Aims and objectives
Density is a recognized risk factor for breast cancer(1).This study aims to map density variation across a screening population and to identify demographic distinctions which may affect density and impact cancer development/detection.
we focus on impact of age on density,
ethnicity on density,
and deprivation index on density.
Methods and materials
This retrospective study on a screening population adheres to local patient confidentiality requirements.Breast density data was obtained from screening mammograms obtained from March 2013-September 2014.All mammograms were performed on Hologic Selenia and Dimensions machines (2011).
At the time of the study,the United Kingdom,
standard screening age was50-70.
After age 70,
women must self-refer to undergo screening.
Below age 50 (in practice,
below age 49),
women who are screened are from high risk groups.
Mammogram densities were measured using Volpara Density software...
32,685 screening records were evaluated (age range 41-90).
Figure2 shows thedistribution of the ages in the study according to prevalent versus incident screen.
The distribution reflects the parameters of the Southwest London United Kingdom screening program; during the time period of the study,
women ages 49-70 were invited for screening.
(Women younger than 49are most likely to be high risk and therefore enrolled in special screening protocols; women older than 70 areself-referred for screening.)
Age and Density
Breast density was plotted versus age...
Breast density is a knownrisk factor for breast cancer (1,6,7).
A variety of studies have suggested that certain demographic factors may be predictive of breast density and,
of breast cancer risk (8-12).
Our study focuses on teasing out therelationship between density and demographic characteristicswhich are readily obtainable through our screening program records,
and socioeconomic status/deprivation index.
this study is not a longitudinal study; instead,
it offers a snapshot view of density in a screening population at one moment in time....
The authors would like to acknowledge VolparaSolutions and Philips for their support.
Martin LJ et al.
Mammographic density and the risk and detection of breast cancer.N Engl J Med.
Shepherd J et al.
Digital mammographic density and breast cancer risk: a case inverted question markcontrol study of six alternative density assessment methods.Breast Cancer Res.
3.R Core Team.
R: A language and environment for statistical computing.
R Foundation forStatistical Computing,
2014 URL http://www.R-project.org/.
Write and Edit XLSX Files.http://CRAN.R-project.org/package=openxlsxWalker A.