Evidence map›Paper›PMID 25126973›Full record

ArticleAcademic radiology2014

Breast MRI BI-RADS assessments and abnormal interpretation rates by clinical indication in US community practices.

Christoph I Lee, Laura Ichikawa, Michele C Rochelle, Karla Kerlikowske, Diana L Miglioretti, Brian L Sprague, Wendy B DeMartini, Karen J Wernli, Bonnie N Joe, Bonnie C Yankaskas and 1 more

Abstract readMulticenter Study
In one paragraph

Article in Academic radiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Diffusion-weighted Imaging Allows for Downgrading MR BI-RADS 4 Lesions in Contrast-enhanced MRI of the Breast to Avoid Unnecessary Biopsy.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021
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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.

Christoph I LeeDepartment of Radiology, University of Washington School of Medicine, 825 Eastlake Ave East, G3-200, Seattle, WA, 98109-1023; Department of Health Services, University of Washington School of Public Health, Seattle, Washington. Electronic address: stophlee@uw.edu.
Laura IchikawaGroup Health Research Institute, Seattle, Washington.
Michele C RochelleDepartment of Radiology, University of Washington School of Medicine, 825 Eastlake Ave East, G3-200, Seattle, WA, 98109-1023.
Karla KerlikowskeGeneral Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, San Francisco, California; Department of Medicine, University of California, San Francisco, San Francisco, California; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California.
Diana L MigliorettiGroup Health Research Institute, Seattle, Washington; Department of Public Health Sciences, University of California, Davis, Davis, California.
Brian L SpragueDepartment of Surgery and Office of Health Promotion Research, University of Vermont, Burlington, Vermont.
Wendy B DeMartiniDepartment of Radiology, University of Wisconsin School of Medicine, Madison, Wisconsin.
Karen J WernliGroup Health Research Institute, Seattle, Washington.
Bonnie N JoeDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California.
Bonnie C YankaskasDepartment of Radiology, School of Medicine, University of North Carolina, Chapel Hill, North Carolina; Department of Epidemiology, School of Public Health, University of North Carolina, Chapel Hill, North Carolina.
Constance D LehmanDepartment of Radiology, University of Washington School of Medicine, 825 Eastlake Ave East, G3-200, Seattle, WA, 98109-1023.

Funding

Staff InvestigatorsP30CA093373 · NCI · UNIVERSITY OF CALIFORNIA DAVIS · PI PRIMO N. LARA · 2002 to 2026
$84.9M
Risk-based Imaging Strategies to Improve Breast Cancer Surveillance OutcomesP01CA154292 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Diana L Miglioretti · 2011 to 2026
$52.9M
Comparative effectiveness of breast imaging strategies in community practiceRC2CA148577 · NCI · KAISER FOUNDATION HEALTH PLAN OF WASHINGTON · PI BUIST, DIANA SM, GELLER, BERTA M · 2009 to 2009
$2.0M
NCI NIH HHS P01 CA154292NCI NIH HHS P01CA154292NCI NIH HHS P30 CA093373NCI NIH HHS RC2 CA148577NCI NIH HHS RC2CA148577
6 · The paper itself

Abstract

RATIONALE AND

objectivesAs breast magnetic resonance imaging (MRI) use grows, benchmark performance parameters are needed for auditing and quality assurance purposes. We describe the variation in breast MRI abnormal interpretation rates (AIRs) by clinical indication among a large sample of US community practices. MATERIALS AND

methodsWe analyzed data from 41 facilities across five Breast Cancer Surveillance Consortium imaging registries. Each registry obtained institutional review board approval for this Health Insurance Portability and Accountability Act compliant analysis. We included 11,654 breast MRI examinations conducted in 2005-2010 among women aged 18-79 years. We categorized clinical indications as 1) screening, 2) extent of disease, 3) diagnostic (eg, breast symptoms), and 4) other (eg, short-interval follow-up). We characterized assessments as positive (ie, Breast Imaging Reporting and Data System [BI-RADS] 0, 4, and 5) or negative (ie, BI-RADS 1, 2, and 6) and provide results with BI-RADS 3 categorized as positive and negative. We tested for differences in AIRs across clinical indications both unadjusted and adjusted for patient characteristics and registry and assessed for changes in AIRs by year within each clinical indication.

resultsWhen categorizing BI-RADS 3 as positive, AIRs were 21.0% (95% confidence interval [CI], 19.8-22.3) for screening, 31.7% (95% CI, 29.6-33.8) for extent of disease, 29.7% (95% CI, 28.3-31.1) for diagnostic, and 27.4% (95% CI, 25.0-29.8) for other indications (P < .0001). When categorizing BI-RADS 3 as negative, AIRs were 10.5% (95% CI, 9.5-11.4) for screening, 21.8% (95% CI, 19.9-23.6) for extent of disease, 17.7% (95% CI, 16.5-18.8) for diagnostic, and 13.3% (95% CI, 11.6-15.2) for other indications (P < .0001). The significant differences in AIRs by indication persisted even after adjusting for patient characteristics and registry (P < .0001). In addition, for most indications, there were no significant changes in AIRs over time.

conclusionsBreast MRI AIRs differ significantly by clinical indication. Practices should stratify breast MRI examinations by indication for quality assurance and auditing purposes.

Indexed as

Practice Guidelines as TopicAdolescentAdultAgedBreast NeoplasmsHumansMagnetic Resonance ImagingMaleMammographyMedical OncologyMiddle AgedPractice Patterns, Physicians'PrevalenceRadiologyReproducibility of ResultsRisk FactorsauditBreast magnetic resonance imagingquality assurance

Identifiers

PMID25126973
PMCPMC4194166

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Registered trials

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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.