Ignite Creation Date:
2025-12-25 @ 2:22 AM
Ignite Modification Date:
2025-12-27 @ 11:44 PM
Study NCT ID:
NCT06088134
Status:
RECRUITING
Last Update Posted:
2025-05-31
First Post:
2023-10-12
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D002292', 'term': 'Carcinoma, Renal Cell'}], 'ancestors': [{'id': 'D000230', 'term': 'Adenocarcinoma'}, {'id': 'D002277', 'term': 'Carcinoma'}, {'id': 'D009375', 'term': 'Neoplasms, Glandular and Epithelial'}, {'id': 'D009370', 'term': 'Neoplasms by Histologic Type'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D007680', 'term': 'Kidney Neoplasms'}, {'id': 'D014571', 'term': 'Urologic Neoplasms'}, {'id': 'D014565', 'term': 'Urogenital Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D052776', 'term': 'Female Urogenital Diseases'}, {'id': 'D005261', 'term': 'Female Urogenital Diseases and Pregnancy Complications'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D007674', 'term': 'Kidney Diseases'}, {'id': 'D014570', 'term': 'Urologic Diseases'}, {'id': 'D052801', 'term': 'Male Urogenital Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 800}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2022-09-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-05', 'completionDateStruct': {'date': '2025-08-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-05-27', 'studyFirstSubmitDate': '2023-10-12', 'studyFirstSubmitQcDate': '2023-10-12', 'lastUpdatePostDateStruct': {'date': '2025-05-31', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-10-18', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-06-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'disease-free survival (DFS)', 'timeFrame': 'recruitment occurred between June 2013 and March 2020', 'description': 'the interval from the date of surgery to disease recurrence, all-cause mortality or the last visit'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Clear Cell Renal Cell Carcinoma', 'Prognostic Cancer Model', 'Recurrent Renal Cell Cancer']}, 'referencesModule': {'references': [{'pmid': '38896853', 'type': 'DERIVED', 'citation': 'Xv Y, Wei Z, Jiang Q, Zhang X, Chen Y, Xiao B, Yin S, Xia Z, Qiu M, Li Y, Tan H, Xiao M. Three-dimensional deep learning model complements existing models for preoperative disease-free survival prediction in localized clear cell renal cell carcinoma: a multicenter retrospective cohort study. Int J Surg. 2024 Nov 1;110(11):7034-7046. doi: 10.1097/JS9.0000000000001808.'}]}, 'descriptionModule': {'briefSummary': "This study aims to preoperatively predict DFS of patients with localised ccRCC using a deep learning prognostic model based on enhanced contrast CT images, validate it's predictive ability in multicentre data and compare it's predictive ability with traditional models."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients admitted to urology departments at participating medical centres', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* underwent partial/radical nephrectomies\n* histologically diagnosed as ccRCC\n* with complete clinical data and preoperative CT image data\n\nExclusion Criteria:\n\n* with incomplete clinic-pathological data\n* lack of preoperative contrast-enhanced CT images or the image quality was unsuitable for analysis\n* who received pre-surgery neoadjuvant or adjuvant therapies\n* with multiple renal tumors or/and had synchronous metastasis'}, 'identificationModule': {'nctId': 'NCT06088134', 'briefTitle': 'Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)', 'organization': {'class': 'OTHER', 'fullName': 'First Affiliated Hospital of Chongqing Medical University'}, 'officialTitle': 'Urology Department of the First Affiliated Hospital of Chongqing Medical University', 'orgStudyIdInfo': {'id': 'DL-ccRCC'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Non-recurrence group'}, {'label': 'Recurrence group'}]}, 'contactsLocationsModule': {'locations': [{'zip': '400016', 'city': 'Chongqing', 'state': 'Chongqing Municipality', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Yingjie Xv', 'role': 'CONTACT', 'email': 'xvyingjiecq@qq.com', 'phone': '83-18725891425'}], 'facility': 'Yingjie Xv', 'geoPoint': {'lat': 29.56026, 'lon': 106.55771}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Mingzhao Xiao', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR_INVESTIGATOR', 'investigatorTitle': 'Urology Department', 'investigatorFullName': 'Mingzhao Xiao', 'investigatorAffiliation': 'First Affiliated Hospital of Chongqing Medical University'}}}}