Ignite Creation Date:
2025-12-26 @ 11:14 AM
Ignite Modification Date:
2026-01-01 @ 6:00 AM
Study NCT ID:
NCT07070128
Status:
RECRUITING
Last Update Posted:
2025-12-03
First Post:
2025-04-16
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Screening Tool Artificial Intelligence-based for Predicting the Genetic Risk of BREAST Cancer
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': 'PROSPECTIVE', 'observationalModel': 'OTHER'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 800}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-08-20', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-11', 'completionDateStruct': {'date': '2026-08-11', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-11-26', 'studyFirstSubmitDate': '2025-04-16', 'studyFirstSubmitQcDate': '2025-07-15', 'lastUpdatePostDateStruct': {'date': '2025-12-03', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-07-17', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-08-11', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Agreement between AI tool results and genetic test results', 'timeFrame': 'Through study completion, an average at one year.', 'description': 'Implement the use of an artificial intelligence (AI)-based tool, WeConecta, to predict the genetic risk of hereditary breast cancer in women treated at a private and public institution, including analyses of the sensitivity, specificity, and positive and negative predictive values of the tool in comparison with the results of the genetic test. Hypothesis: The artificial intelligence (AI)-based tool may present a strong level of agreement regarding the indication for genetic counseling in relation to the indication of mastologists, impacting genetic testing.'}], 'secondaryOutcomes': [{'measure': 'Evaluate the rate of agreement between the AI tool and the breast surgeon', 'timeFrame': 'Through study completion, an average at one year.', 'description': 'Comparison between the number of participants who were indicated to genetic counseling through the AI tool and according to the opinion of the mastologist'}, {'measure': 'Agreement between hereditary breast cancer risk identified by the AI tool and the results of genetic testing.', 'timeFrame': 'Through study completion, an average at one year.', 'description': 'To assess how many patients were identified by the AI tool as having "hereditary breast cancer risk" and how closely they agreed with the actual number obtained from genetic testing results.'}, {'measure': 'Describe the rate of family history profile of women at high risk for breast cancer', 'timeFrame': 'Through study completion, an average at one year.', 'description': 'Describe the rate of family history profile of women at high risk for breast cancer'}, {'measure': 'Examine the rate of high penetrance variants', 'timeFrame': 'Through study completion, an average at one year.', 'description': 'Examine the rate of high penetrance variants.'}, {'measure': 'Describe the rate of profile of patients with confirmed BRCA1 and BRCA2 variants', 'timeFrame': 'Through study completion, an average at one year.', 'description': 'Describe the rate of profile of patients with confirmed BRCA1 and BRCA2 variants'}, {'measure': 'Compare the rate of patient profiles between the two institutions', 'timeFrame': 'Through study completion, an average at one year.', 'description': 'Compare the rate of patients with pathogenic variants and genetic risk of breast cancer between the two institutions involved in the study.'}]}, 'conditionsModule': {'keywords': ['Breast Cancer', 'Artificial Intelligence', 'Genetic Risk'], 'conditions': ['Breast Neoplasms']}, 'descriptionModule': {'briefSummary': "It is a retrospective observational study that will include female patients aged 18 years or older, who were treated between 2017 and 2024, in both public and private institutions, and identified as at high genetic risk by breast specialists and referred to a geneticist. The artificial intelligence-based tool to be used in this study is developed by the startup WeConecta, which will collect data via WhatsApp about the patients' family cancer history with the aim of predicting the genetic risk of developing breast cancer.", 'detailedDescription': 'This is an observational retrospective study. Patients considered by mastologists to be at genetic risk and who have undergone genetic testing with a geneticist will have their electronic medical records reviewed and, if eligible for the study, will answer questions conducted by the virtual assistant using AI about their family history of cancer.\n\nThis study will be conducted in two centers. The first is the Breast Center at Hospital Moinhos de Vento, designated as the coordinating center, located in Porto Alegre, Rio Grande do Sul, Brazil. It is a private center composed of a multidisciplinary team dedicated to breast health care, from routine exams for early detection of malignant tumors, diagnosis, comprehensive treatment at different stages of the disease, to post-treatment follow-up. The second center, designated as a participant, is the Human Genetics Center (CEGH/ICB), located in Goiânia, Brazil. This entity works interdisciplinarily and is linked to the Institute of Biological Sciences at the Federal University of Goiás (UFG), with the aim of developing activities in diagnosis, education, research, and outreach in the field of human genetics.\n\nCEGH/ICB is a public institution that serves women with breast cancer from the Unified Health System (SUS), and its role in the research is to share collected data from the population of interest with the coordinating center.'}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Convenience sampling will be performed, inviting all women treated at both institutions from January 2017 to June 2024 who have been considered by breast surgeons as genetic risk patients and have undergone genetic testing with a geneticist, regardless of whether they have invasive breast carcinoma.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* female patients,\n* aged 18 years or older,\n* identified as high genetic risk by breast surgeons,\n* referred to a geneticist, and\n* who agree to participate in the study.\n\nExclusion Criteria:\n\n* male patients,\n* absence of complete information in the medical records,\n* patients unaware of their biological family history, and\n* patients who do not agree to participate in the study.'}, 'identificationModule': {'nctId': 'NCT07070128', 'acronym': 'STAR-BREAST', 'briefTitle': 'Screening Tool Artificial Intelligence-based for Predicting the Genetic Risk of BREAST Cancer', 'organization': {'class': 'INDUSTRY', 'fullName': 'AstraZeneca'}, 'officialTitle': 'Screening Tool Artificial Intelligence-based for Predicting the Genetic Risk of BREAST Cancer (STAR-BREAST)', 'orgStudyIdInfo': {'id': 'D0817R00113'}}, 'contactsLocationsModule': {'locations': [{'zip': '74605-020', 'city': 'Golania', 'state': 'Goiás', 'status': 'WITHDRAWN', 'country': 'Brazil', 'facility': 'Research Site'}, {'zip': '90035-001', 'city': 'Porto Alegre', 'state': 'Rio Grande do Sul', 'status': 'RECRUITING', 'country': 'Brazil', 'facility': 'Research Site', 'geoPoint': {'lat': -30.03283, 'lon': -51.23019}}, {'zip': '90035-903', 'city': 'Porto Alegre', 'state': 'Rio Grande do Sul', 'status': 'NOT_YET_RECRUITING', 'country': 'Brazil', 'facility': 'Research Site', 'geoPoint': {'lat': -30.03283, 'lon': -51.23019}}], 'centralContacts': [{'name': 'AstraZeneca Clinical Study Information Center', 'role': 'CONTACT', 'email': 'information.center@astrazeneca.com', 'phone': '1-877-240-9479'}]}, 'ipdSharingStatementModule': {'url': 'https://vivli.org/', 'infoTypes': ['STUDY_PROTOCOL', 'SAP'], 'timeFrame': 'AstraZeneca will meet or exceed data availability as per the commitments made to the EFPIA/PhRMA Data-Sharing Principles. For details of our timelines, please refer to our disclosure commitment at https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.', 'ipdSharing': 'YES', 'description': 'Qualified researchers can request access to anonymized individual patient-level data from AstraZeneca group of companies sponsored clinical trials via the request portal Vivli.org. All requests will be evaluated as per the AZ disclosure commitment: https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.\n\n"Yes", indicates that AZ are accepting requests for IPD, but this does not mean all requests will be approved.', 'accessCriteria': 'When a request has been approved AstraZeneca will provide access to the anonymized individual patient-level data via secure research environment Vivli.org. A Signed Data Usage Agreement (non-negotiable contract for data accessors) must be in place before accessing requested information.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'AstraZeneca', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}