Journal article
Longitudinal study of mammographic density measures that predict breast cancer risk
K Krishnan, L Baglietto, J Stone, JA Simpson, G Severi, CF Evans, RJ MacInnis, GG Giles, C Apicella, JL Hopper
Cancer Epidemiology Biomarkers and Prevention | AMER ASSOC CANCER RESEARCH | Published : 2017
Abstract
Background: After adjusting for age and body mass index (BMI), mammographic measures-dense area (DA), percent dense area (PDA), and nondense area (NDA)-are associated with breast cancer risk. Our aim was to use longitudinal data to estimate the extent to which these risk-predicting measures track over time. Methods: We collected 4,320 mammograms (age range, 24-83 years) from 970 women in the Melbourne Collaborative Cohort Study and the Australian Breast Cancer Family Registry. Women had on average 4.5 mammograms (range, 1-14). DA, PDA, and NDA were measured using the Cumulus software and normalized using the Box-Cox method. Correlations in the normalized risk-predicting measures over time in..
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Grants
Awarded by National Cancer Institute
Funding Acknowledgements
The MCCS was supported by the Victorian Breast Cancer Research Consortium, the National Health and Medical Research Council (251533, 209057, and 504711), the Victorian Health Promotion Foundation, and the National Breast Cancer Foundation and was further supported by infrastructure provided by the Cancer Council Victoria. The ABCFR was supported by grant UM1 CA164920 from the U.S. National Cancer Institute. K. Krishnan is supported by the John and Allan Gilmour Research Award and May Stewart Bursary scholarships. L. Baglietto is supported by a Marie Curie International Incoming Fellowship within the 7th European Community Framework Programme. J.L. Hopper is a Principal Research Fellow of the National Health and Medical Research Council. J. Stone is supported by a Postdoctoral Research Fellowship from the National Breast Cancer Foundation.