Evidence map›Paper›PMID 34686934›Full record

ArticleBreast cancer research and treatment2022

Preoperative MRI in breast cancer: effect of breast density on biopsy rate and yield.

Tracy Onega, Weiwei Zhu, Karla Kerlikowske, Diana L Miglioretti, Christoph I Lee, Louise M Henderson, Anna N A Tosteson, Karen J Wernli, Roberta diFlorio, Donald L Weaver and 1 more

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in Breast cancer research and treatment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02980848 (Comparative Effectiveness of Breast Cancer Screening and Diagnostic Evaluation by Extent of Breast Density), which is not on this map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.9field-weighted citation impact, top 14% 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.

NCT02980848 unknown statusnot on this map

Comparative Effectiveness of Breast Cancer Screening and Diagnostic Evaluation by Extent of Breast Density

Typeobservational_patient_registrySponsorUniversity of California, DavisRan2016 to 2022Enrolled1,341,172ConditionsBreast CancerArmsScreening digital mammography, Screening digital breast tomosynthesis, Screening breast magnetic resonance imaging, Diagnostic mammography, Pre-operative breast magnetic resonance imaging
3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 17 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

11 authors at 8 institutions in 1 country.

Tracy OnegaDepartment of Population Health Sciences, and the Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA. tracy.onega@hci.utah.edu.ORCID http://orcid.org/0000-0002-1633-3040
Weiwei ZhuKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Karla KerlikowskeDepartments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
Diana L MigliorettiKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Christoph I LeeDepartment of Radiology, University of Washington, and Seattle Cancer Care Alliance, Seattle, WA, USA.
Louise M HendersonDepartment of Radiology, University of North Carolina, Chapel Hill, NC, USA.
Anna N A TostesonThe Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Karen J WernliKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Roberta diFlorioDepartment of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.
Donald L WeaverDepartment of Pathology, University of Vermont, Burlington, VT, USA.
Diana S M BuistKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Kaiser Permanente Washington Health Research Institute · USDartmouth–Hitchcock Medical Center · USDartmouth Institute for Health Policy and Clinical Practice · USSan Francisco VA Medical Center · USSeattle Cancer Care Alliance · USUniversity of North Carolina at Chapel Hill · USUniversity of Utah · USUniversity of Vermont · US

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Steven D Leach · 1985 to 2026
$91.3M
Risk-based Imaging Strategies to Improve Breast Cancer Surveillance OutcomesP01CA154292 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Janie M Lee · 2011 to 2026
$52.9M
CALIFORNIA COORDINATED CANCER PREVENTION & CONTROL PROGRAMU58DP003862 · DP · CALIFORNIA STATE DEPT OF PUBLIC HEALTH · PI SNIPES, KURT P · 2012 to 2014
$31.5M
Vermont Screening Process Documentation UnitU54CA163303 · NCI · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI SPRAGUE, BRIAN L · 2011 to 2017
$6.4M
STRATEGIC STUDIES IN BREAST CANCER SURVEILLANCEU01CA086082 · NCI · DARTMOUTH COLLEGE · PI ONEGA, TRACY · 2000 to 2011
$4.9M
Effectiveness of Pre-Operative MRI in Breast Cancer Surgery and OutcomesR01CA149365 · NCI · DARTMOUTH COLLEGE · PI ONEGA, TRACY · 2011 to 2015
$2.8M
Comparative effectiveness of breast imaging modalities: a natural experimentR01HS018366 · AHRQ · UNIVERSITY OF ILLINOIS AT CHICAGO · PI RAUSCHER, GARTH H · 2010 to 2014
$1.8M
SURVEILLANCE EPIDEMIOLOGY AND END RESULTSN01CN005230 · CN · FRED HUTCHINSON CANCER RESEARCH CENTER · PI THOMAS, DAVID B · 1990 to 1996
–
SURVEILLANCE EPIDEMIOLOGY &END RESULTS PROGRAMN01CN067009 · CN · FRED HUTCHINSON CANCER RESEARCH CENTER · PI THOMAS, DAVID B · 1996 to 1997
–
AHRQ HHS R01 HS018366NCCDPHP CDC HHS U58 DP003862NCI NIH HHS HHSN261201000029CNCI NIH HHS HHSN261201000034CNCI NIH HHS HHSN261201000035CNCI NIH HHS HHSN261201000035INCI NIH HHS HHSN261201000140CNCI NIH HHS HHSN261201300012INCI NIH HHS N01 CN005230NCI NIH HHS N01 CN067009NCI NIH HHS N01 PC035142NCI NIH HHS P01 CA154292NCI NIH HHS P30 CA023108NCI NIH HHS R01 CA149365NCI NIH HHS U01 CA086082NCI NIH HHS U54 CA163303Patient-Centered Outcomes Research Institute CS-1504-30370
6 · The paper itself

Abstract

purposePreoperative breast MRI is used to evaluate for additional cancer and extent of disease for newly diagnosed breast cancer, yet benefits and harms of preoperative MRI are not well-documented. We examined whether preoperative MRI yields additional biopsy and cancer detection by extent of breast density.

methodsWe followed women in the Breast Cancer Surveillance Consortium with an incident breast cancer diagnosed from 2005 to 2017. We quantified breast biopsies and cancers detected within 6 months of diagnosis by preoperative breast MRI receipt, overall and by breast density, accounting for MRI selection bias using inverse probability weighted logistic regression.

resultsAmong 19,324 women with newly diagnosed breast cancer, 28% had preoperative MRI, 11% additional biopsy, and 5% additional cancer detected. Four times as many women with preoperative MRI underwent additional biopsy compared to women without MRI (22.6% v. 5.1%). Additional biopsy rates with preoperative MRI increased with increasing breast density (27.4% for extremely dense compared to 16.2% for almost entirely fatty breasts). Rates of additional cancer detection were almost four times higher for women with v. without MRI (9.9% v. 2.6%). Conditional on additional biopsy, age-adjusted rates of additional cancer detection were lowest among women with extremely dense breasts, regardless of imaging modality (with MRI: 35.0%; 95% CI 27.0-43.0%; without MRI: 45.1%; 95% CI 32.6-57.5%).

conclusionFor women with dense breasts, preoperative MRI was associated with much higher biopsy rates, without concomitant higher cancer detection. Preoperative MRI may be considered for some women, but selecting women based on breast density is not supported by evidence.

trial registrationClinicalTrials.gov: NCT02980848; registered 2017.

Indexed as

Breast DensityBreast NeoplasmsBiopsyFemaleHumansMagnetic Resonance ImagingMammographyBreast biopsyBreast Cancer Surveillance ConsortiumBreast densityCancer detection rateOccult cancerPreoperative MRI

Identifiers

PMID34686934
PMCPMC9881728
OpenAlexW3206329373

What OpenQuestion holds

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Registered trials

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.