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

被引:0
|
作者
Jessica A. Cintolo-Gonzalez
Danielle Braun
Amanda L. Blackford
Emanuele Mazzola
Ahmet Acar
Jennifer K. Plichta
Molly Griffin
Kevin S. Hughes
机构
[1] Massachusetts General Hospital,Division of Surgical Oncology
[2] Harvard University T H Chan School of Public Health,Department of Biostatistics
[3] Dana-Farber Cancer Institute,Department of Biostatistics and Computational Biology
[4] Johns Hopkins University School of Medicine,Department of Oncology
[5] Duke University Health Systems,undefined
来源
Breast Cancer Research and Treatment | 2017年 / 164卷
关键词
Risk assessment; Risk Models; Breast Cancer Screening;
D O I
暂无
中图分类号
学科分类号
摘要
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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页码:263 / 284
页数:21
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