Literature DB >> 25435185

The influence of mammographic technologists on radiologists' ability to interpret screening mammograms in community practice.

Louise M Henderson1, Thad Benefield2, Mary W Marsh2, Bruce F Schroeder3, Danielle D Durham4, Bonnie C Yankaskas2, J Michael Bowling5.   

Abstract

RATIONALE AND
OBJECTIVES: To determine whether the mammographic technologist has an effect on the radiologists' interpretative performance of screening mammography in community practice.
MATERIALS AND METHODS: In this institutional review board-approved retrospective cohort study, we included Carolina Mammography Registry data from 372 radiologists and 356 mammographic technologists from 1994 to 2009 who performed 1,003,276 screening mammograms. Measures of interpretative performance (recall rate, sensitivity, specificity, positive predictive value [PPV1], and cancer detection rate [CDR]) were ascertained prospectively with cancer outcomes collected from the state cancer registry and pathology reports. To determine if the mammographic technologist influenced the radiologists' performance, we used mixed effects logistic regression models, including a radiologist-specific random effect and taking into account the clustering of examinations across women, separately for screen-film mammography (SFM) and full-field digital mammography (FFDM).
RESULTS: Of the 356 mammographic technologists included, 343 performed 889,347 SFM examinations, 51 performed 113,929 FFDM examinations, and 38 performed both SFM and FFDM examinations. A total of 4328 cancers were reported for SFM and 564 cancers for FFDM. The technologists had a statistically significant effect on the radiologists' recall rate, sensitivity, specificity, and CDR for both SFM and FFDM (P values <.01). For PPV1, variability by technologist was observed for SFM (P value <.0001) but not for FFDM (P value = .088).
CONCLUSIONS: The interpretative performance of radiologists in screening mammography varies substantially by the technologist performing the examination. Additional studies should aim to identify technologist characteristics that may explain this variation.
Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Mammography; observer variation; sensitivity and specificity

Mesh:

Year:  2014        PMID: 25435185      PMCID: PMC4324008          DOI: 10.1016/j.acra.2014.09.013

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  37 in total

1.  Use of clinical history affects accuracy of interpretive performance of screening mammography.

Authors:  Patricia A Carney; Andrea J Cook; Diana L Miglioretti; Stephen A Feig; Erin Aiello Bowles; Berta M Geller; Karla Kerlikowske; Mark Kettler; Tracy Onega; Joann G Elmore
Journal:  J Clin Epidemiol       Date:  2011-10-15       Impact factor: 6.437

2.  Concordance of breast imaging reporting and data system assessments and management recommendations in screening mammography.

Authors:  Stephen H Taplin; Laura E Ichikawa; Karla Kerlikowske; Virginia L Ernster; Robert D Rosenberg; Bonnie C Yankaskas; Patricia A Carney; Berta M Geller; Nicole Urban; Mark B Dignan; William E Barlow; Rachel Ballard-Barbash; Edward A Sickles
Journal:  Radiology       Date:  2002-02       Impact factor: 11.105

3.  Pre-reading mammograms by specialised breast technologists: legal implications for technologist and radiologist in The Netherlands.

Authors:  F J H M van den Biggelaar; K Flobbe; J M A van Engelshoven; N P Y M de Bijl
Journal:  Eur J Health Law       Date:  2009-09

4.  Influence of annual interpretive volume on screening mammography performance in the United States.

Authors:  Diana S M Buist; Melissa L Anderson; Sebastien J P A Haneuse; Edward A Sickles; Robert A Smith; Patricia A Carney; Stephen H Taplin; Robert D Rosenberg; Berta M Geller; Tracy L Onega; Barbara S Monsees; Lawrence W Bassett; Bonnie C Yankaskas; Joann G Elmore; Karla Kerlikowske; Diana L Miglioretti
Journal:  Radiology       Date:  2011-02-22       Impact factor: 11.105

5.  Surgeon-read screening mammography: an analysis of 11,948 examinations.

Authors:  Justus P Apffelstaedt; Veronica Steenkamp; Karin J Baatjes
Journal:  Ann Surg Oncol       Date:  2010-09-19       Impact factor: 5.344

6.  When radiologists perform best: the learning curve in screening mammogram interpretation.

Authors:  Diana L Miglioretti; Charlotte C Gard; Patricia A Carney; Tracy L Onega; Diana S M Buist; Edward A Sickles; Karla Kerlikowske; Robert D Rosenberg; Bonnie C Yankaskas; Berta M Geller; Joann G Elmore
Journal:  Radiology       Date:  2009-09-29       Impact factor: 11.105

7.  Radiologist characteristics associated with interpretive performance of diagnostic mammography.

Authors:  Diana L Miglioretti; Rebecca Smith-Bindman; Linn Abraham; R James Brenner; Patricia A Carney; Erin J Aiello Bowles; Diana S M Buist; Joann G Elmore
Journal:  J Natl Cancer Inst       Date:  2007-12-11       Impact factor: 13.506

8.  Variability in interpretive performance at screening mammography and radiologists' characteristics associated with accuracy.

Authors:  Joann G Elmore; Sara L Jackson; Linn Abraham; Diana L Miglioretti; Patricia A Carney; Berta M Geller; Bonnie C Yankaskas; Karla Kerlikowske; Tracy Onega; Robert D Rosenberg; Edward A Sickles; Diana S M Buist
Journal:  Radiology       Date:  2009-10-28       Impact factor: 11.105

9.  Decreased accuracy in interpretation of community-based screening mammography for women with multiple clinical risk factors.

Authors:  Andrea J Cook; Joann G Elmore; Diana L Miglioretti; Edward A Sickles; Erin J Aiello Bowles; Gary R Cutter; Patricia A Carney
Journal:  J Clin Epidemiol       Date:  2009-09-09       Impact factor: 6.437

10.  Inter-observer variability in mammography screening and effect of type and number of readers on screening outcome.

Authors:  L E M Duijm; M W J Louwman; J H Groenewoud; L V van de Poll-Franse; J Fracheboud; J W Coebergh
Journal:  Br J Cancer       Date:  2009-03-03       Impact factor: 7.640

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  3 in total

1.  Characterizing the Mammography Technologist Workforce in North Carolina.

Authors:  Louise M Henderson; Mary W Marsh; Thad Benefield; Elizabeth Pearsall; Danielle Durham; Bruce F Schroeder; J Michael Bowling; Cheryl A Viglione; Bonnie C Yankaskas
Journal:  J Am Coll Radiol       Date:  2015-12       Impact factor: 5.532

2.  Impact of Full-Field Digital Mammography Versus Film-Screen Mammography in Population Screening: A Meta-Analysis.

Authors:  Rachel Farber; Nehmat Houssami; Sally Wortley; Gemma Jacklyn; Michael L Marinovich; Kevin McGeechan; Alexandra Barratt; Katy Bell
Journal:  J Natl Cancer Inst       Date:  2021-01-04       Impact factor: 13.506

3.  The influence of breast density and key demographics of radiographers on mammography reporting performance - a pilot study.

Authors:  Maram Alakhras; Dana S Al-Mousa; Alaa K Alqadi; Haneen A Sabaneh; Ruba M Karasneh; Kelly M Spuur
Journal:  J Med Radiat Sci       Date:  2021-05-24
  3 in total

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