Ignite Creation Date:
2025-12-25 @ 1:25 AM
Ignite Modification Date:
2025-12-27 @ 7:00 AM
Study NCT ID:
NCT02810093
Status:
UNKNOWN
Last Update Posted:
2016-06-22
First Post:
2016-06-20
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Big Data and Text-mining Technologies Applied for Breast Cancer Medical Data Analysis
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001943', 'term': 'Breast Neoplasms'}], 'ancestors': [{'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D001941', 'term': 'Breast Diseases'}, {'id': 'D012871', 'term': 'Skin Diseases'}, {'id': 'D017437', 'term': 'Skin and Connective Tissue Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 10000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2016-05'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2016-06', 'completionDateStruct': {'date': '2016-12', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2016-06-20', 'studyFirstSubmitDate': '2016-06-20', 'studyFirstSubmitQcDate': '2016-06-20', 'lastUpdatePostDateStruct': {'date': '2016-06-22', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2016-06-22', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2016-11', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Validate the reliability of a computer-based, automatic information retrieval method specific to medical records from breast cancer multidisciplinary meetings', 'timeFrame': '6 months'}], 'secondaryOutcomes': [{'measure': 'Breast cancer recurrence rate after some therapeutic procedures', 'timeFrame': '6 months', 'description': 'Study of the recurrence rate of different subgroups of patients where various procedures were performed'}]}, 'oversightModule': {'oversightHasDmc': False}, 'conditionsModule': {'keywords': ['Breast cancer', 'Text mining', 'Big Data', 'Machine Learning'], 'conditions': ['Breast Cancer']}, 'referencesModule': {'references': [{'pmid': '37453367', 'type': 'DERIVED', 'citation': 'Simoulin A, Thiebaut N, Neuberger K, Ibnouhsein I, Brunel N, Vine R, Bousquet N, Latapy J, Reix N, Moliere S, Lodi M, Mathelin C. From free-text electronic health records to structured cohorts: Onconum, an innovative methodology for real-world data mining in breast cancer. Comput Methods Programs Biomed. 2023 Oct;240:107693. doi: 10.1016/j.cmpb.2023.107693. Epub 2023 Jun 25.'}]}, 'descriptionModule': {'briefSummary': 'Primary purpose :\n\nTo develop a method to automatically extract and structure the information included in numerous medical records from breast cancer patients.\n\nSecondary purpose :\n\nWith this procedure we can analyze the content of ten thousand anonymized textual medical records.\n\nThis information should enable us to explore many subjects, such as:\n\n* The impact of certain therapeutic procedures\n* The characteristics of sub-groups of patients\n* Pregnancy associated breast cancers\n* Risk factors'}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Patients (men and women) suffering from an in situ or invasive cancer treated at Hôpitaux Universitaires de Strasbourg between years 2000 and 2016.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Majority (age \\> 18)\n* Malignant breast tumors\n* signed informed consent\n\nExclusion Criteria:\n\n* Benign breast pathology\n* Patients not initially treated at the Hôpitaux Universitaires de Strasbourg'}, 'identificationModule': {'nctId': 'NCT02810093', 'acronym': 'SENOMETRY', 'briefTitle': 'Big Data and Text-mining Technologies Applied for Breast Cancer Medical Data Analysis', 'organization': {'class': 'OTHER', 'fullName': 'University Hospital, Strasbourg, France'}, 'officialTitle': 'SENOMETRY : Big Data and Text-mining Technologies Applied for Breast Cancer Medical Data Analysis', 'orgStudyIdInfo': {'id': '6373'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Breast cancer patients between 2000 and 2016', 'description': 'Patients treated for a breast cancer between 2000 and 2016 in the Hospital of Strasbourg (France).', 'interventionNames': ['Other: retrospective medical records analyze']}], 'interventions': [{'name': 'retrospective medical records analyze', 'type': 'OTHER', 'description': 'Ten thousand medical records (between years 2000 and 2016) will be analyzed', 'armGroupLabels': ['Breast cancer patients between 2000 and 2016']}]}, 'contactsLocationsModule': {'locations': [{'zip': '67091', 'city': 'Strasbourg', 'status': 'RECRUITING', 'country': 'France', 'contacts': [{'name': 'Carole Mathelin, MD', 'role': 'CONTACT', 'email': 'carole.mathelin.x@gmail.com', 'phone': '03 88 12 78 34'}, {'name': 'Karl Neuberger', 'role': 'CONTACT', 'email': 'kneuberger@quantmetry.com'}], 'facility': 'University Strasbourg Hospital', 'geoPoint': {'lat': 48.58392, 'lon': 7.74553}}], 'centralContacts': [{'name': 'Anne Laudamy', 'role': 'CONTACT', 'email': 'anne.laudamy@chru-strasbourg.fr', 'phone': '+33 3 88 11 66 88'}, {'name': 'anatta Razafimanantsoa', 'role': 'CONTACT', 'email': 'anatta.razafimanantsoa@chru-strasbourg.fr', 'phone': '+ 33 3 88 11 54 14'}], 'overallOfficials': [{'name': 'Carole Mathelin, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': "Strasbourg's University Hospitals"}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University Hospital, Strasbourg, France', 'class': 'OTHER'}, 'collaborators': [{'name': 'Quantmetry', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'SPONSOR'}}}}