Evidence map›Paper›PMID 25960128›Full record

ArticleJournal of comparative effectiveness research2015

Predictors of preoperative MRI for breast cancer: differences by data source.

Elizabeth T Loggers, Hongyuan Gao, Laura S Gold, Larry Kessler, Ruth Etzioni, Diana Sm Buist, ADVICE Investigators

Abstract read
In one paragraph

Article in Journal of comparative effectiveness research, 2015. 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

7 authors.

Elizabeth T LoggersFred Hutchinson Cancer Research Center, Clinical Research Division, 1100 Fairview Ave, D5-380, Seattle, WA 98109, USA.
Hongyuan GaoGroup Health Research Institute, Seattle, WA, USA.
Laura S GoldSchool of Pharmacy, University of Washington, Seattle, WA, USA.
Larry KesslerDepartment of Health Services, School of Public Health, University of Washington, Seattle, WA, USA.
Ruth EtzioniDepartment of Health Services, School of Public Health, University of Washington, Seattle, WA, USA.
Diana Sm BuistGroup Health Research Institute, Seattle, WA, USA.
ADVICE Investigators

Funding

Risk-based Imaging Strategies to Improve Breast Cancer Surveillance OutcomesP01CA154292 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Anna N. A. Tosteson · 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
SURVEILLANCE EPIDEMIOLOGY &END RESULTS PROGRAMN01CN067009 · CN · FRED HUTCHINSON CANCER RESEARCH CENTER · PI THOMAS, DAVID B · 1996 to 1997
–
NCI NIH HHS N01 CN067009NCI NIH HHS N01 PC035142NCI NIH HHS P01 CA154292NCI NIH HHS RC2 CA148577
6 · The paper itself

Abstract

aimInvestigate how the results of predictive models of preoperative MRI for breast cancer change based on available data. MATERIALS &

methodsA total of 1919 insured women aged ≥18 with stage 0-III breast cancer diagnosed 2002-2009. Four models were compared using nested multivariable logistic, backwards stepwise regression; model fit was assessed via area under the curve (AUC), R

resultsMRI recipients (n = 245) were more recently diagnosed, younger, less comorbid, with higher stage disease. Significant variables included: Model 1/Claims (AUC = 0.76, R

conclusionClinical variables accounted for little of the observed variability compared with claims data.

Indexed as

breast cancerchart abstractionclaims/utilization dataMRIpredictive variablesrisk factor datasurvey data

Identifiers

PMID25960128
PMCPMC4641841

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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.