Evidence map›Paper›PMID 25794085›Full record

ArticleAJR. American journal of roentgenology2015

Do mammographic technologists affect radiologists' diagnostic mammography interpretative performance?

Louise M Henderson, Thad Benefield, J Michael Bowling, Danielle D Durham, Mary W Marsh, Bruce F Schroeder, Bonnie C Yankaskas

Open access · greenAbstract read
In one paragraph

Article in AJR. American journal of roentgenology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Characterizing the Mammography Technologist Workforce in North Carolina.Journal of the American College of Radiology : JACR · 2015
    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 at 1 institution in 1 country.

Louise M Henderson1 Department of Radiology, The University of North Carolina, CB 7515, Chapel Hill, NC 27599-7515.
Thad Benefield
J Michael Bowling
Danielle D Durham
Mary W Marsh
Bruce F Schroeder
Bonnie C Yankaskas
University of North Carolina at Chapel Hill · US

Funding

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
UTILITY AND OUTCOMES FROM MAMMOGRAPHY IN NORTH CAROLINAU01CA070040 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI YANKASKAS, BONNIE C · 1995 to 2011
$6.4M
Technologists Effect on the Accuracy of Mammography (TEAM)R01CA155342 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HENDERSON, LOUISE · 2012 to 2015
$1.2M
NCI NIH HHS P01 CA154292NCI NIH HHS R01 CA155342NCI NIH HHS R01CA155342NCI NIH HHS U01 CA070040NCI NIH HHS U01CA70040
6 · The paper itself

Abstract

objectiveThe purpose of this study was to determine whether the technologist has an effect on the radiologists' interpretative performance of diagnostic mammography. MATERIALS AND

methodsUsing data from a community-based mammography registry from 1994 to 2009, we identified 162,755 diagnostic mammograms interpreted by 286 radiologists and performed by 303 mammographic technologists. We calculated sensitivity, false-positive rate, and positive predictive value (PPV) of the recommendation for biopsy from mammography for examinations performed (i.e., images acquired) by each mammographic technologist, separately for conventional (film-screen) and digital modalities. We assessed the variability of these performance measures among mammographic technologists, using mixed effects logistic regression and taking into account the clustering of examinations within women, radiologists, and radiology practices.

resultsAmong the 291 technologists performing conventional examinations, mean sensitivity of the examinations performed was 83.0% (95% CI, 80.8-85.2%), mean false-positive rate was 8.5% (95% CI, 8.0-9.0%), and mean PPV of the recommendation for biopsy from mammography was 27.1% (95% CI, 24.8-29.4%). For the 45 technologists performing digital examinations, mean sensitivity of the examinations they performed was 79.6% (95% CI, 73.1-86.2%), mean false-positive rate was 8.8% (95% CI, 7.5-10.0%), and mean PPV of the recommendation for biopsy from mammography was 23.6% (95% CI, 18.8-28.4%). We found significant variation by technologist in the sensitivity, false-positive rate, and PPV of the recommendation for biopsy from mammography for conventional but not digital mammography (p < 0.0001 for all three interpretive performance measures).

conclusionOur results suggest that the technologist has an influence on radiologists' interpretive performance for diagnostic conventional but not digital mammography. Future studies should examine why this difference between modalities exists and determine if similar patterns are observed for screening mammography.

Indexed as

Clinical CompetenceInterprofessional RelationsPractice Patterns, Physicians'Technology, RadiologicBiopsyBreast NeoplasmsDiagnosis, DifferentialFalse Positive ReactionsFemaleHumansMammographyMass ScreeningObserver VariationPredictive Value of TestsRegistriesSensitivity and Specificitydiagnostic mammographyfalse-positive ratepositive predictive value of biopsysensitivityvariability

Identifiers

PMID25794085
PMCPMC4465588
OpenAlexW2031108936

What OpenQuestion holds

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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.