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NCT Number: NCT07070128

Screening Tool Artificial Intelligence-based for Predicting the Genetic Risk of BREAST Cancer

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.

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Key information

Conditions

Breast Neoplasms Breast Diseases Neoplasms Neoplasms by Site Skin Diseases Skin and Connective Tissue Diseases

Sex eligibility

Female

Study type

Observational

Primary location

Research Site, Golania, Goiás, Brazil

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About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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.

Exclusion criteria

  • 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.

Treatment and study plan

Primary outcomes

  1. Agreement between AI tool results and genetic test results

    Time frame: 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.

Secondary outcomes

  1. Evaluate the rate of agreement between the AI tool and the breast surgeon

    Time frame: Through study completion, an average at one year.

    Comparison between the number of participants who were indicated to genetic counseling through the AI tool and according to the opinion of the mastologist

  2. Agreement between hereditary breast cancer risk identified by the AI tool and the results of genetic testing.

    Time frame: Through study completion, an average at one year.

    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.

  3. Describe the rate of family history profile of women at high risk for breast cancer

    Time frame: Through study completion, an average at one year.

    Describe the rate of family history profile of women at high risk for breast cancer

  4. Examine the rate of high penetrance variants

    Time frame: Through study completion, an average at one year.

    Examine the rate of high penetrance variants.

  5. Describe the rate of profile of patients with confirmed BRCA1 and BRCA2 variants

    Time frame: Through study completion, an average at one year.

    Describe the rate of profile of patients with confirmed BRCA1 and BRCA2 variants

  6. Compare the rate of patient profiles between the two institutions

    Time frame: Through study completion, an average at one year.

    Compare the rate of patients with pathogenic variants and genetic risk of breast cancer between the two institutions involved in the study.

Study contacts

Contact information is provided by the study sponsor or research team.

AstraZeneca Clinical Study Information Center

CONTACT

[email protected]

1-877-240-9479

Sponsors and collaborators

Lead sponsor

AstraZeneca

Industry

Registry information

Official study title

Screening Tool Artificial Intelligence-based for Predicting the Genetic Risk of BREAST Cancer (STAR-BREAST)

Acronym: STAR-BREAST

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Jul 17, 2025
Registry last updated
Jun 24, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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