Evidence map›Paper›PMID 33162349›Full record

ArticleClinical breast cancer2021

Development and Implementation of an Algorithm to Guide MRI Screening in Patients With a Personal History of Treated Breast Cancer.

Roberta M Strigel, Erin Bravo, Amye J Tevaarwerk, Bethany M Anderson, Amy L Stella, Heather B Neuman

Abstract read
In one paragraph

Article in Clinical breast cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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.

Roberta M StrigelDepartment of Radiology, University of Wisconsin, Madison, WI; Department of Medical Physics, University of Wisconsin, Madison, WI; Carbone Cancer Center, University of Wisconsin, Madison, WI.
Erin BravoDepartment of Radiology, University of Wisconsin, Madison, WI.
Amye J TevaarwerkCarbone Cancer Center, University of Wisconsin, Madison, WI; Department of Medicine, University of Wisconsin, Madison, WI.
Bethany M AndersonCarbone Cancer Center, University of Wisconsin, Madison, WI; Department of Human Oncology, University of Wisconsin, Madison, WI.
Amy L StellaCarbone Cancer Center, University of Wisconsin, Madison, WI; Department of Medicine, University of Wisconsin, Madison, WI.
Heather B NeumanCarbone Cancer Center, University of Wisconsin, Madison, WI; Department of Surgery, University of Wisconsin, Madison, WI. Electronic address: neuman@surgery.wisc.edu.

Funding

NCI NIH HHS L30 CA179525
6 · The paper itself

Abstract

introductionLimited data exist to guide appropriate use of magnetic resonance imaging (MRI) screening in women with a personal history of breast cancer. We developed an algorithm to inform the use of MRI screening in patients with a personal history, implemented it, and evaluated initial implementation at our community and academic practice sites. PATIENTS AND

methodsA multidisciplinary committee of providers developed the initial algorithm on the basis of available literature and consensus. To evaluate projected MRI utilization based on the initial algorithm and inform algorithm revision, charts of patients < 80 years of age diagnosed and treated in 2010 with stage 0-III breast cancer (n = 236) were reviewed. The revised algorithm was implemented into the electronic medical record (September 2013). Thirteen months after implementation (2014-2015), chart review of patients with a personal history of breast cancer who underwent screening MRI was performed to assess algorithm adherence.

resultsBefore algorithm development, 9% (20/236) of patients received MRI screening (6 genetic mutation/family history, 4 occult primary, 8 young age/breast density, 2 unknown). Use of MRI screening was projected to increase to 25% with algorithm implementation. In postimplementation review, we identified 183 patients with a personal history of breast cancer who underwent screening MRI, with 94% algorithm adherence.

conclusionWe successfully developed and implemented an algorithm to guide MRI screening in patients with a personal breast cancer history. Clinicians can use this algorithm to guide patient discussions regarding the utility of MRI screening. Further prospective study, including cancer detection rates, biopsy rate, and mortality, are necessary to confirm the algorithm's usefulness.

Indexed as

AlgorithmsAged, 80 and overBreast NeoplasmsEarly Detection of CancerFemaleHumansMagnetic Resonance ImagingMammographyPractice Guidelines as TopicCancer survivorsHigh riskImagingMagnetic resonance imagingSurveillance

Identifiers

PMID33162349
PMCPMC8812335

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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.