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Genetic Testing Could Improve Breast Cancer Prevention, Authors Say

Analysis combines questionnaire, genetic profiling, and mammography scans

Screening women for a wide range of known genetic risk factors could improve strategies for breast cancer prevention, a new analysis has shown.

Scientists at the Institute of Cancer Research in London and at the National Cancer Institute in Bethesda, Maryland, used mathematical models to show that analyzing genetic data, in combination with a range of other risk factors, could substantially improve the ability to identify women at highest risk of developing breast cancer.

Their study showed that prevention strategies could be improved not only by testing for major cancer-predisposition genes, such as BRCA1 and BRCA2 –– which identify a small percentage of women at very high risk –– but also by factoring in data on multiple gene variants that individually have only a small effect on risk but are more common in the population.

The new research was published November 13 in the Journal of the National Cancer Institute.  

The researchers stressed that their study was a computer-modeling analysis and would need to be confirmed by further research aimed at validating the models they used and by assessing real-life prevention approaches. But they also said that identifying women at highest risk using genetic and other factors could allow preventive treatments and tailored advice to be offered more effectively, potentially reducing the number of women who develop breast cancer. And genetic testing could be performed using currently available technology, they added.

In the study, the researchers modeled the potential risk stratification of eight hypothetical scenarios. Depending on the risk factors measured under each scenario, they used a mixture of a general practitioner- or self-administered questionnaire, genetic profiling, and mammography scans to measure breast-tissue density to calculate risk.

The risk factors were:

  • Genetic profile
  • Family history of breast cancer
  • Age at menarche
  • Number of births and age at first live birth
  • Oral contraceptive use
  • Use of combined menopausal therapy
  • Body mass index
  • Alcohol consumption
  • Smoking status
  • History of benign breast disease
  • Breast-tissue density

The most effective of the eight models at predicting breast cancer risk combined analyses of all of the risk factors. For instance, when applied to 50 year-old women, such a model could identify the most at-risk 10.2% of women –– who account for 32.2% of all breast cancer cases.

According to the authors, that means doctors would be able to tell an individual 50-year-old woman whether she was in the most at-risk 10% of the population –– and potentially identify lifestyle changes or preventive treatments that could reduce her risk, or provide better advice on the potential benefits and harms of taking hormone replacement therapy to reduce menopausal symptoms.

Sources: Institute of Cancer Research; November 13, 2014; and JNCI; November 13, 2014.

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