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Breast cancer risk models: a comprehensive overview of existing models, validation, and clinical applications.

Publication ,  Journal Article
Cintolo-Gonzalez, JA; Braun, D; Blackford, AL; Mazzola, E; Acar, A; Plichta, JK; Griffin, M; Hughes, KS
Published in: Breast Cancer Res Treat
July 2017

Numerous models have been developed to quantify the combined effect of various risk factors to predict either risk of developing breast cancer, risk of carrying a high-risk germline genetic mutation, specifically in the BRCA1 and BRCA2 genes, or the risk of both. These breast cancer risk models can be separated into those that utilize mainly hormonal and environmental factors and those that focus more on hereditary risk. Given the wide range of models from which to choose, understanding what each model predicts, the populations for which each is best suited to provide risk estimations, the current validation and comparative studies that have been performed for each model, and how to apply them practically is important for clinicians and researchers seeking to utilize risk models in their practice. This review provides a comprehensive guide for those seeking to understand and apply breast cancer risk models by summarizing the majority of existing breast cancer risk prediction models including the risk factors they incorporate, the basic methodology in their development, the information each provides, their strengths and limitations, relevant validation studies, and how to access each for clinical or investigative purposes.

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Published In

Breast Cancer Res Treat

DOI

EISSN

1573-7217

Publication Date

July 2017

Volume

164

Issue

2

Start / End Page

263 / 284

Location

Netherlands

Related Subject Headings

  • Risk Factors
  • Risk Assessment
  • Oncology & Carcinogenesis
  • Models, Statistical
  • Humans
  • Germ-Line Mutation
  • Genetic Predisposition to Disease
  • Female
  • Confounding Factors, Epidemiologic
  • Breast Neoplasms
 

Citation

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Cintolo-Gonzalez, J. A., Braun, D., Blackford, A. L., Mazzola, E., Acar, A., Plichta, J. K., … Hughes, K. S. (2017). Breast cancer risk models: a comprehensive overview of existing models, validation, and clinical applications. Breast Cancer Res Treat, 164(2), 263–284. https://doi.org/10.1007/s10549-017-4247-z
Cintolo-Gonzalez, Jessica A., Danielle Braun, Amanda L. Blackford, Emanuele Mazzola, Ahmet Acar, Jennifer K. Plichta, Molly Griffin, and Kevin S. Hughes. “Breast cancer risk models: a comprehensive overview of existing models, validation, and clinical applications.Breast Cancer Res Treat 164, no. 2 (July 2017): 263–84. https://doi.org/10.1007/s10549-017-4247-z.
Cintolo-Gonzalez JA, Braun D, Blackford AL, Mazzola E, Acar A, Plichta JK, et al. Breast cancer risk models: a comprehensive overview of existing models, validation, and clinical applications. Breast Cancer Res Treat. 2017 Jul;164(2):263–84.
Cintolo-Gonzalez, Jessica A., et al. “Breast cancer risk models: a comprehensive overview of existing models, validation, and clinical applications.Breast Cancer Res Treat, vol. 164, no. 2, July 2017, pp. 263–84. Pubmed, doi:10.1007/s10549-017-4247-z.
Cintolo-Gonzalez JA, Braun D, Blackford AL, Mazzola E, Acar A, Plichta JK, Griffin M, Hughes KS. Breast cancer risk models: a comprehensive overview of existing models, validation, and clinical applications. Breast Cancer Res Treat. 2017 Jul;164(2):263–284.
Journal cover image

Published In

Breast Cancer Res Treat

DOI

EISSN

1573-7217

Publication Date

July 2017

Volume

164

Issue

2

Start / End Page

263 / 284

Location

Netherlands

Related Subject Headings

  • Risk Factors
  • Risk Assessment
  • Oncology & Carcinogenesis
  • Models, Statistical
  • Humans
  • Germ-Line Mutation
  • Genetic Predisposition to Disease
  • Female
  • Confounding Factors, Epidemiologic
  • Breast Neoplasms