Longitudinal Study of Mammographic Density Measures That Predict Breast Cancer Risk

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 intervals of different lengths were estimated using nonlinear mixed-effects modeling of Gompertz curves. Results: Mean normalized DA and PDA were constant with age to the early 40s, decreased over the next two decades, and were almost constant fromthemid-60sonward. Mean normalizedNDA increased nonlinearly with age. After adjusting for age and BMI, the within-woman correlation estimates for normalizedDAwere 0.94, 0.93, 0.91, 0.91, and 0.91 formammograms taken 2, 4, 6, 8, and 10 years apart, respectively. Similar correlationswere estimated for the age-and BMI-adjusted normalized PDA and NDA. Conclusions: The mammographic measures that predict breast cancer risk are highly correlated over time. Impact: This has implications for etiologic research and clinical management whereby women at increased risk could be identified at a young age (e.g., early 40s or even younger) and recommended appropriate screening and prevention strategies. (C) 2017 AACR.