BACKGROUND: The effect of changes in mammographic density over time on the risk of breast cancer remains inconclusive. METHODS: We used information from four centres of the Breast Cancer Screening Program in Spain in the period 1996-2015. We analysed individual level data from 117,388 women first screened age 50-54, with at least two screening examinations. Breast density was determined using the BI-RADS classification (A to D in increasing order) at earliest and latest screening examination. Adjusted ...
BACKGROUND: The effect of changes in mammographic density over time on the risk of breast cancer remains inconclusive. METHODS: We used information from four centres of the Breast Cancer Screening Program in Spain in the period 1996-2015. We analysed individual level data from 117,388 women first screened age 50-54, with at least two screening examinations. Breast density was determined using the BI-RADS classification (A to D in increasing order) at earliest and latest screening examination. Adjusted Poisson regression models were used to estimate the relative risk (RR) and 95% confidence intervals (95%CI) of the association between changes in mammographic density and breast cancer risk over time. RESULTS: During an average 5.8 years of follow-up, 1592 (1.36%) women had a breast cancer diagnosis. An increase in density category increased breast cancer risk, and a decrease in density decreased the risk, compared with women who remained in the same BI-RADS category. Women whose density category increased from B to C or B to D had a RR of 1.55 (95%CI = 1.24-1.94) and 2.32 (95%CI = 1.48-3.63), respectively. The RR for women whose density increased from C to D was 1.51 (95%CI = 1.03-2.22). Changes in BI-RADS density were similarly associated with the risk for invasive cancer than for ductal carcinoma in situ. CONCLUSIONS: Although a modest proportion of women changed BI-RADS density category, mammographic density changes modulated the risk of breast cancer and identified women at a differential risk. Using two longitudinal measures of BI-RADS density could help target women for risk-based screening strategies.
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