Screening Tool Artificial Intelligence-based for Predicting the Genetic Risk of BREAST Cancer (STAR-BREAST)
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- AstraZeneca
- 入组人数
- 800
- 试验地点
- 3
- 主要终点
- Agreement between AI tool results and genetic test results
研究概览
简要总结
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.
详细描述
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.
This 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.
CEGH/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.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 性别
- Female
- 接受健康志愿者
- 否
入选标准
- •female patients,
- •aged 18 years or older,
- •identified as high genetic risk by breast surgeons,
- •referred to a geneticist, and
- •who agree to participate in the study.
排除标准
- •male patients,
- •absence of complete information in the medical records,
- •patients unaware of their biological family history, and
- •patients who do not agree to participate in the study.
结局指标
主要结局
Agreement between AI tool results and genetic test results
时间窗: Through study completion, an average at one year.
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.
次要结局
- Evaluate the rate of agreement between the AI tool and the breast surgeon(Through study completion, an average at one year.)
- Agreement between hereditary breast cancer risk identified by the AI tool and the results of genetic testing.(Through study completion, an average at one year.)
- Describe the rate of family history profile of women at high risk for breast cancer(Through study completion, an average at one year.)
- Examine the rate of high penetrance variants(Through study completion, an average at one year.)
- Describe the rate of profile of patients with confirmed BRCA1 and BRCA2 variants(Through study completion, an average at one year.)
- Compare the rate of patient profiles between the two institutions(Through study completion, an average at one year.)