Ignite Creation Date:
2025-12-26 @ 5:22 PM
Ignite Modification Date:
2025-12-29 @ 4:47 AM
Study NCT ID:
NCT06983106
Status:
COMPLETED
Last Update Posted:
2025-05-21
First Post:
2025-04-21
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Correlation Between Body Composition and Pathologic Grade/Prognosis in GEP-NENs: A Retrospective Study
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D018358', 'term': 'Neuroendocrine Tumors'}], 'ancestors': [{'id': 'D017599', 'term': 'Neuroectodermal Tumors'}, {'id': 'D009373', 'term': 'Neoplasms, Germ Cell and Embryonal'}, {'id': 'D009370', 'term': 'Neoplasms by Histologic Type'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D009380', 'term': 'Neoplasms, Nerve Tissue'}]}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2024-11-04', 'size': 138672, 'label': 'Study Protocol and Statistical Analysis Plan', 'hasIcf': False, 'hasSap': True, 'filename': 'Prot_SAP_000.pdf', 'typeAbbrev': 'Prot_SAP', 'uploadDate': '2025-04-15T13:08', 'hasProtocol': True}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 633}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2024-11-04', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-05', 'completionDateStruct': {'date': '2025-03-29', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2025-05-13', 'studyFirstSubmitDate': '2025-04-21', 'studyFirstSubmitQcDate': '2025-05-13', 'lastUpdatePostDateStruct': {'date': '2025-05-21', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-05-21', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-12-30', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Correlation between CT-measured abdominal fat index(cm3/m3) and pathological grade (WHO classification) in GEP-NENs', 'timeFrame': 'Preoperative contrast-enhanced CT performed within one month before surgery', 'description': 'Quantify abdominal visceral fat index(cm3/m3) ,subcutaneous fat index(cm3/m3) and intermuscular fat index(cm3/m3) using preoperative contrast-enhanced CT, and analyze their Pearson correlation coefficient with pathological grade (WHO classification: G1, G2, G3).'}], 'secondaryOutcomes': [{'measure': 'Correlation between CT-measured abdominal fat index(cm3/m3) and 10-year overall survival (days) in GEP-NENs', 'timeFrame': 'From baseline CT to 10-year follow-up or death', 'description': 'Quantify abdominal visceral fat index(cm3/m3) ,subcutaneous fat index(cm3/m3) and intermuscular fat index(cm3/m3) via preoperative CT, and analyze its Spearman correlation with overall survival (days from diagnosis to death) and progression-free survival (days from diagnosis to progression) using adjusted Cox proportional hazards models.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Neuroendocrine Tumors']}, 'descriptionModule': {'briefSummary': 'The goal of this observational study is to learn about the value of body composition as predictors of pathological grading and prognosis in patients with gastroenteropancreatic neuroendocrine neoplasms.\n\nThe main question it aims to answer is: Does body composition affect the pathological grading and prognosis of patients with gastroenteropancreatic neuroendocrine tumors? Participants with gastroenteropancreatic neuroendocrine neoplasms will answer questions about their physical condition during follow-up visits.', 'detailedDescription': 'Objectives To explore the value of body composition parameters (BCPs) as predictors of pathological grading, prognosis in patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs).\n\nMethods This retrospective multicenter analysis enrolled GEP-NENs patients pathologically confirmed from three institutions between 2015 and 2024. The volume of skeletal muscle and abdominal fat tissue was calculated based on CT scans at diagnosis. Univariate and multivariate logistic regression analyses were used to identify the relationships between BCPs and the pathological grade. The Kaplan-Meier method, along with the log-rank test, was employed for survival analysis. Independent prognostic factors were identified through uni- and multivariable Cox regression analyses.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'This retrospective multi-center study involved three separate medical centers. Data from April 2015 to April 2024 were obtained from the respective hospital information systems, with CT scan images retrieved from the Picture Archiving and Communication System. Patients were included based on the following criteria: (1) a confirmed diagnosis of GEP-NENs via histopathology with a WHO grading; (2) available enhanced CT scans that included full abdominal imaging before surgery or biopsy. The exclusion criteria were: (1) therapeutic interventions before surgery or biopsy; (2) poor image quality or incomplete CT images of the whole abdomen. The WHO grading was derived from the postoperative pathology reports, which were meticulously reviewed and certified by experienced senior pathologists.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* A confirmed diagnosis of GEP-NENs via histopathology with a WHO grading\n* Available enhanced CT scans that included full abdominal imaging before surgery or biopsy\n\nExclusion Criteria:\n\n* Therapeutic interventions before surgery or biopsy\n* Poor image quality or incomplete CT images of the whole abdomen'}, 'identificationModule': {'nctId': 'NCT06983106', 'acronym': 'GEP-NENs', 'briefTitle': 'Correlation Between Body Composition and Pathologic Grade/Prognosis in GEP-NENs: A Retrospective Study', 'organization': {'class': 'OTHER', 'fullName': 'Tongji Hospital'}, 'officialTitle': 'Value of Automatically Segmented Three-Dimensional(3D) Volumetric Body Composition in Predicting the Pathological Grading and Prognosis of Gastroenteropancreatic Neuroendocrine Neoplasms: A Multicenter Study', 'orgStudyIdInfo': {'id': 'TJ-IRB202411010'}}, 'armsInterventionsModule': {'interventions': [{'name': 'body composition calculate', 'type': 'OTHER', 'description': 'The goal of this observational study is to learn about the value of body composition as predictors of pathological grading and prognosis in patients with gastroenteropancreatic neuroendocrine neoplasms. The volume of abdominal skeletal muscle and fat tissue is calculated based on CT scans at diagnosis.'}]}, 'contactsLocationsModule': {'locations': [{'zip': '430030', 'city': 'Wuhan', 'state': 'Hubei', 'country': 'China', 'facility': 'Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology', 'geoPoint': {'lat': 30.58333, 'lon': 114.26667}}], 'overallOfficials': [{'name': 'Zhen Li, Dr', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Tongji Hospital'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Tongji Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'Zhen Li', 'investigatorAffiliation': 'Tongji Hospital'}}}}