Assessing women at high risk of breast cancer: a review of risk assessment models

  • Amir E
  • Freedman O
  • Seruga B
 et al. 
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Women who are at high risk of breast cancer can be offered more intensive surveillance or prophylactic measures, such as surgery or chemoprevention. Central to decisions regarding the level of prevention is accurate and individualized risk assessment. This review aims to distill the diverse literature and provide practicing clinicians with an overview of the available risk assessment methods. Risk assessments fall into two groups: the risk of carrying a mutation in a high-risk gene such as BRCA1 or BRCA2 and the risk of developing breast cancer with or without such a mutation. Knowledge of breast cancer risks, taken together with the risks and benefits of the intervention, is needed to choose an appropriate disease management strategy. A number of models have been developed for assessing these risks, but independent validation of such models has produced variable results. Some models are able to predict both mutation carriage risks and breast cancer risk; however, to date, all are limited by only moderate discriminatory accuracy. Further improvements in the knowledge of how to best integrate both new risk factors and newly discovered genetic variants into these models will allow clinicians to more accurately determine which women are most likely to develop breast cancer. These steady and incremental improvements in models will need to undergo revalidation.

Author-supplied keywords

  • *Germ-Line Mutation
  • *Models, Statistical
  • *Population Surveillance
  • Breast Diseases/pathology/radiography
  • Breast Neoplasms/*epidemiology/*etiology/genetics/
  • Confounding Factors (Epidemiology)
  • Decision Support Techniques
  • Female
  • Genes, BRCA1
  • Genes, BRCA2
  • Genetic Predisposition to Disease
  • Genetic Testing
  • Humans
  • Mammography
  • Mass Screening/methods
  • Predictive Value of Tests
  • Reproduction
  • Risk Assessment
  • Risk Factors
  • Time Factors

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  • E Amir

  • O C Freedman

  • B Seruga

  • D G Evans

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