Evidence map›Paper›PMID 32374471›Full record

Observational studyCancer2020

New mammography screening performance metrics based on the entire screening episode.

Brian L Sprague, Diana L Miglioretti, Christoph I Lee, Hannah Perry, Anna A N Tosteson, Karla Kerlikowske

Open access · greenAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

15 citing papers in PubMed, 20 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

6 authors at 5 institutions in 1 country.

Brian L SpragueDepartment of Surgery, University of Vermont, Burlington, Vermont, USA.ORCID 0000-0001-7948-8317
Diana L MigliorettiDivision of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis, California, USA.
Christoph I LeeDepartment of Radiology, University of Washington School of Medicine, Seattle, Washington, USA.ORCID 0000-0002-8185-7721
Hannah PerryDepartment of Radiology, University of Vermont, Burlington, Vermont, USA.
Anna A N TostesonDartmouth Institute for Health Policy and Clinical Practice, Lebanon, New Hampshire, USA.
Karla KerlikowskeDepartment of Medicine, University of California San Francisco, San Francisco, California, USA.
University of Vermont · USDartmouth College · USKaiser Permanente Washington Health Research Institute · USSan Francisco VA Medical Center · USUniversity of Washington · US

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
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
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
Agency for Healthcare Research and Quality R01 HS018366-01A1AHRQ HHS R01 HS018366NCI NIH HHS P01 CA154292NCI NIH HHS P01CA154292NCI NIH HHS P30 CA023108NCI NIH HHS U54 CA163303NCI NIH HHS U54CA163303Patient-Centered Outcomes Research Institute PCS-1504-30370
6 · The paper itself

Abstract

backgroundEstablished mammography screening performance metrics use the initial screening mammography assessment because they were developed for radiologist performance auditing, yet these metrics are frequently used to inform health policy and screening decision making. The authors have developed new performance metrics based on the final assessment that consider the entire screening episode, including diagnostic workup.

methodsThe authors used data from 2,512,577 screening episodes during 2005-2017 at 146 facilities in the United States participating in the Breast Cancer Surveillance Consortium. Screening performance metrics based on the final assessment of the screening episode were compared with conventional metrics defined with the initial assessment. Results were also stratified by breast density and breast cancer risk.

resultsThe cancer detection rates were similar for the final assessment (4.1 per 1000; 95% confidence interval [CI], 3.8-4.3 per 1000) and the initial assessment (4.1 per 1000; 95% CI, 3.9-4.3 per 1000). The interval cancer rate was 12% higher when it was based on the final assessment (0.77 per 1000; 95% CI, 0.71-0.83 per 1000) versus the initial assessment (0.69 per 1000; 95% CI, 0.64-0.74 per 1000), and this resulted in a modest difference in sensitivity (84.1% [95% CI, 83.0%-85.1%] vs 85.7% [95% CI, 84.8%-86.6%], respectively). Absolute differences in the interval cancer rate between final and initial assessments increased with breast density and breast cancer risk (eg, a difference of 0.29 per 1000 for women with extremely dense breasts and a 5-year risk >2.49%).

conclusionsEstablished screening performance metrics underestimate the interval cancer rate of a mammography screening episode, particularly for women with dense breasts or an elevated breast cancer risk. Women, clinicians, policymakers, and researchers should use final-assessment performance metrics to support informed screening decisions.

Indexed as

RegistriesAdultAgedAged, 80 and overBenchmarkingBreastBreast DensityBreast NeoplasmsEarly Detection of CancerFemaleFollow-Up StudiesHumansMammographyMass ScreeningMiddle AgedProspective Studiesbreast densitybreast neoplasmsmammographymass screeningoutcome assessment

Identifiers

PMID32374471
PMCPMC7319901
OpenAlexW3022255965

What OpenQuestion holds

Textmetadata
LicenceTDM
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.