Ignite Creation Date:
2025-12-25 @ 2:32 AM
Ignite Modification Date:
2025-12-29 @ 1:15 PM
Study NCT ID:
NCT05425134
Status:
UNKNOWN
Last Update Posted:
2023-02-09
First Post:
2022-06-15
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Deep Learning Signature for Predicting Occult Nodal Metastasis of Clinical N0 Lung Cancer
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D002289', 'term': 'Carcinoma, Non-Small-Cell Lung'}, {'id': 'D008175', 'term': 'Lung Neoplasms'}, {'id': 'D008207', 'term': 'Lymphatic Metastasis'}], 'ancestors': [{'id': 'D002283', 'term': 'Carcinoma, Bronchogenic'}, {'id': 'D001984', 'term': 'Bronchial Neoplasms'}, {'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'}, {'id': 'D009362', 'term': 'Neoplasm Metastasis'}, {'id': 'D009385', 'term': 'Neoplastic Processes'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 5000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2022-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-02', 'completionDateStruct': {'date': '2023-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-02-07', 'studyFirstSubmitDate': '2022-06-15', 'studyFirstSubmitQcDate': '2022-06-15', 'lastUpdatePostDateStruct': {'date': '2023-02-09', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-06-21', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2023-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Area under the receiver operating characteristic curve', 'timeFrame': '2022.1-2023.12', 'description': 'Area under the receiver operating characteristic curve'}], 'secondaryOutcomes': [{'measure': 'Sensitivity Sensitivity', 'timeFrame': '2022.1-2023.12', 'description': 'Sensitivity'}, {'measure': 'Specificity', 'timeFrame': '2022.1-2023.12', 'description': 'Specificity'}, {'measure': 'Positive predictive value', 'timeFrame': '2022.1-2023.12', 'description': 'Positive predictive value'}, {'measure': 'Negative predictive value', 'timeFrame': '2022.1-2023.12', 'description': 'Negative predictive value'}, {'measure': 'Accuracy', 'timeFrame': '2022.1-2023.12', 'description': 'Accuracy'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Lung cancer', 'Lymph node metastasis', 'Deep learning', 'PET-CT'], 'conditions': ['Non-small Cell Lung Cancer']}, 'descriptionModule': {'briefSummary': 'The purpose of this study is to evaluate the performance of a PET/CT-based deep learning signature for predicting occult nodal metastasis of clinical stage N0 non-small cell lung cancer in a multicenter prospective cohort.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '75 Years', 'minimumAge': '20 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Clinica N0 Non-small Cell Lung Cancer', 'eligibilityCriteria': 'Inclusion Criteria:\n\n(1) Participants scheduled for surgery for radiological finding of pulmonary lesions from the preoperative thin-section CT scans; (2) The maximum short-axis diameter of N1 and N2 lymph nodes less than 1 cm on CT scan; (3) The SUVmax of N1 and N2 lymph nodes less than 2.5; (4) Pathological confirmation of primary NSCLC; (5) Age ranging from 20-75 years; (6) Obtained written informed consent.\n\nExclusion Criteria:\n\n(1) Multiple lung lesions; (2) Poor quality of PET-CT images; (3) Participants with incomplete clinical information; (4) Participants not receiving systematic lymph node dissection; (5) Participants who have received neoadjuvant therapy.'}, 'identificationModule': {'nctId': 'NCT05425134', 'briefTitle': 'Deep Learning Signature for Predicting Occult Nodal Metastasis of Clinical N0 Lung Cancer', 'organization': {'class': 'OTHER', 'fullName': 'Shanghai Pulmonary Hospital, Shanghai, China'}, 'officialTitle': 'PET/CT-based Deep Learning Signature for Predicting Occult Nodal Metastasis of Clinical Stage N0 Non-Small Cell Lung Cancer: A Multicenter Prospective Diagnostic Trial', 'orgStudyIdInfo': {'id': 'DLNMS'}}, 'armsInterventionsModule': {'interventions': [{'name': 'PET/CT-based Deep Learning Signature', 'type': 'DIAGNOSTIC_TEST', 'description': 'Deep Learning Signature Based on PET-CT for Predicting Occult Nodal Metastasis of Clinical N0 Non-small Cell Lung Cancer'}]}, 'contactsLocationsModule': {'locations': [{'city': 'Zunyi', 'state': 'Guizhou', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Yongxiang Song, Dr', 'role': 'CONTACT'}], 'facility': 'Affiliated Hospital of Zunyi Medical University', 'geoPoint': {'lat': 27.68667, 'lon': 106.90722}}, {'city': 'Nanchang', 'state': 'Jiangxi', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Bentong Yu, Dr', 'role': 'CONTACT'}], 'facility': 'The First Affiliated Hospital of Nanchang University', 'geoPoint': {'lat': 28.68396, 'lon': 115.85306}}, {'city': 'Yangpu', 'state': 'Shanghai Municipality', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Chang Chen, MD, PhD', 'role': 'CONTACT', 'email': 'chenthoracic@163.com', 'phone': '+86-021-65115006', 'phoneExt': '2074'}], 'facility': 'Shanghai Pulmonary Hospital', 'geoPoint': {'lat': 31.26193, 'lon': 121.51904}}, {'city': 'Ningbo', 'state': 'Zhejiang', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Minglei Yang, Dr', 'role': 'CONTACT'}], 'facility': 'Ningbo HwaMei Hospital', 'geoPoint': {'lat': 29.87819, 'lon': 121.54945}}], 'centralContacts': [{'name': 'Chang Chen, MD, PhD', 'role': 'CONTACT', 'email': 'chenthoracic@163.com', 'phone': '+86-021-65115006', 'phoneExt': '2074'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Shanghai Pulmonary Hospital, Shanghai, China', 'class': 'OTHER'}, 'collaborators': [{'name': 'Ningbo No.2 Hospital', 'class': 'OTHER'}, {'name': 'Zunyi Medical College', 'class': 'OTHER'}, {'name': 'The First Affiliated Hospital of Nanchang University', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'Chang Chen', 'investigatorAffiliation': 'Shanghai Pulmonary Hospital, Shanghai, China'}}}}