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 from the mid-60s onward. Mean normalized NDA increased nonlinearly with age. After adjusting for age and BMI, the within-woman correlation estimates for normalized DA were 0.94, 0.93, 0.91, 0.91, and 0.91 for mammograms taken 2, 4, 6, 8, and 10 years apart, respectively. Similar correlations were 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. Cancer Epidemiol Biomarkers Prev; 26(4); 651–60. ©2017 AACR .