Identifying High-Risk Female Patients

  • BBSG – Brazilian Breast Study Group


It is estimated that 75–80% of breast cancer cases originate in women with no risk factors for the disease. Only 10% of tumors are considered hereditary, and 10–15% have a positive family history (family cancer). However, identifying higher-risk patients is useful, as it allows selecting those cases that benefit from interventions while also reassuring those at low risk.

Recommended Reading

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    Berry DA, Parmigiani G, Sanchez J, Schildkraut J, Winer E. Probability of carrying a mutation of breast-ovarian cancer gene BRCA1 based on family history. J Natl Cancer Inst. 1997;89(3):227–38. BRCAPRO. Mathematical model with Bayesian theorem that calculates the risk of the proband to be a carrier of genetic mutation in the BRCA, later validated by diagnostic studiesCrossRefGoogle Scholar
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    Brentnall A, et al. Mammographic density adds accuracy to both the Tyrer-Cuzick and Gail breast cancer risk models in a prospective UK screening. Breast Cancer Res. 2015;17:147. A prospective study in the United Kingdom that analyzed breast density to improve the accuracy of Gail and Cuzick's risk models. The study included 50,628 patients with a follow-up of 3.2 years. In the univariate analysis, breast density impacted on the best accuracy of the Tyrer-Cuzick and Gail models in predicting cancer risk.CrossRefGoogle Scholar
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    Evans DG, Howell A. Breast cancer risk-assessment models. Breast Cancer Res. 2007;9:213–21. A review study comparing the efficacy of the major risk assessment models to calculate the onset of disease and the risk of BRCA mutation. In the first category, the best model was Tyrer-Cuzick (81%), followed by Claus (56%), BRCAPRO (49%) and Gail (48%). In the second, BRCAPRO is the most effective for BRCA 1 and Manchester for BRCA 2.CrossRefGoogle Scholar
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    Gail MH, Brinton LA, Byar DP, Corle DK, Green SB, Schairer C, et al. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst. 1989;81(24):1879–86. First report of Gail's model; case-control report in North American patients participating in a prevention study. Subsequently, Chlebowski et al. observed that it only predicted tumors with positive receptors. Another model for African Americans is suggested.CrossRefGoogle Scholar
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    NICE. 2013 – current UK guidance on the management of patients at high risk of breast cancer due to their family history. Guidelines on management and identification of high-risk patient for breast cancer.Google Scholar
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    Santen RJ, Boyd NF, Chlebowski RT, Cummings S, Cuzick J, Dowsett M, et al. Critical assessment of new risk factors for breast câncer: considerations for development of as improved risk prediction model. Endocr Relat Cancer. 2007;14:169–87. Review article that updates the main risk factors for breast cancer, mainly analyzing hormonal influence: dense breasts and plasma levels of free estrogen. It also includes personal factors (atypia and radiotherapy) and genetic factors.CrossRefGoogle Scholar
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    Tyrer J, Duffy SW, Cuzick J. A breast cancer prediction model incorporating familial and personal risk factors. Stat Med. 2004;23(7):1111–30. Model of Tyrer-Cuzick. Bayesian theorem that evaluates most known risks of breast cancer and calculates the risk for the disease and for being a mutation carrier in BRCACrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • BBSG – Brazilian Breast Study Group
    • 1
  1. 1.BBSGSão PauloBrazil

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