Evidence map›Paper›PMID 27552842›Full record

ArticleBreast cancer research : BCR2016

Relationships between mammographic density, tissue microvessel density, and breast biopsy diagnosis.

Ashley S Felix, Petra Lenz, Ruth M Pfeiffer, Stephen M Hewitt, Jennifer Morris, Deesha A Patel, Berta Geller, Pamela M Vacek, Donald L Weaver, Rachael E Chicoine and 11 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Breast cancer research : BCR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

11 citing papers in PubMed, 25 citations in OpenAlex.

  1. Trial
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  8. Observational
  9. Microvessel Density (MVD) in Locally Advanced Breast CancerAsian Pacific journal of cancer prevention : APJCP · 2019
    Article
  10. Article
  11. Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2018
    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

21 authors at 8 institutions in 2 countries.

Ashley S FelixDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. Felix.20@osu.edu.
Petra LenzClinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA.
Ruth M PfeifferDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Stephen M HewittLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Jennifer MorrisLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Deesha A PatelDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Berta GellerDepartment of Family Medicine, University of Vermont, Burlington, VT, USA.
Pamela M VacekDepartment of Pathology, University of Vermont, Burlington, VT, USA.
Donald L WeaverDepartment of Pathology, University of Vermont, Burlington, VT, USA.
Rachael E ChicoineOffice of Health Promotion Research, University of Vermont, Burlington, VT, USA.
John ShepherdUniversity of California, San Francisco, CA, USA.
Amir Pasha MahmoudzadehUniversity of California, San Francisco, CA, USA.
Jeff WangUniversity of California, San Francisco, CA, USA.
Bo FanUniversity of California, San Francisco, CA, USA.
Serghei MalkovUniversity of California, San Francisco, CA, USA.
Sally D HerschornDepartment of Radiology, University of Vermont, Burlington, VT, USA.
Jason M JohnsonDepartment of Diagnostic Radiology, Neuroradiology Section, MD Anderson Cancer Center, Houston, TX, USA.
Renata L CoraDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Louise A BrintonDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Mark E ShermanDivision of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Gretchen L GierachDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
National Cancer Institute · USNational Institutes of Health · USUniversity of California, San Francisco · USUniversity of Vermont · USFrederick National Laboratory for Cancer Research · USHokkaido University · JPThe University of Texas MD Anderson Cancer Center · USVermont Department of Health · US

Funding

Hormone-Related CancersZIACP010126 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI GIERACH, GRETCHEN · 2009 to 2025
$103.5M
VERMONT BREAST CANCER SURVEILLANCE SYSTEMU01CA070013 · NCI · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI GELLER, BERTA M · 1995 to 2011
$6.7M
Lesion Composition and Quantitative Imaging Analysis on Breast Cancer DiagnosisR01CA166945 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI GIGER, MARYELLEN L., SHEPHERD, JOHN ALAN · 2013 to 2017
$3.3M
NCI NIH HHS R01 CA166945NCI NIH HHS U01 CA070013
6 · The paper itself

Abstract

backgroundWomen with high levels of mammographic density (MD) have a four- to six-fold increased risk of developing breast cancer; however, most neither have a prevalent tumor nor will they develop one. Magnetic resonance imaging (MRI) studies suggest that background parenchymal enhancement, an indicator of vascularity, is related to increased breast cancer risk. Correlations of microvessel density (MVD) in tissue, MD and biopsy diagnosis have not been defined, and we investigated these relationships among 218 women referred for biopsy.

methodsMVD was determined by counting CD31-positive vessels in whole sections of breast biopsies in three representative areas; average MVD was transformed to approximate normality. Using digital mammograms, we quantified MD volume with single X-ray absorptiometry. We used linear regression to evaluate associations between MVD and MD adjusted for age and body mass index (BMI) overall, and stratified by biopsy diagnosis: cases (in situ or invasive cancer, n = 44) versus non-cases (non-proliferative or proliferative benign breast disease, n = 174). Logistic regression adjusted for age, BMI, and MD was used to calculate odds ratios (ORs) and 95 % confidence intervals (CIs) for associations between MVD and biopsy diagnosis. We also assessed whether the MVD-breast cancer association varied by MD.

resultsMVD and MD were not consistently associated. Higher MVD was significantly associated with higher odds of in situ/invasive disease (ORAdjusted = 1.69, 95 % CI = 1.17-2.44). MVD-breast cancer associations were strongest among women with greater non-dense volume.

conclusionsIncreased MVD in tissues is associated with breast cancer, independently of MD, consistent with MRI findings suggestive of its possible value as a radiological cancer biomarker.

Indexed as

Breast DensityNeovascularization, PathologicAdultAgedBiopsyBreast NeoplasmsFemaleHumansImmunohistochemistryMammographyMicrovesselsMiddle AgedPlatelet Endothelial Cell Adhesion Molecule-1Risk FactorsPlatelet Endothelial Cell Adhesion Molecule-1AngiogenesisBreast neoplasmsLesional densityMammographic densityPathology

Identifiers

PMID27552842
PMCPMC4995674
OpenAlexW2516963336

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.