Breast cancer risk models: a comprehensive overview of existing models, validation, and clinical applications View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-07

AUTHORS

Jessica A. Cintolo-Gonzalez, Danielle Braun, Amanda L. Blackford, Emanuele Mazzola, Ahmet Acar, Jennifer K. Plichta, Molly Griffin, Kevin S. Hughes

ABSTRACT

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. More... »

PAGES

263-284

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10549-017-4247-z

    DOI

    http://dx.doi.org/10.1007/s10549-017-4247-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1085066438

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28444533


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