Evidence map›Paper›PMID 33392844›Full record

ArticleBreast cancer research and treatment2021

Association of mammographic density measures and breast cancer "intrinsic" molecular subtypes.

Geffen Kleinstern, Christopher G Scott, Rulla M Tamimi, Matthew R Jensen, V Shane Pankratz, Kimberly A Bertrand, Aaron D Norman, Daniel W Visscher, Fergus J Couch, Kathleen Brandt and 7 more

Abstract read
In one paragraph

Article in Breast cancer research and treatment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Causal Effects of Breast Cancer Risk Factors across Hormone Receptor Breast Cancer Subtypes: A Two-Sample Mendelian Randomization Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
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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

17 authors.

Geffen KleinsternSchool of Public Health, University of Haifa, Haifa, Israel.
Christopher G ScottDivision of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA.
Rulla M TamimiChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Matthew R JensenDivision of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA.
V Shane PankratzUniversity of New Mexico, Albuquerque, NM, USA.
Kimberly A BertrandSlone Epidemiology Center, Boston University School of Medicine, Boston, MA, USA.
Aaron D NormanDivision of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA.
Daniel W VisscherDepartment of Anatomic Pathology, Mayo Clinic College of Medicine, Rochester, MN, USA.
Fergus J CouchDepartment of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, MN, USA.
Kathleen BrandtDepartment of Radiology, Mayo Clinic College of Medicine, Rochester, MN, USA.
John ShepherdUniversity of Hawaii, Honolulu, HI, USA.
Fang-Fang WuDivision of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First St. SW, Rochester, MN, 55905, USA.
Yunn-Yi ChenDepartment of Pathology and Laboratory Services, University of California, San Francisco, CA, USA.
Steven R CummingsSan Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA.
Stacey WinhamDivision of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA.
Karla KerlikowskeDepartments of Epidemiology and Biostatistics and General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, CA, USA.
Celine M VachonDivision of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First St. SW, Rochester, MN, 55905, USA. vachon.celine@mayo.edu.ORCID http://orcid.org/0000-0002-1962-9322

Funding

Statistical MethodsP01CA087969 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ROSNER, BERNARD A · 2000 to 2019
$77.8M
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
The Role of CHFR in Tumorigenesis and Paclitaxel-Sensitivity in Breast CancerP50CA116201 · NCI · MAYO CLINIC ROCHESTER · PI Fergus Joseph Couch · 2005 to 2026
$49.9M
Tissue and Outcomes CoreP50CA058207 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BLACKBURN, ELIZABETH H · 1992 to 2012
$32.7M
Risk Factors for Breast Cancer in Younger NursesR01CA050385 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI ELIASSEN, A. HEATHER, WILLETT, WALTER C. · 1989 to 2019
$32.3M
Life Course Cancer Epidemiology Cohort in WomenU01CA176726 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI ELIASSEN, A. HEATHER, WILLETT, WALTER C. · 2018 to 2025
$22.4M
Life Course Cancer Epidemiology Cohort in WomenUM1CA176726 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI WILLETT, WALTER C. · 2013 to 2017
$15.7M
Prediction of Neoadjuvant Chemo Pathological Response Using MRI MarkersR01CA127927 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI SU, MIN-YING L. · 2008 to 2017
$5.0M
A Mayo Cohort Study of Mammographic Breast DensityR01CA097396 · NCI · MAYO CLINIC ROCHESTER · PI VACHON, CELINE M · 2003 to 2007
$3.1M
Automated Density Measures for Estimating Breast Cancer Risk and Therapy ResponseR01CA177150 · NCI · MAYO CLINIC ROCHESTER · PI KERLIKOWSKE, KARLA M, VACHON, CELINE M · 2013 to 2017
$3.0M
Genetic epidemiology of cell division regulation in breast cancerR01CA122340 · NCI · MAYO CLINIC ROCHESTER · PI COUCH, FERGUS JOSEPH · 2007 to 2011
$3.0M
BRCA2 missense mutations and breast cancerR01CA116167 · NCI · MAYO CLINIC ROCHESTER · PI COUCH, FERGUS JOSEPH · 2007 to 2011
$3.0M
National Institutes of Health (US) UM1CA186107NCI NIH HHS P01 CA087969NCI NIH HHS P01 CA154292NCI NIH HHS P50 CA058207NCI NIH HHS P50 CA116201NCI NIH HHS R01 CA050385NCI NIH HHS R01 CA097396NCI NIH HHS R01 CA122340NCI NIH HHS R01 CA124865NCI NIH HHS R01 CA127927NCI NIH HHS R01 CA128931NCI NIH HHS R01 CA131332NCI NIH HHS R01 CA140286NCI NIH HHS R01CA140286NCI NIH HHS R01 CA177150NCI NIH HHS R01CA2128931NCI NIH HHS R01CA97396NCI NIH HHS R03 CA136071NCI NIH HHS R21 CA170955NCI NIH HHS R21 CA208938NCI NIH HHS U01 CA176726NIH HHS P01CA087969NIH HHS P01CA154292NIH HHS P50CA116201NIH HHS P50CA58207NIH HHS R01CA050385NIH HHS R01CA116167NIH HHS R01CA124865NIH HHS R01CA131332NIH HHS U01CA63740NIH HHS UM1CA176726U.S. Department of Defense DAMD17-00-1-033
6 · The paper itself

Abstract

purposeWe evaluated the association of percent mammographic density (PMD), absolute dense area (DA), and non-dense area (NDA) with risk of "intrinsic" molecular breast cancer (BC) subtypes.

methodsWe pooled 3492 invasive BC and 10,148 controls across six studies with density measures from prediagnostic, digitized film-screen mammograms. We classified BC tumors into subtypes [63% Luminal A, 21% Luminal B, 5% HER2 expressing, and 11% as triple negative (TN)] using information on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and tumor grade. We used polytomous logistic regression to calculate odds ratio (OR) and 95% confidence intervals (CI) for density measures (per SD) across the subtypes compared to controls, adjusting for age, body mass index and study, and examined differences by age group.

resultsAll density measures were similarly associated with BC risk across subtypes. Significant interaction of PMD by age (P = 0.001) was observed for Luminal A tumors, with stronger effect sizes seen for younger women < 45 years (OR = 1.69 per SD PMD) relative to women of older ages (OR = 1.53, ages 65-74, OR = 1.44 ages 75 +). Similar but opposite trends were seen for NDA by age for risk of Luminal A: risk for women: < 45 years (OR = 0.71 per SD NDA) was lower than older women (OR = 0.83 and OR = 0.84 for ages 65-74 and 75 + , respectively) (P < 0.001). Although not significant, similar patterns of associations were seen by age for TN cancers.

conclusionsMammographic density measures were associated with risk of all "intrinsic" molecular subtypes. However, findings of significant interactions between age and density measures may have implications for subtype-specific risk models.

Indexed as

Breast DensityBreast NeoplasmsAgedBiomarkers, TumorCase-Control StudiesErb-b2 Receptor Tyrosine KinasesFemaleHumansMiddle AgedReceptors, EstrogenReceptors, ProgesteroneRisk FactorsBiomarkers, TumorErb-b2 Receptor Tyrosine KinasesReceptors, EstrogenReceptors, ProgesteroneBreast cancer“Intrinsic” molecular subtypesMammographic density

Identifiers

PMID33392844
PMCPMC8216504

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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.