Evidence map›Paper›PMID 32227180›Full record

ArticleJAMA network open2020

Assessment of Radiologist Performance in Breast Cancer Screening Using Digital Breast Tomosynthesis vs Digital Mammography.

Brian L Sprague, R Yates Coley, Karla Kerlikowske, Garth H Rauscher, Louise M Henderson, Tracy Onega, Christoph I Lee, Sally D Herschorn, Anna N A Tosteson, Diana L Miglioretti

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.5field-weighted citation impact, top 6% 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

17 citing papers in PubMed, 37 citations in OpenAlex.

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  16. What do experts look at and what do experts find when reading mammograms?Journal of medical imaging (Bellingham, Wash.) · 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

10 authors at 8 institutions in 1 country.

Brian L SpragueDepartment of Surgery, University of Vermont Cancer Center, University of Vermont, Burlington.
R Yates ColeyKaiser Permanente Washington Health Research Institute, Seattle.
Karla KerlikowskeDepartment of Medicine, University of California, San Francisco.
Garth H RauscherDivision of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago.
Louise M HendersonDepartment of Radiology, University of North Carolina, Chapel Hill.
Tracy OnegaDepartment of Biomedical Data Science, The Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire.
Christoph I LeeDepartment of Radiology, University of Washington School of Medicine, Seattle.
Sally D HerschornDepartment of Radiology, University of Vermont Cancer Center, University of Vermont, Burlington.
Anna N A TostesonThe Dartmouth Institute for Health Policy and Clinical Practice, Lebanon, New Hampshire.
Diana L MigliorettiDivision of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis.
Dartmouth Institute for Health Policy and Clinical Practice · USUniversity of Vermont · USKaiser Permanente Washington Health Research Institute · USSan Francisco VA Medical Center · USUniversity of California, Davis · USUniversity of Illinois Chicago · USUniversity of North Carolina at Chapel Hill · USUniversity of Washington · 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 Diana L Miglioretti · 2011 to 2026
$52.9M
Vermont Screening Process Documentation UnitU54CA163303 · NCI · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI SPRAGUE, BRIAN L · 2011 to 2017
$6.4M
Comparative effectiveness of breast imaging modalities: a natural experimentR01HS018366 · AHRQ · UNIVERSITY OF ILLINOIS AT CHICAGO · PI RAUSCHER, GARTH H · 2010 to 2014
$1.8M
AHRQ HHS R01 HS018366NCI NIH HHS P01 CA154292NCI NIH HHS P30 CA023108NCI NIH HHS U54 CA163303
6 · The paper itself

Abstract

Importance: Many US radiologists have screening mammography recall rates above the expert-recommended threshold of 12%. The influence of digital breast tomosynthesis (DBT) on the distribution of radiologist recall rates is uncertain. Objective: To evaluate radiologists' recall and cancer detection rates before and after beginning interpretation of DBT examinations. Design, Setting, and Participants: This cohort study included 198 radiologists from 104 radiology facilities in the Breast Cancer Surveillance Consortium who interpreted 251 384 DBT and 2 000 681 digital mammography (DM) screening examinations from 2009 to 2017, including 126 radiologists (63.6%) who interpreted DBT examinations during the study period and 72 (36.4%) who exclusively interpreted DM examinations (to adjust for secular trends). Data were analyzed from April 2018 to July 2019. Exposures: Digital breast tomosynthesis and DM screening examinations. Main Outcomes and Measures: Recall rate and cancer detection rate. Results: A total of 198 radiologists interpreted 2 252 065 DM and DBT examinations (2 000 681 [88.8%] DM examinations; 251 384 [11.2%] DBT examinations; 710 934 patients [31.6%] aged 50-59 years; 1 448 981 [64.3%] non-Hispanic white). Among the 126 radiologists (63.6%) who interpreted DBT examinations, 83 (65.9%) had unadjusted DM recall rates of no more than 12% before using DBT, with a median (interquartile range) recall rate of 10.0% (7.5%-13.0%). On DBT examinations, 96 (76.2%) had an unadjusted recall rate of no more than 12%, with a median (interquartile range) recall rate of 8.8% (6.3%-11.3%). A secular trend in recall rate was observed, with the multivariable-adjusted risk of recall on screening examinations declining by 1.2% (95% CI, 0.9%-1.5%) per year. After adjusting for examination characteristics and secular trends, recall rates were 15% lower on DBT examinations compared with DM examinations interpreted before DBT use (relative risk, 0.85; 95% CI, 0.83-0.87). Adjusted recall rates were significantly lower on DBT examinations compared with DM examinations interpreted before DBT use for 45 radiologists (35.7%) and significantly higher for 18 (14.3%); 63 (50.0%) had no statistically significant change. The unadjusted cancer detection rate on DBT was 5.3 per 1000 examinations (95% CI, 5.0-5.7 per 1000 examinations) compared with 4.7 per 1000 examinations (95% CI, 4.6-4.8 per 1000 examinations) on DM examinations interpreted before DM use (multivariable-adjusted risk ratio, 1.21; 95% CI, 1.11-1.33). Conclusions and Relevance: In this study, DBT was associated with an overall decrease in recall rate and an increase in cancer detection rate. However, our results indicated that there is wide variability among radiologists, including a subset of radiologists who experienced increased recall rates on DBT examinations. Radiology practices should audit radiologist DBT screening performance and consider additional DBT training for radiologists whose performance does not improve as expected.

Indexed as

MammographyRadiologistsAdultAgedAged, 80 and overBreast NeoplasmsCohort StudiesFemaleHumansMiddle AgedUnited States

Identifiers

PMID32227180
PMCPMC7292996
OpenAlexW3013254027

What OpenQuestion holds

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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.