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    • Subcategory of 'Diagnosis' designed to be very sensitiveRule Out
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    Chief Complaint


    Organ System


    Patent Pending

    Gail Model for Breast Cancer Risk

    Estimates risk for breast cancer based on demographic and clinical data.


    This calculator includes inputs based on race, which may or may not provide better estimates; this calculator can be run with Race as “Unknown,” but users should know this defaults to the “White” option. Our evidence section reviews some of the issues with Race in this model. See here for more on our approach to addressing race and bias on MDCalc.


    The Gail Model is for use in women with no history of breast cancer, DCIS or LCIS. Other tools may be more appropriate for women with known mutations in BRCA1, BRCA2, or other hereditary syndromes associated with breast cancer. See the Evidence section for more information.

    When to Use
    Why Use

    The Gail Model is one of several risk assessment models that can help determine the absolute 5 year risk and lifetime risk of developing breast cancer.

    • Other models include the Tyrer-Cuzick (also referred to as IBIS, International Breast Cancer Intervention Study) model, the Claus model, BRCAPro, and BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm).
    • The Gail Model for Breast Cancer risk estimates the absolute 5 year risk and lifetime risk of developing breast cancer.
    • Family history includes only first degree relatives with breast cancer, which is not enough information to estimate the risk of a patient having BRCA mutation. It also underestimates the cancer risk for patients with extensive family history.
    • The Gail Model is a good predictor of risk for populations but not for individuals.
    • It adjusts risk for race/ethnicity.
    • It may underestimate breast cancer risk in patients with atypical hyperplasia and strong family history.
    • The Gail Model was NOT designed to estimate risk for:
      • Women with a prior diagnosis of breast cancer, lobular carcinoma in situ (LCIS), or ductal carcinoma in situ (DCIS).
      • Women who have received previous radiation therapy to the chest for treatment of Hodgkin lymphoma.
      • Women with gene mutations in BRCA1 or BRCA2, or those who are known to have certain genetic syndromes that increase risk for breast cancer.
      • Women of age <35 or >85.

    It helps determine which risk-reduction options—medical (chemoprevention with tamoxifen), surgical (prophylactic mastectomy) or lifestyle changes only—are most appropriate for individual patients by weighing risks and benefits of intervention versus likelihood of developing cancer.

    7-11 years old
    12-13 years old
    >13 years old
    No births
    <20 years old
    20-24 years old
    25-29 years old
    ≥30 years old
    American-Indian/Alaskan Native


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    Next Steps
    Creator Insights
    Dr. Mitchell Gail

    About the Creator

    Mitchell Gail, MD, PhD, is an adjunct professor at Johns Hopkins University and a principal investigator at the National Cancer Institute Division of Cancer Epidemiology & Genetics, Biostatistics Branch. He is a former president of the American Statistical Association. He has won numerous awards, most notably the American Cancer Society Award for Research Excellence in Cancer Epidemiology and Prevention. His research focuses on creating models for determining absolute risk of diseases.

    To view Dr. Mitchell Gail's publications, visit PubMed

    Are you Dr. Mitchell Gail? Send us a message to review your photo and bio, and find out how to submit Creator Insights!
    MDCalc loves calculator creators – researchers who, through intelligent and often complex methods, discover tools that describe scientific facts that can then be applied in practice. These are real scientific discoveries about the nature of the human body, which can be invaluable to physicians taking care of patients.
    Content Contributors
    • Akiko Chiba, MD
    About the Creator
    Dr. Mitchell Gail
    Are you Dr. Mitchell Gail?
    Content Contributors
    • Akiko Chiba, MD