Evidence map›Paper›PMID 32727722›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2020

Breast Cancer Population Attributable Risk Proportions Associated with Body Mass Index and Breast Density by Race/Ethnicity and Menopausal Status.

Michael C S Bissell, Karla Kerlikowske, Brian L Sprague, Jeffery A Tice, Charlotte C Gard, Katherine Y Tossas, Garth H Rauscher, Amy Trentham-Dietz, Louise M Henderson, Tracy Onega and 3 more

Open access · greenAbstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
3.3field-weighted citation impact, top 6% of its field
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

43 citing papers in PubMed, 66 citations in OpenAlex.

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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

13 authors at 11 institutions in 1 country.

Michael C S BissellDivision of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis, California. mcbissell@ucdavis.edu.
Karla KerlikowskeGeneral Internal Medicine Section, Department of Veteran Affairs and Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California.
Brian L SpragueDepartment of Surgery, Office of Health Promotion Research, Larner College of Medicine at the University of Vermont and University of Vermont Cancer Center, Burlington, Vermont.ORCID 0000-0002-9857-2028
Jeffery A TiceDivision of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California.ORCID 0000-0002-9857-2028
Charlotte C GardDepartment of Economics, Applied Statistics, and International Business, New Mexico State University, Las Cruces, New Mexico.
Katherine Y TossasDepartment of Health Behavior and Policy, School of Medicine, Virginia Commonwealth University, Richmond, Virginia.
Garth H RauscherDivision of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, Illinois.ORCID 0000-0003-0374-944X
Amy Trentham-DietzDepartment of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin.ORCID 0000-0002-5971-4660
Louise M HendersonDepartment of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
Tracy OnegaDepartment of Biomedical Data Science, Dartmouth College, Lebanon, New Hampshire.ORCID 0000-0002-1633-3040
Theresa H M KeeganCenter for Oncology Hematology Outcomes Research and Training (COHORT) and Division of Hematology and Oncology, University of California Davis School of Medicine, Sacramento, California.
Diana L MigliorettiORCID 0000-0002-5547-1833
Breast Cancer Surveillance Consortium
University of California, Davis · USDartmouth College · USKaiser Permanente Washington Health Research Institute · USNew Mexico State University · USSan Francisco General Hospital · USSan Francisco VA Medical Center · USUniversity of Illinois Chicago · USUniversity of North Carolina at Chapel Hill · USUniversity of Vermont · USUniversity of Wisconsin Carbone Cancer Center · USVirginia Commonwealth University · US

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Staff InvestigatorsP30CA093373 · NCI · UNIVERSITY OF CALIFORNIA DAVIS · PI Gina M Dayton · 2002 to 2026
$84.9M
Risk-based Imaging Strategies to Improve Breast Cancer Surveillance OutcomesP01CA154292 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KARLA M KERLIKOWSKE · 2011 to 2026
$52.9M
Vermont Screening Process Documentation UnitU54CA163303 · NCI · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI SPRAGUE, BRIAN L · 2011 to 2017
$6.4M
Comparative effectiveness of breast imaging modalities: a natural experimentR01HS018366 · AHRQ · UNIVERSITY OF ILLINOIS AT CHICAGO · PI RAUSCHER, GARTH H · 2010 to 2014
$1.8M
AHRQ HHS R01 HS018366NCI NIH HHS P01 CA154292NCI NIH HHS P30 CA023108NCI NIH HHS P30 CA093373NCI NIH HHS U54 CA163303
6 · The paper itself

Abstract

backgroundOverweight/obesity and dense breasts are strong breast cancer risk factors whose prevalences vary by race/ethnicity. The breast cancer population attributable risk proportions (PARP) explained by these factors across racial/ethnic groups are unknown.

methodsWe analyzed data collected from 3,786,802 mammography examinations (1,071,653 women) in the Breast Cancer Surveillance Consortium, associated with 21,253 invasive breast cancers during a median of 5.2 years follow-up. HRs for body mass index (BMI) and breast density, adjusted for age and registry were estimated using separate Cox regression models by race/ethnicity (White, Black, Hispanic, Asian) and menopausal status. HRs were combined with observed risk-factor proportions to calculate PARPs for shifting overweight/obese to normal BMI and shifting heterogeneously/extremely dense to scattered fibroglandular densities.

resultsThe prevalences and HRs for overweight/obesity and heterogeneously/extremely dense breasts varied across races/ethnicities and menopausal status. BMI PARPs were larger for postmenopausal versus premenopausal women (12.0%-28.3% vs. 1.0%-9.9%) and nearly double among postmenopausal Black women (28.3%) than other races/ethnicities (12.0%-15.4%). Breast density PARPs were larger for premenopausal versus postmenopausal women (23.9%-35.0% vs. 13.0%-16.7%) and lower among premenopausal Black women (23.9%) than other races/ethnicities (30.4%-35.0%). Postmenopausal density PARPs were similar across races/ethnicities (13.0%-16.7%).

conclusionsOverweight/obesity and dense breasts account for large proportions of breast cancers in White, Black, Hispanic, and Asian women despite large differences in risk-factor distributions. IMPACT: Risk prediction models should consider how race/ethnicity interacts with BMI and breast density. Efforts to reduce BMI could have a large impact on breast cancer risk reduction, particularly among postmenopausal Black women.

Indexed as

AdultBody Mass IndexBreast DensityBreast NeoplasmsEthnicityFemaleHumansMenopauseMiddle AgedRace FactorsRisk Factors

Identifiers

PMID32727722
PMCPMC7541499
OpenAlexW3045982382

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.