Literature DB >> 21343539

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

Diana S M Buist1, 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.   

Abstract

PURPOSE: To examine whether U.S. radiologists' interpretive volume affects their screening mammography performance.
MATERIALS AND METHODS: Annual interpretive volume measures (total, screening, diagnostic, and screening focus [ratio of screening to diagnostic mammograms]) were collected for 120 radiologists in the Breast Cancer Surveillance Consortium (BCSC) who interpreted 783 965 screening mammograms from 2002 to 2006. Volume measures in 1 year were examined by using multivariate logistic regression relative to screening sensitivity, false-positive rates, and cancer detection rate the next year. BCSC registries and the Statistical Coordinating Center received institutional review board approval for active or passive consenting processes and a Federal Certificate of Confidentiality and other protections for participating women, physicians, and facilities. All procedures were compliant with the terms of the Health Insurance Portability and Accountability Act.
RESULTS: Mean sensitivity was 85.2% (95% confidence interval [CI]: 83.7%, 86.6%) and was significantly lower for radiologists with a greater screening focus (P = .023) but did not significantly differ by total (P = .47), screening (P = .33), or diagnostic (P = .23) volume. The mean false-positive rate was 9.1% (95% CI: 8.1%, 10.1%), with rates significantly higher for radiologists who had the lowest total (P = .008) and screening (P = .015) volumes. Radiologists with low diagnostic volume (P = .004 and P = .008) and a greater screening focus (P = .003 and P = .002) had significantly lower false-positive and cancer detection rates, respectively. Median invasive tumor size and proportion of cancers detected at early stages did not vary by volume.
CONCLUSION: Increasing minimum interpretive volume requirements in the United States while adding a minimal requirement for diagnostic interpretation could reduce the number of false-positive work-ups without hindering cancer detection. These results provide detailed associations between mammography volumes and performance for policymakers to consider along with workforce, practice organization, and access issues and radiologist experience when reevaluating requirements. © RSNA, 2011.

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Year:  2011        PMID: 21343539      PMCID: PMC3064821          DOI: 10.1148/radiol.10101698

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  25 in total

1.  Standardized abnormal interpretation and cancer detection ratios to assess reading volume and reader performance in a breast screening program.

Authors:  L Kan; I A Olivotto; L J Warren Burhenne; E A Sickles; A J Coldman
Journal:  Radiology       Date:  2000-05       Impact factor: 11.105

2.  Improving the accuracy of mammography: volume and outcome relationships.

Authors:  Laura Esserman; Helen Cowley; Carey Eberle; Alastair Kirkpatrick; Sophia Chang; Kevin Berbaum; Alastair Gale
Journal:  J Natl Cancer Inst       Date:  2002-03-06       Impact factor: 13.506

3.  Association of volume and volume-independent factors with accuracy in screening mammogram interpretation.

Authors:  Craig A Beam; Emily F Conant; Edward A Sickles
Journal:  J Natl Cancer Inst       Date:  2003-02-19       Impact factor: 13.506

4.  Mammographic characteristics of 115 missed cancers later detected with screening mammography and the potential utility of computer-aided detection.

Authors:  R L Birdwell; D M Ikeda; K F O'Shaughnessy; E A Sickles
Journal:  Radiology       Date:  2001-04       Impact factor: 11.105

5.  Time trends in radiologists' interpretive performance at screening mammography from the community-based Breast Cancer Surveillance Consortium, 1996-2004.

Authors:  Laura E Ichikawa; William E Barlow; Melissa L Anderson; Stephen H Taplin; Berta M Geller; R James Brenner
Journal:  Radiology       Date:  2010-05-26       Impact factor: 11.105

6.  Interval cancer peer review in East Anglia: implications for monitoring doctors as well as the NHS breast screening programme.

Authors:  P D Britton; J McCann; D O'Driscoll; G Hunnam; R M Warren
Journal:  Clin Radiol       Date:  2001-01       Impact factor: 2.350

7.  The impact of alternative practices on the cost and quality of mammographic screening in the United States.

Authors:  E Burnside; J Belkora; L Esserman
Journal:  Clin Breast Cancer       Date:  2001-07       Impact factor: 3.225

8.  The visibility of cancer on previous mammograms in retrospective review.

Authors:  I Saarenmaa; T Salminen; U Geiger; P Heikkinen; S Hyvärinen; J Isola; V Kataja; M L Kokko; R Kokko; E Kumpulainen; A Kärkkäinen; J Pakkanen; P Peltonen; A Piironen; A Salo; M L Talviala; M Hakama
Journal:  Clin Radiol       Date:  2001-01       Impact factor: 2.350

9.  Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography.

Authors:  Patricia A Carney; Diana L Miglioretti; Bonnie C Yankaskas; Karla Kerlikowske; Robert Rosenberg; Carolyn M Rutter; Berta M Geller; Linn A Abraham; Steven H Taplin; Mark Dignan; Gary Cutter; Rachel Ballard-Barbash
Journal:  Ann Intern Med       Date:  2003-02-04       Impact factor: 25.391

10.  International variation in screening mammography interpretations in community-based programs.

Authors:  Joann G Elmore; Connie Y Nakano; Thomas D Koepsell; Laurel M Desnick; Carl J D'Orsi; David F Ransohoff
Journal:  J Natl Cancer Inst       Date:  2003-09-17       Impact factor: 13.506

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  39 in total

1.  An interactive system for computer-aided diagnosis of breast masses.

Authors:  Xingwei Wang; Lihua Li; Wei Liu; Weidong Xu; Dror Lederman; Bin Zheng
Journal:  J Digit Imaging       Date:  2012-10       Impact factor: 4.056

2.  Mammographic interpretive volume and diagnostic mammogram interpretation performance in community practice.

Authors:  Sebastien Haneuse; Diana S M Buist; Diana L Miglioretti; Melissa L Anderson; Patricia A Carney; Tracy Onega; Berta M Geller; Karla Kerlikowske; Robert D Rosenberg; Bonnie C Yankaskas; Joann G Elmore; Stephen H Taplin; Robert A Smith; Edward A Sickles
Journal:  Radiology       Date:  2011-11-21       Impact factor: 11.105

3.  Radiologists' interpretive skills in screening vs. diagnostic mammography: are they related?

Authors:  Joann G Elmore; Andrea J Cook; Andy Bogart; Patricia A Carney; Berta M Geller; Stephen H Taplin; Diana S M Buist; Tracy Onega; Christoph I Lee; Diana L Miglioretti
Journal:  Clin Imaging       Date:  2016-07-01       Impact factor: 1.605

4.  Comparative effectiveness of digital versus film-screen mammography in community practice in the United States: a cohort study.

Authors:  Karla Kerlikowske; Rebecca A Hubbard; Diana L Miglioretti; Berta M Geller; Bonnie C Yankaskas; Constance D Lehman; Stephen H Taplin; Edward A Sickles
Journal:  Ann Intern Med       Date:  2011-10-18       Impact factor: 25.391

5.  Digital Breast Tomosynthesis: Radiologist Learning Curve.

Authors:  Diana L Miglioretti; Linn Abraham; Christoph I Lee; Diana S M Buist; Sally D Herschorn; Brian L Sprague; Louise M Henderson; Anna N A Tosteson; Karla Kerlikowske
Journal:  Radiology       Date:  2019-02-26       Impact factor: 11.105

6.  Prediction of near-term breast cancer risk based on bilateral mammographic feature asymmetry.

Authors:  Maxine Tan; Bin Zheng; Pandiyarajan Ramalingam; David Gur
Journal:  Acad Radiol       Date:  2013-12       Impact factor: 3.173

7.  Reduction of false-positive recalls using a computerized mammographic image feature analysis scheme.

Authors:  Maxine Tan; Jiantao Pu; Bin Zheng
Journal:  Phys Med Biol       Date:  2014-07-17       Impact factor: 3.609

Review 8.  Imaging-based screening: maximizing benefits and minimizing harms.

Authors:  Jessica C Germino; Joann G Elmore; Ruth C Carlos; Christoph I Lee
Journal:  Clin Imaging       Date:  2015-06-12       Impact factor: 1.605

9.  A new quantitative image analysis method for improving breast cancer diagnosis using DCE-MRI examinations.

Authors:  Qian Yang; Lihua Li; Juan Zhang; Guoliang Shao; Bin Zheng
Journal:  Med Phys       Date:  2015-01       Impact factor: 4.071

10.  Applying a new bilateral mammographic density segmentation method to improve accuracy of breast cancer risk prediction.

Authors:  Shiju Yan; Yunzhi Wang; Faranak Aghaei; Yuchen Qiu; Bin Zheng
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-07-19       Impact factor: 2.924

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