Mammographic Density Change and Risk of Breast Cancer

Shadi Azam; Mikael Eriksson; Arvid Sjölander; Roxanna Hellgren; Marike Gabrielson; Kamila Czene; Per Hall

Disclosures

J Natl Cancer Inst. 2020;112(4):391-399. 

In This Article

Abstract and Introduction

Abstract

Background: We examined the association between annual mammographic density change (MDC) and breast cancer (BC) risk, and how annual MDC influences the association between baseline mammographic density (MD) and BC risk.

Methods: We used the Karolinska Mammography Project for Risk Prediction of Breast Cancer cohort of Swedish women (N = 43 810) aged 30–79 years with full access to BC risk factors and mammograms. MD was measured as dense area (cm2) and percent MD using the STRATUS method. We used the contralateral mammogram for women with BC and randomly selected a mammogram from either left or right breast for healthy women. We calculated relative area MDC between repeated examinations. Relative area MDC was categorized as decreased (>10% decrease per year), stable (no change), or increased (>10% increase per year). We used Cox proportional hazards regression to estimate the association of BC with MDC and interaction analysis to investigate how MDC modified the association between baseline MD and BC risk. All tests of statistical significance were two-sided.

Results: In all, 563 women were diagnosed with BC. Compared with women with a decreased MD over time, no statistically significant difference in BC risk was seen for women with either stable MD or increasing MD (hazard ratio = 1.01, 95% confidence interval = 0.82 to 1.23, P = .90; and hazard ratio = 0.98, 95% confidence interval = 0.80 to 1.22, P = .90, respectively). Categorizing baseline MD and subsequently adding MDC did not seem to influence the association between baseline MD and BC risk.

Conclusions: Our results suggest that annual MDC does not influence BC risk. Furthermore, MDC does not seem to influence the association between baseline MD and BC risk.

Introduction

Mammographic density (MD) is a strong risk factor for breast cancer (BC).[1,2] The dense part of the breast consists of epithelial tissue and stroma and appears bright on a mammogram, whereas fat tissue appears dark.[3] Women with mammograms where the dense tissue occupies more than 75% of a mammogram have a 4–6 times greater risk of BC compared with women with dense tissue occupying less than 5%.[1,4] Most studies on the association of MD and BC risk have involved only a single measure of density with a large variation in time between BC and time of last negative mammogram.[1,5] However, MD is a dynamic trait that typically declines with increasing age,[6] a physiological phenomenon called involution.[7,8] We have previously shown, on average, MD decreases by 1 cm2/y.[9] An apparent paradox is that MD decreases with age in most women whereas BC incidence increases. One explanation could be that MD change (MDC), rather than a MD measure at a single point in time, is a better measure of BC risk. Our hypothesis was that women who do not experience a density decrease over time have a higher risk of BC compared with women in whom a decrease is seen.

A few studies have evaluated the association between MDC and BC risk. However, the results are conflicting, and all previous studies have important limitations such as inability to investigate MDC and risk of BC among premenopausal women, because screening in most countries starts at the age of 50 years;[10–12] using retrospective case-control sampling, which is more susceptible to bias than the prospective cohort design;[10–13] using an obsolete imaging technique (screen-film mammography instead of full-field digital mammography);[10] using a semi-automated, reader-dependent measure of density;[11,14] not aligning images before density measures are performed;[15] and using a qualitative and crude measurement of MD (Breast Imaging Reporting and Data System [BI-RADS] score).[14]

In the current study, we were able to address all of these limitations. We investigated 43 810 women from the unique prospective Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort,[16] and used a novel approach when measuring density changes over time, to elucidate the association between MDC with age and risk of BC separated by menopausal status. Furthermore, we investigated if adding MDC to a single baseline measure of MD may be a better method to predict a woman's risk of BC than using a baseline measure alone.

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