomics, and multi-omics)-each reflecting distinct dimensions of tumor heterogeneity-to enable joint prediction of treatment response and clinical outcomes.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients diagnosed with esophgeal cancer and have received treatment in Tongji hospital', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Histopathologically diagnosed esophageal cancer\n2. Complete baseline clinical data available (including demographic characteristics, ECOG performance score, TNM staging, etc.)\n3. No other primary malignant tumors\n4. Provision of informed consent\n5. Availability of pre-treatment CT imaging\n\nExclusion Criteria:\n\n1. Imaging data quality insufficient for analysis\n2. Presence of another primary malignant tumor\n3. Severe systemic disease'}, 'identificationModule': {'nctId': 'NCT07354295', 'briefTitle': 'Integrating Multimodal AI to Predict Treatment Response and Refine Risk Stratification in Esophageal Cancer （Radiogenomics-Esophagus）', 'organization': {'class': 'OTHER', 'fullName': 'Tongji Hospital'}, 'officialTitle': 'Multimodal AI-based Therapy Response Prediction and Risk Stratification for Esophageal Cancer', 'orgStudyIdInfo': {'id': '4059393'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Surgical resection cohort', 'description': 'neither neoajuvant therapy nor anti-tumor treatment prior to surgery'}, {'label': 'neoadjuvant therapy cohort', 'description': 'received neoadjuvant therapy and esophagectomy'}, {'label': 'conservative treatment', 'description': 'concervative treatment includes chemo/immuno/radiotherapy and targeted theray'}, {'label': 'Endoscopic submucosal dissection (ESD)', 'description': 'Endoscopic submucosal dissection (ESD)'}]}, 'contactsLocationsModule': {'locations': [{'zip': '430030', 'city': 'Wuhan', 'state': 'Other (Non U.s.)', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Shu Peng, doctor', 'role': 'CONTACT', 'email': 'drpeng90@hotmail.com', 'phone': '+8618571716422'}, {'role': 'CONTACT', 'email': 'drpeng90@hotmail.com'}, {'name': 'Shu Peng, Doctor', 'role': 'PRINCIPAL_INVESTIGATOR'}], 'facility': 'Tongji hospital, Tongji medical college, Huazhong university of science and technology', 'geoPoint': {'lat': 30.58333, 'lon': 114.26667}}], 'centralContacts': [{'name': 'Shu Peng, Doctor', 'role': 'CONTACT', 'email': 'drpeng90@hotmail.com', 'phone': '+8618571716422'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': "In accordance with the institution's data confidentiality requirements"}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Shu Peng', 'class': 'OTHER'}, 'collaborators': [{'name': 'Union Hospital, Tongji Medical College, Huazhong University of Science and Technology', 'class': 'OTHER'}, {'name': 'The First Affiliated Hospital of Henan University of Science and Technology', 'class': 'OTHER'}, {'name': "Henan Provincial People's Hospital", 'class': 'OTHER'}, {'name': 'Zhongnan Hospital', 'class': 'OTHER'}, {'name': 'Renmin Hospital of Wuhan University', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR_INVESTIGATOR', 'investigatorTitle': 'Dr', 'investigatorFullName': 'Shu Peng', 'investigatorAffiliation': 'Tongji Hospital'}}}}