The DOI matches its Crossref record.
Mammographic Features and Breast Cancer Risk: Effects With Time, Age, and Menopause Status
Abstract
BACKGROUND: Mammographic images from women with a high proportion of epithelial and stromal breast tissues are described as showing high-density parenchymal patterns. Most past studies that noted an increase in breast cancer risk associated with mammographic parenchymal patterns showing high density either 1) lacked information on other breast cancer risk factors, 2) were too small, or 3) included insufficient follow-up time to adequately resolve persisting doubts whether mammographic features are "independent" measures of breast cancer risk and not a detection artifact. PURPOSE: The purpose of this study was twofold: 1) to evaluate the associations between mammographic features and other breast cancer risk factors and 2) to assess effects of mammographic features on breast cancer risk by time, age, and menopause status. METHODS: To address these questions, we analyzed detailed information from a large, nested case-control study with 16 years of follow-up. This study used information from both screening and follow-up phases of the Breast Cancer Detection Demonstration Project, a nationwide program that offered annual breast cancer screening for more than 280,000 women from 1973 to 1980. Mammographic features were assessed from the base-line screening mammographic examination for 1880 incident case subjects and 2152 control subjects. Control subjects were randomly selected from women of the same age and race as each case subject. Control subjects attended the same screening center as the case subject and were free of breast cancer at the case subject's date of diagnosis. Odds ratios (ORs) with 95% confidence intervals (CIs) provided estimates of the relative risk of breast cancer. RESULTS: Mammographic features were associated with known breast cancer risk factors. However, the high-density parenchymal pattern effects were independent of family history, age at first birth, alcohol consumption, and benign breast disease. The increase risk for women with Wolfe's two high-density parenchymal patterns, P2 (OR = 3.2; 95% CI = 2.5-4.0) and Dy (OR = 2.9; 95% CI = 2.2-3.9), was explained primarily by measured percent of the breast with dense mammographic appearance. Compared with women with no visible breast density, women who had a breast density of 75% or greater had an almost fivefold increased risk of breast cancer (95% CI = 3.6-7.1). These effects persisted for 10 or more years and were noted for both premenopausal and postmenopausal women of all ages. CONCLUSIONS: Of the breast cancer risk factors assessed in the participants, high-density mammographic parenchymal patterns, as measured by the proportion of breast area composed of epithelial and stromal tissue, had the greatest impact on breast cancer risk. Of the breast cancers in this study, 28% were attributable to having 50% or greater breast density.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Diversity and biology of cancer-associated fibroblasts
Biffi, G., & Tuveson, D. A. (2021) · Physiological Reviews · doi:10.1152/physrev.00048.2019 · Cited by 1,265
The Nurses׳ Health Study: lifestyle and health among women
Colditz, G. A., & Hankinson, S. E. (2005) · Nature reviews. Cancer · doi:10.1038/nrc1608 · Cited by 590
Systematic Review: Using Magnetic Resonance Imaging to Screen Women at High Risk for Breast Cancer
Warner, E., Messersmith, H., Causer, P., Eisen, A., Shumak, R., & Plewes, D. (2008) · Annals of Internal Medicine · doi:10.7326/0003-4819-148-9-200805060-00007 · Cited by 564
Breast Tissue Composition and Susceptibility to Breast Cancer
Boyd, N. F., Martin, L. J., Bronskill, M., Yaffe, M. J., Duric, N., & Minkin, S. (2010) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djq239 · Cited by 478
An overview of mammographic density and its association with breast cancer
Nazari, S. S., & Mukherjee, P. (2018) · Breast Cancer · doi:10.1007/s12282-018-0857-5 · Cited by 298
Metadata
- Authors
- Byrne, C., Schairer, C., Wolfe, J., Parekh, N., Salane, M., Brinton, L. A., Hoover, R., & Haile, R.
- Venue
- JNCI Journal of the National Cancer Institute
- Publisher
- Oxford University Press (OUP)
- Published
- 1995-11-01
- Volume
- 87
- Issue
- 21
- Pages
- 1622-1629
- ISSN
- 0027-8874 (ISSN-L)
- 1460-2105
- OpenAlex
- W2330411228
- Cited by
- 864
- References
- 0
- FWCI
- 10.60
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Mammographic Features and Breast Cancer Risk: Effects With Time, Age, and Menopause Status. https://app.cochat.ai/papers/10.1093/jnci/87.21.1622
- The paper
- Byrne, C., Schairer, C., Wolfe, J., Parekh, N., Salane, M., Brinton, L. A., Hoover, R., & Haile, R. (1995). Mammographic Features and Breast Cancer Risk: Effects With Time, Age, and Menopause Status. JNCI Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/87.21.1622
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.