Evidence map›Paper›PMID 31660981›Full record

ArticleBreast cancer research : BCR2019

Automated volumetric breast density measures: differential change between breasts in women with and without breast cancer.

Kathleen R Brandt, Christopher G Scott, Diana L Miglioretti, Matthew R Jensen, Amir P Mahmoudzadeh, Carrie Hruska, Lin Ma, Fang Fang Wu, Steven R Cummings, Aaron D Norman and 5 more

Open access · goldAbstract read
In one paragraph

Article in Breast cancer research : BCR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 15% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
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  10. Medication use and mammographic breast density.Breast cancer research and treatment · 2021
    Article
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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

15 authors at 6 institutions in 1 country.

Kathleen R BrandtDepartment of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. brandt.kathy@mayo.edu.ORCID 0000-0003-2144-261X
Christopher G ScottDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Diana L MigliorettiKaiser Permanente Washington Health Research Institute, 1730 Minor Avenue, Seattle, WA, 98101, USA.
Matthew R JensenDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Amir P MahmoudzadehDepartment of Radiology and Biomedical Imaging, University of California, 505 Parnassus Avenue, San Francisco, CA, 94143, USA.
Carrie HruskaDepartment of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Lin MaDivision of Research, Kaiser Permanente, 2000 Broadway, Oakland, CA, 94612, USA.
Fang Fang WuDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Steven R CummingsCalifornia Pacific Medical Center Research Institute, 475 Brannan Street #220, San Francisco, CA, 94107, USA.
Aaron D NormanDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Natalie J EngmannDepartment of Epidemiology and Biostatistics, University of California, 550 16th Street, Second Floor, San Francisco, CA, 94158, USA.
John A ShepherdUniversity of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI, 96813, USA.
Stacey J WinhamDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Karla KerlikowskeDepartment of Epidemiology and Biostatistics, University of California, 550 16th Street, Second Floor, San Francisco, CA, 94158, USA.
Celine M VachonDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Mayo Clinic · USUniversity of California, San Francisco · USCalifornia Pacific Medical Center · USKaiser Permanente · USKaiser Permanente Washington Health Research Institute · USUniversity of Hawaiʻi at Mānoa · US

Funding

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
Radiomic phenotypes of breast parenchyma and association with breast cancer risk and detectionR01CA207084 · NCI · MAYO CLINIC ROCHESTER · PI KERLIKOWSKE, KARLA M, KONTOS, DESPINA · 2017 to 2021
$3.2M
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
NCI NIH HHS P01 CA154292NCI NIH HHS R01 CA177150NCI NIH HHS R01 CA207084
6 · The paper itself

Abstract

backgroundGiven that breast cancer and normal dense fibroglandular tissue have similar radiographic attenuation, we examine whether automated volumetric density measures identify a differential change between breasts in women with cancer and compare to healthy controls.

methodsEligible cases (n = 1160) had unilateral invasive breast cancer and bilateral full-field digital mammograms (FFDMs) at two time points: within 2 months and 1-5 years before diagnosis. Controls (n = 2360) were matched to cases on age and date of FFDMs. Dense volume (DV) and volumetric percent density (VPD) for each breast were assessed using Volpara™. Differences in DV and VPD between mammograms (median 3 years apart) were calculated per breast separately for cases and controls and their difference evaluated by using the Wilcoxon signed-rank test. To simulate clinical practice where cancer laterality is unknown, we examined whether the absolute difference between breasts can discriminate cases from controls using area under the ROC curve (AUC) analysis, adjusting for age, BMI, and time.

resultsAmong cases, the VPD and DV between mammograms of the cancerous breast decreased to a lesser degree (- 0.26% and - 2.10 cm

conclusionThere is a small relative increase in volumetric density measures over time in the breast with cancer which is not found in the normal breast. However, the magnitude of this difference is small, and this measure alone does not appear to be a good discriminator between women with and without breast cancer.

Indexed as

Breast DensityAgedAutomationBreastBreast NeoplasmsCase-Control StudiesEarly Detection of CancerFemaleHumansMammographyMiddle AgedReproducibility of ResultsSensitivity and SpecificityTumor BurdenBreast cancerBreast densityRiskTissue asymmetryVolumetric density

Identifiers

PMID31660981
PMCPMC6819393
OpenAlexW2982469773

What OpenQuestion holds

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LicenceCC BY
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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.