Evidence map›Paper›PMID 39593160›Full record

ArticleBreast cancer research : BCR2024

Longitudinal history of mammographic breast density and breast cancer risk by familial risk, menopausal status, and initial mammographic density level in a high risk cohort: a nested case-control study.

Parisa Tehranifar, Erica J Lee Argov, Shweta Athilat, Yuyan Liao, Ying Wei, Alexandra J White, Katie M O'Brien, Dale P Sandler, Mary Beth Terry

Abstract read
In one paragraph

Article in Breast cancer research : BCR, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Parisa TehranifarDepartment of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th Street, New York, NY, 10032, USA. pt140@columbia.edu.
Erica J Lee ArgovDepartment of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th Street, New York, NY, 10032, USA.
Shweta AthilatDepartment of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th Street, New York, NY, 10032, USA.
Yuyan LiaoDepartment of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th Street, New York, NY, 10032, USA.
Ying WeiDepartment of Biostatistics, Columbia University Mailman School of Public Health, New York, NY, USA.
Alexandra J WhiteEpidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.
Katie M O'BrienEpidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.
Dale P SandlerEpidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.
Mary Beth TerryDepartment of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th Street, New York, NY, 10032, USA.

Funding

Social and Environmental Determinants of Health EquityZIAES103325 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI JACKSON, CHANDRA · 2017 to 2025
$12.7M
Integrating Mammograms in Analyses of Genes and Environment in Sisters (IMAGES)U01CA203993 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI TEHRANIFAR, PARISA · 2017 to 2020
$1.8M
Intramural NIH HHS ZIA ES103325National Cancer Institute, United States U01CA203993NCI NIH HHS U01 CA203993NIEHS NIH HHS Z1A ES103325
6 · The paper itself

Abstract

backgroundElevated mammographic density is associated with increased breast cancer risk. However, the contribution of longitudinal changes in mammographic density to breast cancer risk beyond initial mammographic density levels, considering familial breast cancer risk and menopausal status, remains uncertain but holds important clinical implications.

methodsIn a nested case-control study within the Sister Study (323 cases, 899 controls; 12,095 mammograms), a cohort enriched for family history of breast cancer, we examined case-control status in relation to the largest annual change in percent density and dense area using mammograms available spanning 5.4 years, on average, using multivariable logistic regression and to the rate of mammographic density change using linear mixed-effects models. We considered effect modification by: mammographic density level of the earlier mammogram, the extent of family history, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation (BOADICEA) risk strata, and menopausal status.

resultsCases (diagnosed < 60 years) had greater initial percent density and dense area levels and a slower rate of decline in dense area than controls. Women with stable mammographic density (≤ 10% annual change) had an increased breast cancer risk as compared with women whose largest mammographic density change was > 10% annual decline (e.g., Odds Ratio (OR) 2.34, 95% Confidence Interval (CI) 1.63-3.37 for dense area). Increasing vs. decreasing dense area was also associated with elevated risk, especially in women with the highest dense area levels at the earlier mammogram (OR: 2.56, 95%CI 1.50-4.36). Although generally similar across menopausal and familial risk categories, the associations of MD change with risk appeared stronger in pre-menopausal and lower-risk women.

conclusionsWomen who maintain higher levels of mammographic density (i.e. do not decrease over time) or have increasing mammographic density over time have a higher risk of subsequent breast cancer than women with high mammographic density that decreases over time. These findings suggest potential for incorporating mammographic density trajectories in clinical risk assessment, and the importance of additional breast cancer monitoring in women not experiencing declines in mammographic density over time.

Indexed as

Breast DensityBreast NeoplasmsMammographyMenopauseAdultAgedCase-Control StudiesFemaleGenetic Predisposition to DiseaseHumansLongitudinal StudiesMiddle AgedRisk FactorsBreast cancerMammographic breast densityMammographyRisk prediction

Identifiers

PMID39593160
PMCPMC11590558

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.