Ignite Creation Date:
2025-12-24 @ 7:09 PM
Ignite Modification Date:
2025-12-30 @ 6:52 PM
Study NCT ID:
NCT04909957
Status:
UNKNOWN
Last Update Posted:
2022-01-19
First Post:
2021-01-26
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Prediction of Lymph Node Invasion for Prostate Adenocarcinoma
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 400}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2021-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-01', 'completionDateStruct': {'date': '2022-11-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2022-01-17', 'studyFirstSubmitDate': '2021-01-26', 'studyFirstSubmitQcDate': '2021-06-01', 'lastUpdatePostDateStruct': {'date': '2022-01-19', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-06-02', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-11-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Predicted risk of lymph-node involvement vs Briganti 2017', 'timeFrame': 'immediately after the intervention/procedure/surgery', 'description': 'Comparison between the predicted risk of lymph node involvement based on the new algorithm and the predicted risk with the Briganti 2017'}], 'secondaryOutcomes': [{'measure': 'Predicted risk of lymph-node involvement vs Briganti 2012, Briganti 2018, Briganti 2019 and MSKCC', 'timeFrame': 'immediately after the intervention/procedure/surgery', 'description': 'Comparison between the predicted risk of lymph node involvement based on the new algorithm and the predicted risk with the Briganti 2012, Briganti 2018, Briganti 2019 and MSKCC'}, {'measure': 'Biochemical recurrence free survival', 'timeFrame': 'immediately after the intervention/procedure/surgery', 'description': 'Prediction of Biochemical recurrence free survival'}, {'measure': 'Extra-prostatic disease', 'timeFrame': 'immediately after the intervention/procedure/surgery', 'description': 'Prediction of Extra-prostatic disease'}, {'measure': 'Seminal vesicle invasion', 'timeFrame': 'immediately after the intervention/procedure/surgery', 'description': 'Prediction of Seminal vesicle invasion'}, {'measure': 'Automatic segmentation of the index lesion', 'timeFrame': 'immediately after the intervention/procedure/surgery', 'description': 'Comparison between a manual segmentation of the index lesion and an automatic segmentation'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['MRI', 'Lymph node'], 'conditions': ['Adenocarcinoma of the Prostate']}, 'descriptionModule': {'briefSummary': 'Despite lymph node involvement (LNI) being one of the main prognostic factors in patients with prostate cancer (PCa), pelvic lymph node irradiation remains debated, possibly due to an insufficient selection of patients. Significant advances in LNI risk modelling have been achieved with the addition of visual interpretation of magnetic resonance imaging (MRI) data, but it is likely that quantitative analysis could further improve prediction models. In this study, the investigators aimed to develop and internally validate a novel LNI risk prediction model based on radiomic features extracted from pre-operative multimodal MRI.'}, 'eligibilityModule': {'sex': 'MALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'The population consists of patients operated on for an adenocarcinoma of the prostate by radical prostatectomy with extensive lymph node dissection and for whom pre-operative MRI is available and analyzable.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Histologically proven adenocarcinoma of the prostate treated by prostatectomy with extensive lymph node dissection\n* Available pre-operative +/- PET choline\n\nExclusion Criteria:\n\n* Unanalyzable pre-operative MRI'}, 'identificationModule': {'nctId': 'NCT04909957', 'acronym': 'PRED-NCHIR', 'briefTitle': 'Prediction of Lymph Node Invasion for Prostate Adenocarcinoma', 'organization': {'class': 'OTHER', 'fullName': 'University Hospital, Brest'}, 'officialTitle': 'Prediction of Lymph Node Invasion in Patients Operated on for Prostate Adenocarcinoma', 'orgStudyIdInfo': {'id': '29BRC20.0290'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Absence of invaded lymph node after extensive lymph node dissection', 'description': 'Absence of invaded lymph node after extensive lymph node dissection'}, {'label': 'Presence of invaded lymph node after extensive lymph node dissection', 'description': 'Presence of invaded lymph node after extensive lymph node dissection'}]}, 'contactsLocationsModule': {'locations': [{'zip': '29200', 'city': 'Brest', 'status': 'RECRUITING', 'country': 'France', 'contacts': [{'name': 'Ulrike Schick, MD, PhD', 'role': 'CONTACT', 'email': 'ulrike.schick@chu-brest.fr', 'phone': '+33298223398'}], 'facility': 'CHRU Brest', 'geoPoint': {'lat': 48.39029, 'lon': -4.48628}}], 'centralContacts': [{'name': 'Ulrike Ulrike Schick', 'role': 'CONTACT', 'email': 'ulrike.schick@chu-brest.fr', 'phone': '+33298223398'}]}, 'ipdSharingStatementModule': {'infoTypes': ['STUDY_PROTOCOL'], 'timeFrame': 'Data will be available beginning three month and ending five years following the publication', 'ipdSharing': 'YES', 'description': 'All collected data that underlie results in a publication', 'accessCriteria': 'Data access requests will be reviewed by the internal committee of Brest UH. Requestors will be required to sign and complete a data access agreement.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University Hospital, Brest', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}