Evidence map›Paper›PMID 31242899›Full record

ArticleBMC cancer2019

Predictors of mammographic density among women with a strong family history of breast cancer.

Olivia Moran, Andrea Eisen, Rochelle Demsky, Kristina Blackmore, Julia A Knight, Seema Panchal, Ophira Ginsburg, Kevin Zbuk, Martin Yaffe, Kelly A Metcalfe and 2 more

Abstract read
In one paragraph

Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Associations of Oral Contraceptives with Mammographic Breast Density in Premenopausal Women.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022
    Article
  7. Article
  8. Article
4 · The record

Corrections and comments

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

12 authors.

Olivia MoranWomen's College Research Institute, Women's College Hospital, 76 Grenville St., 6th Floor, Toronto, ON, Canada.
Andrea EisenToronto-Sunnybrook Regional Cancer Center, Toronto, ON, Canada.
Rochelle DemskyDivision of Gynecologic Oncology, Princess Margaret Hospital, University Health Network, Toronto, ON, Canada.
Kristina BlackmorePrevention and Cancer Control, Cancer Care Ontario, Toronto, ON, Canada.
Julia A KnightLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Seema PanchalMount Sinai Hospital, University of Toronto, Toronto, ON, Canada.
Ophira GinsburgPerlmutter Cancer Centre, Department of Population Health, NYU Langone Health, New York, NY, USA.
Kevin ZbukDepartment of Oncology, McMaster University, Hamilton, ON, Canada.
Martin YaffeDepartment of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Kelly A MetcalfeWomen's College Research Institute, Women's College Hospital, 76 Grenville St., 6th Floor, Toronto, ON, Canada.
Steven A NarodWomen's College Research Institute, Women's College Hospital, 76 Grenville St., 6th Floor, Toronto, ON, Canada.
Joanne KotsopoulosWomen's College Research Institute, Women's College Hospital, 76 Grenville St., 6th Floor, Toronto, ON, Canada. joanne.kotsopoulos@wchospital.ca.ORCID http://orcid.org/0000-0001-9624-4218

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMammographic density is one of the strongest risk factors for breast cancer. In the general population, mammographic density can be modified by various exposures; whether this is true for women a strong family history is not known. Thus, we evaluated the association between reproductive, hormonal, and lifestyle risk factors and mammographic density among women with a strong family history of breast cancer but no BRCA1 or BRCA2 mutation.

methodsWe included 97 premenopausal and 59 postmenopausal women (age range: 27-68 years). Risk factor data was extracted from the research questionnaire closest in time to the mammogram performed nearest to enrollment. The Cumulus software was used to measure percent density, dense area, and non-dense area for each mammogram. Multivariate generalized linear models were used to evaluate the relationships between breast cancer risk factors and measures of mammographic density, adjusting for relevant covariates.

resultsAmong premenopausal women, those who had two live births had a mean percent density of 28.8% vs. 41.6% among women who had one live birth (P=0.04). Women with a high body weight had a lower mean percent density compared to women with a low body weight among premenopausal (17.6% vs. 33.2%; P=0.0006) and postmenopausal women (8.7% vs. 14.7%; P=0.04). Among premenopausal women, those who smoked for 14 years or longer had a lower mean dense area compared to women who smoked for a shorter duration (25.3cm

conclusionsIn this cohort of women with a strong family history of breast cancer, body weight was associated with mammographic density. These findings suggest that mammographic density may explain the underlying relationship between some of these risk factors and breast cancer risk, and lend support for the inclusion of mammographic density into risk prediction models.

Indexed as

Body WeightFamily HealthMammographyAdultAgedBreast DensityBreast NeoplasmsCross-Sectional StudiesEx-SmokersFemaleGenes, BRCA1Genes, BRCA2HumansLife StyleLinear ModelsMiddle Agedbreast cancerfamilial breast cancermammographic densityrisk factors

Identifiers

PMID31242899
PMCPMC6595553

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LicenceCC BY
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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.