Predictors of Mammographic Density: Insights Gained from a Novel Regression Analysis of a Twin Study
Gillian S Dite, Lyle C Gurrin, Graham B Byrnes, Jennifer Stone, Anoma Gunasekara, Margaret RE McCredie, Dallas R English, Graham G Giles, Jennifer Cawson, Robert A Hegele, Anna M Chiarelli, Martin J Yaffe, Norman F Boyd, John L Hopper
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION | AMER ASSOC CANCER RESEARCH | Published : 2008
Understanding which factors influence mammographically dense and nondense areas is important because percent mammographic density adjusted for age is a strong, continuously distributed risk factor for breast cancer, especially when adjusted for weight or body mass index. Using computer-assisted methods, we measured mammographically dense areas for 571 monozygotic and 380 dizygotic Australian and North American twin pairs ages 40 to 70 years. We used a novel regression modeling approach in which each twin's measure of dense and nondense area was regressed against one or both of the twin's and co-twin's covariates. The nature of changes to regression estimates with the inclusion of the twin an..View full abstract
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Awarded by NATIONAL CANCER INSTITUTE
The studies were supported in Australia by grants from the Kathleen Cuningham Foundation (now the National Breast Cancer Foundation), the National Health and Medical Research Foundation, the Victorian Breast Cancer Research Consortium and the Merck Sharp and Dohme Research Foundation, and in North America by a grant from the Canadian Breast Cancer Research Initiative.