Gail Model for Breast Cancer Risk
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.
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.
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Patients who have an increased risk of developing breast cancer, defined as calculated 5 year risk >1.7%, are candidates for chemoprevention (such as tamoxifen).
Patients with elevated breast cancer risk (>1.7%) should be referred to a breast surgeon to discuss possible risk reduction interventions.
Facts & Figures
- The Gail Model is one of the oldest risk models—originally published in 1989—and well validated.
- These parameters were used as criteria for the National Surgical Adjuvant Breast and Bowel Project (NSABP) prevention trials to identify patients with increased risk of breast cancer (5 year risk of >1.7%).
- Lifetime risk estimates assume a life expectancy of 90 years.
- The original Gail model (also known as Gail model 1) was developed in 1989 using data derived from a subset of the Breast Cancer Detection Demonstration Project, a breast cancer screening program that ran from 1973 to 1980, and was initially designed to predict the risk of developing invasive cancer or carcinoma in situ.
- The Gail model was modified by statisticians (also known as Gail model 2) in order to predict the risk of invasive cancer specifically, and the modified version is the basis for the model that is widely used today.
- Both models were validated in 1999 for the National Surgical Adjuvant Breast and Bowel Project (NSABP) using data from the Breast Cancer Prevention Trial, based on data from 5,969 white women age 35 and older.
- Gail and colleagues carried out a case-control study in 2007 looking specifically at risk for black women, and found that the original model underestimated the risk in this population. They developed a model based on data from 1,607 black women with invasive breast cancer and 1,647 without in the Women's Contraceptive and Reproductive Experiences (CARE) Study and found that 30.3% of black women had elevated risk (using a cutoff of 1.66% for 5-year risk), compared with 14.5% as estimated by the previous tool. The Gail model now incorporates these findings to estimate risk for black women.
- Similarly, they developed a overestimate risk in this population. The Gail model now incorporates these findings to estimate risk for Asian and Pacific Islander American women.
- With regard to newer models, Amir and colleagues compared four different breast cancer risk assessment models in 1,933 patients and found that the Tyrer-Cuzick model was superior (the Gail model, Claus model, and BRCAPRO all underestimated risk).
Original/Primary ReferenceGail MH, Brinton LA, Byar DP, Corle DK, Green SB, Shairer C, Mulvihill JJ: Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 81(24):1879-86, 1989
ValidationCostantino JP, Gail MH, Pee D, Anderson S, Redmond CK, Benichou J, Wieand HS: Validation studies for models projecting the risk of invasive and total breast cancer incidence. J Natl Cancer Inst 91(18):1541-8, 1999.
Other ReferencesGail MH, Costantino JP, Bryant J, Croyle R, Freedman L, Helzlsouer K, Vogel V: Weighing the risks and benefits of tamoxifen treatment for preventing breast cancer. J Natl Cancer Inst 91(21):1829-46, 1999.Rockhill B, Spiegelman D, Byrne C, Hunter DJ, Colditz GA: Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst 93(5):358-66, 2001.Gail MH, Costantino JP, Pee D, Bondy M, Newman L, Selvan M, Anderson GL, Malone KE, Marchbanks PA, McCaskill-Stevens W, Norman SA, Simon MS, Spirtas R, Ursin G, and Bernstein L. Projecting Individualized Absolute Invasive Breast Cancer Risk in African American Women. J Natl Cancer Inst 99(23):1782-1792, 2007.Matsuno RK, Costantino JP, Ziegler RG, Anderson GL, Li H, Pee D, Gail MH. Projecting Individualized Absolute Invasive Breast Cancer Risk in Asian and Pacific Island American Women. J Natl Cancer Inst 2011.Amir E, Evans DG, Shenton A et al. Evaluation of breast cancer risk assessment packages in the family history evaluation and screening programme. J Med Genet. 2003;40:807-814Quante AS, Whittemore AS, Shriver T et al. Breast cancer risk assessment across the risk continuum: genetic and nongenetic risk factors contributing to differential model performance. Breast Cancer Res. 2012 Nov 5;14(6):R144Banegas MP, Gail MH, LaCroix A, Thompson B, Martinez ME, Wactawski-Wende J, John EM, Hubbell FA, Yasmeen S, Katki HA. Evaluating breast cancer risk projections for Hispanic women. Breast Cancer Res Treat. 2012 Feb;132(1):347-53.Kaur JS, Roubidoux MA, Sloan J, Novotny P. Can the Gail model be useful in American Indian and Alaska Native populations? Cancer. 2004 Mar 1;100(5):906-12
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
- Akiko Chiba, MD