Evidence map›Paper›PMID 33764423›Full record

ArticleJAMA network open2021

Assessment of a Risk-Based Approach for Triaging Mammography Examinations During Periods of Reduced Capacity.

Diana L Miglioretti, Michael C S Bissell, Karla Kerlikowske, Diana S M Buist, Steven R Cummings, Louise M Henderson, Tracy Onega, Ellen S O'Meara, Garth H Rauscher, Brian L Sprague and 4 more

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
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  3. Observational
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 12 institutions in 1 country.

Diana L MigliorettiDivision of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis.
Michael C S BissellDivision of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis.
Karla KerlikowskeDepartments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco.
Diana S M BuistKaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle.
Steven R CummingsSan Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco.
Louise M HendersonDepartment of Radiology, University of North Carolina, Chapel Hill.
Tracy OnegaHuntsman Cancer Institute, Department of Population Health Sciences, University of Utah, Salt Lake City.
Ellen S O'MearaKaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle.
Garth H RauscherDivision of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago.
Brian L SpragueOffice of Health Promotion Research, University of Vermont Cancer Center, Department of Surgery, Larner College of Medicine at the University of Vermont, Burlington.
Anna N A TostesonNorris Cotton Cancer Center, The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire.
Karen J WernliKaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle.
Janie M LeeDepartment of Radiology, University of Washington School of Medicine, Seattle.
Christoph I LeeDepartment of Radiology, University of Washington School of Medicine, Seattle.
Kaiser Permanente · USUniversity of California, Davis · USCalifornia Pacific Medical Center · USDartmouth Institute for Health Policy and Clinical Practice · USFred Hutch Cancer Center · USHuntsman Cancer Institute · USKaiser Permanente Washington Health Research Institute · USUniversity of California, San Francisco · USUniversity of Illinois Chicago · USUniversity of North Carolina at Chapel Hill · USUniversity of Vermont · 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: Breast cancer screening, surveillance, and diagnostic imaging services were profoundly limited during the initial phase of the coronavirus disease 2019 (COVID-19) pandemic. Objective: To develop a risk-based strategy for triaging mammograms during periods of decreased capacity. Design, Setting, and Participants: This population-based cohort study used data collected prospectively from mammography examinations performed in 2014 to 2019 at 92 radiology facilities in the Breast Cancer Surveillance Consortium. Participants included individuals undergoing mammography. Data were analyzed from August 10 to November 3, 2020. Exposures: Clinical indication for screening, breast symptoms, personal history of breast cancer, age, time since last mammogram/screening interval, family history of breast cancer, breast density, and history of high-risk breast lesion. Main Outcomes and Measures: Combinations of clinical indication, clinical history, and breast cancer risk factors that subdivided mammograms into risk groups according to their cancer detection rate were identified using classification and regression trees. Results: The cohort included 898 415 individuals contributing 1 878 924 mammograms (mean [SD] age at mammogram, 58.6 [11.2] years) interpreted by 448 radiologists, with 1 722 820 mammograms in individuals without a personal history of breast cancer and 156 104 mammograms in individuals with a history of breast cancer. Most individuals were aged 50 to 69 years at imaging (1 113 174 mammograms [59.2%]), and 204 305 (11.2%) were Black, 206 087 (11.3%) were Asian or Pacific Islander, 126 677 (7.0%) were Hispanic or Latina, and 40 021 (2.2%) were another race/ethnicity or mixed race/ethnicity. Cancer detection rates varied widely based on clinical indication, breast symptoms, personal history of breast cancer, and age. The 12% of mammograms with very high (89.6 [95% CI, 82.3-97.5] to 122.3 [95% CI, 108.1-138.0] cancers detected per 1000 mammograms) or high (36.1 [95% CI, 33.1-39.3] to 47.5 [95% CI, 42.4-53.3] cancers detected per 1000 mammograms) cancer detection rates accounted for 55% of all detected cancers and included mammograms to evaluate an abnormal mammogram or breast lump in individuals of all ages regardless of breast cancer history, to evaluate breast symptoms other than lump in individuals with a breast cancer history or without a history but aged 60 years or older, and for short-interval follow-up in individuals aged 60 years or older without a breast cancer history. The 44.2% of mammograms with very low cancer detection rates accounted for 13.1% of detected cancers and included annual screening mammograms in individuals aged 50 to 69 years (3.8 [95% CI, 3.5-4.1] cancers detected per 1000 mammograms) and all screening mammograms in individuals younger than 50 years regardless of screening interval (2.8 [95% CI, 2.6-3.1] cancers detected per 1000 mammograms). Conclusions and Relevance: In this population-based cohort study, clinical indication and individual risk factors were associated with cancer detection and may be useful for prioritizing mammography in times and settings of decreased capacity.

Indexed as

COVID-19MammographyPandemicsAgedBreastBreast NeoplasmsCohort StudiesEarly Detection of CancerFemaleHealth Care RationingHumansMass ScreeningMedical History TakingMiddle AgedPhysical ExaminationRadiology

Identifiers

PMID33764423
PMCPMC7994953
OpenAlexW3137336496

What OpenQuestion holds

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LicenceCC BY
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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.