ArticleJAMA oncology2017
Population-Attributable Risk Proportion of Clinical Risk Factors for Breast Cancer.
Article in JAMA oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 135 papers, 7 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
135 citing papers in PubMed, 7 syntheses or guidelines pooled it, 222 citations in OpenAlex.
- Overweight and obesity increase breast cancer risk in postmenopausal women: a meta-analysis of 38 observational studies.GeroScience · 2026Pooled it
- Targeting Ferroptosis as the Achilles' Heel of Breast Cancer: Mechanisms and Therapeutic Opportunities from a Comprehensive Systematic Review.International journal of molecular sciences · 2025Pooled it
- Screening for breast cancer: a systematic review update to inform the Canadian Task Force on Preventive Health Care guideline.Systematic reviews · 2024Pooled it
- Artificial Intelligence-Driven Mammography-Based Future Breast Cancer Risk Prediction: A Systematic Review.Journal of the American College of Radiology : JACR · 2024Pooled it
- Effects of bariatric surgery on breast density in adult obese women: systematic review and meta-analysis.Frontiers in immunology · 2023Pooled it
- Chemoprevention Agents to Reduce Mammographic Breast Density in Premenopausal Women: A Systematic Review of Clinical Trials.JNCI cancer spectrum · 2021Pooled it
- Does marital status correlate with the female breast cancer risk? A systematic review and meta-analysis of observational studies.PloS one · 2020Pooled it
- Identification of women at risk of hereditary breast-ovarian cancer among participants in a population-based breast cancer screening.Familial cancer · 2022Trial
- Deep learning applied to two-dimensional color Doppler flow imaging ultrasound images significantly improves diagnostic performance in the classification of breast masses: a multicenter study.Chinese medical journal · 2021Trial
- Effect of Metformin on Breast Density in Overweight/Obese Premenopausal Women.Diabetes, metabolic syndrome and obesity : targets and therapy · 2021Trial
- Reproducible automated breast density measure with no ionizing radiation using fat-water decomposition MRI.Journal of magnetic resonance imaging : JMRI · 2018Trial
- Attributable breast cancer burden in Malaysia: mammographic density, lifestyle, and hereditary factors.Cancer causes & control : CCC · 2026Article
- AI for Breast Cancer Risk Prediction Beyond Breast Density.Journal of the Korean Society of Radiology · 2026Review
- AutoCumulus: an automated mammographic density measure created using artificial intelligence.BMC cancer · 2026Article
- Comparison of breast cancer awareness and attitudes toward screenings in women with and without a family history.BMC cancer · 2026Article
- Co-Pathogenic Role of BRCA1 and OBSCN Deletions in Chinese Familial Breast Cancer: A Case Report.The American journal of case reports · 2026Article
- Targeting Sphingosine-1-Phosphate Signaling Attenuates Doxorubicin-Aggravated Bone Loss in Obese Breast Cancer Mice.Smart medicine · 2026Article
- Adherence to breast and cervical cancer screening guidelines according to obesity status: a French cross-sectional multicenter survey.Preventive medicine reports · 2026Article
- Residential proximity to Superfund sites and breast cancer incidence in a nationwide cohort.Environmental epidemiology (Philadelphia, Pa.) · 2026Article
- Evaluating the potential causal relationship between carnitine-related metabolites and breast cancer: a Mendelian randomization and transcriptomic analysis.Archives of medical science : AMS · 2026Article
75 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
importanceMany established breast cancer risk factors are used in clinical risk prediction models, although the proportion of breast cancers explained by these factors is unknown.
objectiveTo determine the population-attributable risk proportion (PARP) for breast cancer associated with clinical breast cancer risk factors among premenopausal and postmenopausal women. DESIGN, SETTING, AND
participantsCase-control study with 1:10 matching on age, year of risk factor assessment, and Breast Cancer Surveillance Consortium (BCSC) registry. Risk factor data were collected prospectively from January 1, 1996, through October 31, 2012, from BCSC community-based breast imaging facilities. A total of 18 437 women with invasive breast cancer or ductal carcinoma in situ were enrolled as cases and matched to 184 309 women without breast cancer, with a total of 58 146 premenopausal and 144 600 postmenopausal women enrolled in the study. EXPOSURES: Breast Imaging Reporting and Data System (BI-RADS) breast density (heterogeneously or extremely dense vs scattered fibroglandular densities), first-degree family history of breast cancer, body mass index (>25 vs 18.5-25), history of benign breast biopsy, and nulliparity or age at first birth (≥30 years vs <30 years). MAIN OUTCOMES AND MEASURES: Population-attributable risk proportion of breast cancer.
resultsOf the 18 437 women with breast cancer, the mean (SD) age was 46.3 (3.7) years among premenopausal women and 61.7 (7.2) years among the postmenopausal women. Overall, 4747 (89.8%) premenopausal and 12 502 (95.1%) postmenopausal women with breast cancer had at least 1 breast cancer risk factor. The combined PARP of all risk factors was 52.7% (95% CI, 49.1%-56.3%) among premenopausal women and 54.7% (95% CI, 46.5%-54.7%) among postmenopausal women. Breast density was the most prevalent risk factor for both premenopausal and postmenopausal women and had the largest effect on the PARP; 39.3% (95% CI, 36.6%-42.0%) of premenopausal and 26.2% (95% CI, 24.4%-28.0%) of postmenopausal breast cancers could potentially be averted if all women with heterogeneously or extremely dense breasts shifted to scattered fibroglandular breast density. Among postmenopausal women, 22.8% (95% CI, 18.3%-27.3%) of breast cancers could potentially be averted if all overweight and obese women attained a body mass index of less than 25. CONCLUSIONS AND RELEVANCE: Most women with breast cancer have at least 1 breast cancer risk factor routinely documented at the time of mammography, and more than half of premenopausal and postmenopausal breast cancers are explained by these factors. These easily assessed risk factors should be incorporated into risk prediction models to stratify breast cancer risk and promote risk-based screening and targeted prevention efforts.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.