Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 478

The DOI matches its Crossref record; 99 of the 99 references it cites were found in a registry or an index.

Breast Tissue Composition and Susceptibility to Breast Cancer

Open access
Boyd, N. F., Martin, L. J., Bronskill, M., Yaffe, M. J., Duric, N., Minkin, S.·2010·JNCI Journal of the National Cancer Institute

Abstract

Breast density, as assessed by mammography, reflects breast tissue composition. Breast epithelium and stroma attenuate x-rays more than fat and thus appear light on mammograms while fat appears dark. In this review, we provide an overview of selected areas of current knowledge about the relationship between breast density and susceptibility to breast cancer. We review the evidence that breast density is a risk factor for breast cancer, the histological and other risk factors that are associated with variations in breast density, and the biological plausibility of the associations with risk of breast cancer. We also discuss the potential for improved risk prediction that might be achieved by using alternative breast imaging methods, such as magnetic resonance or ultrasound. After adjustment for other risk factors, breast density is consistently associated with breast cancer risk, more strongly than most other risk factors for this disease, and extensive breast density may account for a substantial fraction of breast cancer. Breast density is associated with risk of all of the proliferative lesions that are thought to be precursors of breast cancer. Studies of twins have shown that breast density is a highly heritable quantitative trait. Associations between breast density and variations in breast histology, risk of proliferative breast lesions, and risk of breast cancer may be the result of exposures of breast tissue to both mitogens and mutagens. Characterization of breast density by mammography has several limitations, and the uses of breast density in risk prediction and breast cancer prevention may be improved by other methods of imaging, such as magnetic resonance or ultrasound tomography.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/jnci/djq239

Cites

99 of 99 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cites

Show all 99 references

Cited by

See all 478

Metadata

Authors
Boyd, N. F., Martin, L. J., Bronskill, M., Yaffe, M. J., Duric, N., & Minkin, S.
Venue
JNCI Journal of the National Cancer Institute
Published
2010-07-08
Volume
102
Issue
16
Pages
1224-1237
ISSN
  • 0027-8874 (ISSN-L)
  • 1460-2105
OpenAlex
W2147153911
Cited by
478
References
99
FWCI
17.96
Type
journal article
Language
en
Open access
bronze

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: Breast Tissue Composition and Susceptibility to Breast Cancer. https://app.cochat.ai/papers/10.1093/jnci/djq239
The paper
Boyd, N. F., Martin, L. J., Bronskill, M., Yaffe, M. J., Duric, N., & Minkin, S. (2010). Breast Tissue Composition and Susceptibility to Breast Cancer. JNCI Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/djq239

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.