Journal article
Explaining variance in the Cumulus mammographic measures that predict breast cancer risk: A twins and sisters study
TL Nguyen, DF Schmidt, E Makalic, GS Dite, J Stone, C Apicella, M Bui, RJ MacInnis, F Odefrey, JN Cawson, SA Treloar, MC Southey, GG Giles, JL Hopper
Cancer Epidemiology Biomarkers and Prevention | Published : 2013
Abstract
Background: Mammographic density, the area of the mammographic image that appears white or bright, predicts breast cancer risk. We estimated the proportions of variance explained by questionnaire-measured breast cancer risk factors and by unmeasured residual familial factors. Methods: For 544MZand 339 DZ twin pairs and 1,558 non-twin sisters from 1,564 families, mammographic density was measured using the computer-assisted method Cumulus. We estimated associations using multilevel mixed-effects linear regression and studied familial aspects using a multivariate normal model. Results: The proportions of variance explained by age, body mass index (BMI), and other risk factors, respectively, we..
View full abstractGrants
Awarded by Cooperative Research Centre for Discovery of Genes for Common Human Diseases, Australia under the Australian Government's Cooperative Research Centres program
Funding Acknowledgements
This study was supported by the National Health and Medical Research Council (NHMRC) of Australia, the National Breast Cancer Foundation, the Victorian Breast Cancer Research Consortium (VBCRC), Cancer Australia, the Victorian Health Promotion Foundation and the NSW Cancer Council, the Cooperative Research Centre for Discovery of Genes for Common Human Diseases, Australia (19972004) under the Australian Government's Cooperative Research Centres program, and Cerylid Biosciences Ltd. J.L. Hopper is an NHMRC Senior Principal Research Fellow, and M. Southey is an NHMRC Senior Research Fellow.