DESCRIPTION: Women with a high proportion of mammographically dense breast
tissue have a three to six-fold increased risk of developing breast cancer.
The percent of the breast that appears dense on a mammogram reflects the
proportion of stromal and epithelial tissue compared to fat, and varies
considerably among healthy women. In well-designed studies, the magnitude
of the breast cancer risk associated with increased mammographic density
exceeded that of most other predictors, and was independent of the
traditional breast cancer risk factors. The proposed study will expand the
current understanding of mammographic density and for the first time
evaluate the associations between plasma levels of endogenous hormones,
growth factors, insulin, cholesterol, nutrients and antioxidants with
mammographic density and breast cancer risk. This study benefits from the
prospective design and extensive information available for the subjects in
the ongoing case-control study of plasma biomarkers and breast cancer risk
(CA49449), nested within the Nurse's Health Study (CA40356). It is
estimated that both mammographic information and plasma biomarkers will be
available for 690 cases and 924 controls. Among these cases and controls
this study will determine if the breast cancer risk associated with
mammographic density is explained by the plasma levels of growth factors,
insulin, cholesterol, nutrients and antioxidants. Among the 233 cases and
466 controls who were postmenopausal and not using postmenopausal hormones
at the time of the blood donation, this study is intended to determine if
the breast cancer risk associated with mammographic density is partially
explained by the plasma levels of endogenous hormones. To assess
mammographic density this study will employ a newly developed method, which
is designed to determine the percent of the breast area with mammographic
density based on a texture analysis of the digitized image, capturing the
relation between stromal and epithelial tissue. As part of this study, the
new computerized system to assess mammographic features will be compared to
the existing techniques of assessing percent mammographic density: 1) a
visual assessment of percent density by a radiologist; 2) measured
assessment from the marked area of density; and 3) a computer-assisted
measure of percent density from a grey-scale based system.
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