Literature DB >> 22106351

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

Sebastien Haneuse1, 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.   

Abstract

PURPOSE: To investigate the association between radiologist interpretive volume and diagnostic mammography performance in community-based settings.
MATERIALS AND METHODS: This study received institutional review board approval and was HIPAA compliant. A total of 117,136 diagnostic mammograms that were interpreted by 107 radiologists between 2002 and 2006 in the Breast Cancer Surveillance Consortium were included. Logistic regression analysis was used to estimate the adjusted effect on sensitivity and the rates of false-positive findings and cancer detection of four volume measures: annual diagnostic volume, screening volume, total volume, and diagnostic focus (percentage of total volume that is diagnostic). Analyses were stratified by the indication for imaging: additional imaging after screening mammography or evaluation of a breast concern or problem.
RESULTS: Diagnostic volume was associated with sensitivity; the odds of a true-positive finding rose until a diagnostic volume of 1000 mammograms was reached; thereafter, they either leveled off (P < .001 for additional imaging) or decreased (P = .049 for breast concerns or problems) with further volume increases. Diagnostic focus was associated with false-positive rate; the odds of a false-positive finding increased until a diagnostic focus of 20% was reached and decreased thereafter (P < .024 for additional imaging and P < .001 for breast concerns or problems with no self-reported lump). Neither total volume nor screening volume was consistently associated with diagnostic performance.
CONCLUSION: Interpretive volume and diagnostic performance have complex multifaceted relationships. Our results suggest that diagnostic interpretive volume is a key determinant in the development of thresholds for considering a diagnostic mammogram to be abnormal. Current volume regulations do not distinguish between screening and diagnostic mammography, and doing so would likely be challenging. © RSNA, 2011.

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Year:  2011        PMID: 22106351      PMCID: PMC3244665          DOI: 10.1148/radiol.11111026

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


  17 in total

1.  Performance of first mammography examination in women younger than 40 years.

Authors:  Bonnie C Yankaskas; Sebastien Haneuse; Julie M Kapp; Karla Kerlikowske; Berta Geller; Diana S M Buist
Journal:  J Natl Cancer Inst       Date:  2010-05-03       Impact factor: 13.506

2.  Diagnostic value of radiological breast imaging in a non-screening population.

Authors:  K Flobbe; E S van der Linden; A G Kessels; J M van Engelshoven
Journal:  Int J Cancer       Date:  2001-05-15       Impact factor: 7.396

3.  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

4.  Performance of clinical mammography: a nationwide study from Denmark.

Authors:  Allan Jensen; Ilse Vejborg; Niels Severinsen; Susanne Nielsen; Fritz Rank; Gerd Just Mikkelsen; Jørgen Hilden; Dorte Vistisen; Uffe Dyreborg; Elsebeth Lynge
Journal:  Int J Cancer       Date:  2006-07-01       Impact factor: 7.396

5.  Accuracy of diagnostic mammography at facilities serving vulnerable women.

Authors:  L Elizabeth Goldman; Rod Walker; Diana L Miglioretti; Rebecca Smith-Bindman; Karla Kerlikowske
Journal:  Med Care       Date:  2011-01       Impact factor: 2.983

6.  Performance of diagnostic mammography for women with signs or symptoms of breast cancer.

Authors:  William E Barlow; Constance D Lehman; Yingye Zheng; Rachel Ballard-Barbash; Bonnie C Yankaskas; Gary R Cutter; Patricia A Carney; Berta M Geller; Robert Rosenberg; Karla Kerlikowske; Donald L Weaver; Stephen H Taplin
Journal:  J Natl Cancer Inst       Date:  2002-08-07       Impact factor: 13.506

7.  Performance parameters for screening and diagnostic mammography: specialist and general radiologists.

Authors:  Edward A Sickles; Dulcy E Wolverton; Katherine E Dee
Journal:  Radiology       Date:  2002-09       Impact factor: 11.105

8.  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

9.  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

10.  Variability of interpretive accuracy among diagnostic mammography facilities.

Authors:  Sara L Jackson; Stephen H Taplin; Edward A Sickles; Linn Abraham; William E Barlow; Patricia A Carney; Berta Geller; Eric A Berns; Gary R Cutter; Joann G Elmore
Journal:  J Natl Cancer Inst       Date:  2009-05-26       Impact factor: 13.506

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  11 in total

1.  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

2.  How Many of the Biopsy Decisions Taken at Inexperienced Breast Radiology Units Were Correct?

Authors:  Özlem Demircioğlu; Meral Uluer; Erkin Arıbal
Journal:  J Breast Health       Date:  2017-01-01

3.  Training the ACRIN 6666 Investigators and effects of feedback on breast ultrasound interpretive performance and agreement in BI-RADS ultrasound feature analysis.

Authors:  Wendie A Berg; Jeffrey D Blume; Jean B Cormack; Ellen B Mendelson
Journal:  AJR Am J Roentgenol       Date:  2012-07       Impact factor: 3.959

4.  Effect of radiologists' diagnostic work-up volume on interpretive performance.

Authors:  Diana S M Buist; Melissa L Anderson; Robert A Smith; Patricia A Carney; Diana L Miglioretti; Barbara S Monsees; Edward A Sickles; Stephen H Taplin; Berta M Geller; Bonnie C Yankaskas; Tracy L Onega
Journal:  Radiology       Date:  2014-06-24       Impact factor: 11.105

5.  Factors associated with breast screening radiologists' annual mammogram reading volume in Italy.

Authors:  Doralba Morrone; Livia Giordano; Franca Artuso; Daniela Bernardi; Chiara Fedato; Alfonso Frigerio; Daniela Giorgi; Carlo Naldoni; Gianni Saguatti; Daniela Severi; Mario Taffurelli; Daniela Terribile; Leonardo Ventura; Lauro Bucchi
Journal:  Radiol Med       Date:  2016-03-31       Impact factor: 3.469

6.  Do mammographic technologists affect radiologists' diagnostic mammography interpretative performance?

Authors:  Louise M Henderson; Thad Benefield; J Michael Bowling; Danielle D Durham; Mary W Marsh; Bruce F Schroeder; Bonnie C Yankaskas
Journal:  AJR Am J Roentgenol       Date:  2015-04       Impact factor: 3.959

7.  Patient and Radiologist Characteristics Associated With Accuracy of Two Types of Diagnostic Mammograms.

Authors:  Sara L Jackson; Linn Abraham; Diana L Miglioretti; Diana S M Buist; Karla Kerlikowske; Tracy Onega; Patricia A Carney; Edward A Sickles; Joann G Elmore
Journal:  AJR Am J Roentgenol       Date:  2015-08       Impact factor: 3.959

8.  Strengthening Health Services Research Using Target Trial Emulation: An Application to Volume-Outcomes Studies.

Authors:  Arin L Madenci; Kerollos Nashat Wanis; Zara Cooper; Sebastien Haneuse; S V Subramanian; Albert Hofman; Miguel A Hernán
Journal:  Am J Epidemiol       Date:  2021-11-02       Impact factor: 5.363

9.  A machine learning model based on readers' characteristics to predict their performances in reading screening mammograms.

Authors:  Ziba Gandomkar; Sarah J Lewis; Tong Li; Ernest U Ekpo; Patrick C Brennan
Journal:  Breast Cancer       Date:  2022-02-05       Impact factor: 3.307

10.  Interpretive Performance and Inter-Observer Agreement on Digital Mammography Test Sets.

Authors:  Sung Hun Kim; Eun Hye Lee; Jae Kwan Jun; You Me Kim; Yun Woo Chang; Jin Hwa Lee; Hye Won Kim; Eun Jung Choi
Journal:  Korean J Radiol       Date:  2019-02       Impact factor: 3.500

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