Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D008175', 'term': 'Lung Neoplasms'}], 'ancestors': [{'id': 'D012142', 'term': 'Respiratory Tract Neoplasms'}, {'id': 'D013899', 'term': 'Thoracic Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 150}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2024-07-02', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-07', 'completionDateStruct': {'date': '2027-07-02', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-01-09', 'studyFirstSubmitDate': '2024-07-08', 'studyFirstSubmitQcDate': '2024-07-08', 'lastUpdatePostDateStruct': {'date': '2025-01-13', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-07-15', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-07-02', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Correlation analysis of sequencing results and body composition', 'timeFrame': '0.5 year', 'description': 'Conducting correlation analysis between body composition and results of multi-omics sequencing'}, {'measure': 'Correlation analysis of sequencing results and tumor radiomic features', 'timeFrame': '0.5 year', 'description': 'Conducting correlation analysis between radiomic features and results of multi-omics sequencing'}], 'secondaryOutcomes': [{'measure': 'Constructing tumor microenvironment prediction model', 'timeFrame': '2 years', 'description': 'Constructing radiomic model to predict tumor microenvironment. The indicator is the area under the curve (AUC) of the prediction model'}, {'measure': 'Constructing a multi-dimensional prognostic prediction model', 'timeFrame': '3 years', 'description': 'A high-dimensional model was constructed to predict the prognosis of patients through multi-omics sequencing data, body composition, and tumor radiomic features. The indicator is the area under the curve (AUC) of the prediction model.'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Lung Cancer']}, 'descriptionModule': {'briefSummary': 'This is the prospective, observational cohort study (Radiogenomics-Lung), which aims to explore the relationship between the imaging information of lung cancer patients, tumor microenvironment and the prognosis of lung cancer patients.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients were treated for lung cancer', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Patients were treated for lung cancer in Wuhan Union Hospital from July 2024 to July 2027;\n2. Aged \\> 18 years old;\n3. At least one chest CT scan before treatment;\n4. Tissue biopsy pathological examination confirmed the diagnosis of the above tumors.\n\nExclusion Criteria:\n\n1. Poor image quality;\n2. Incomplete clinical data or loss of follow-up;\n3. Presence of another primary malignancy other than lung cancer;\n4. Unclear pathological diagnosis。'}, 'identificationModule': {'nctId': 'NCT06500312', 'briefTitle': 'Decoding the Association of Imaging and Tumor Microenvironment in Lung Cancer Using Radiogenomic Approach(Radiogenomics-Lung)', 'organization': {'class': 'OTHER', 'fullName': 'Union Hospital, Tongji Medical College, Huazhong University of Science and Technology'}, 'officialTitle': 'Assessment the Association of Imaging and Tumor Microenvironment in Lung Cancer With Radiogenomics', 'orgStudyIdInfo': {'id': '0482'}}, 'contactsLocationsModule': {'locations': [{'zip': '430000', 'city': 'Wuhan', 'state': 'Hubei', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Lian Yang', 'role': 'CONTACT', 'email': 'yanglian@hust.edu.cn', 'phone': '18986273791'}], 'facility': 'Union Hospital,Tongji Medical College,Huazhong University of Science and Technology', 'geoPoint': {'lat': 30.58333, 'lon': 114.26667}}], 'centralContacts': [{'name': 'Lian Yang', 'role': 'CONTACT', 'email': 'yanglian@hust.edu.cn', 'phone': '18986273791'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Union Hospital, Tongji Medical College, Huazhong University of Science and Technology', 'class': 'OTHER'}, 'collaborators': [{'name': "First Affiliated Hospital Xi'an Jiaotong University", 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}