Oral Presentation Joint 2016 COSA and ANZBCTG Annual Scientific Meeting

Towards tailored screening: Should breast cancer screening programs routinely measure mammographic density? (#119)

Jennifer Stone 1 2
  1. Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, WA, Australia
  2. University of Western Australia, Perth

Background: The principal goal of breast cancer screening is early detection of disease in asymptomatic women leading to lower treatment costs and an eventual reduction in breast cancer mortality. Whilst population-based mammographic screening provides the best chances of early detection, not all women have an equal opportunity to achieve an earlier diagnosis. Women not only differ in terms of their underlying risk, but also the sensitivity of their mammogram to detect abnormalities. Thus, the benefit of screening varies widely throughout the population, with majority of women being at very low absolute risk, yet in Australia most women are screened the same way (every two years between ages 50 and 74). A stratified screening program - where women of different categories of risk are recommended different screening intervals or supplemental screening - may be a more efficient and cost-effective way of detecting breast cancer.  Key risk factors could be measured at screening to identify women at different categories of risk: mammographic density and known breast cancer susceptibility genetic variants.  

Methods: I will review the current evidence to support the implementation of mammographic density and genetic testing into Australian BreastScreen programs. 

Results: Mammographic density, the white appearance of parenchymal tissue on a mammogram, is one of the strongest predictors of breast cancer risk and significantly reduces the sensitivity of a mammogram. There is now commercially available software that provides automated reliable measures of mammographic density that strongly predict breast cancer risk. There has also been increasing advances in explaining the genetic variation in familial breast cancer risk and risk prediction modelling applicable to population based screening programs.

Conclusion: Systematic collection of mammographic density measurements and other important risk factors at the time of screening could facilitate a paradigm shift towards stratified breast cancer screening programs in Australia.