Literature DB >> 24814694

Assessing the effect of a true-positive recall case in screening mammography: does perceptual priming alter radiologists' performance?

S J Lewis1, C R Mello-Thoms, P C Brennan, W Lee, A Tan, M F McEntee, M Evanoff, M Pietrzyk, W M Reed.   

Abstract

OBJECTIVE: To measure the effect of the insertion of less-difficult malignant cases on subsequent breast cancer detection by breast imaging radiologists.
METHODS: The research comprises two studies. Study 1: 8 radiologists read 2 sets of images each consisting of 40 mammographic cases. Set A contained four abnormal cases, and Set B contained six abnormal cases, including two priming cases (less difficult malignancies) placed at intervals of three and five subsequent cases before a subtle cancer. Study 2: 16 radiologists read a third condition of the same cases, known as Set C, containing six abnormal cases and two priming cases immediately preceding the subtle cancer cases. The readers were asked to localize malignancies and give confidence ratings on decisions.
RESULTS: Although not significant, a decrease in performance was observed in Set B compared with in Set A. There was a significant increase in the receiver operating characteristic (ROC) area under the curve (z = -2.532; p = 0.0114) and location sensitivity (z = -2.128; p = 0.0333) between the first and second halves of Set A and a marginal improvement in jackknife free-response ROC figure of merit (z = -1.89; p = 0.0587) between the first and second halves of Set B. In Study 2, Set C yielded no significant differences between the two halves of the study.
CONCLUSION: Overall findings show no evidence that priming with lower difficulty malignant cases affects the detection of higher difficulty cancers; however, performance may decrease with priming. ADVANCES IN KNOWLEDGE: This research suggests that inserting additional malignant cases in screening mammography sets as an audit tool may potentially lead to a decrease in performance of experienced breast radiologists.

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Mesh:

Year:  2014        PMID: 24814694      PMCID: PMC4075586          DOI: 10.1259/bjr.20140029

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  18 in total

1.  From the laboratory to the clinic: the "prevalence effect".

Authors:  David Gur; Howard E Rockette; Thomas Warfel; Joan M Lacomis; Carl R Fuhrman
Journal:  Acad Radiol       Date:  2003-11       Impact factor: 3.173

2.  Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system.

Authors:  David Gur; Jules H Sumkin; Howard E Rockette; Marie Ganott; Christiane Hakim; Lara Hardesty; William R Poller; Ratan Shah; Luisa Wallace
Journal:  J Natl Cancer Inst       Date:  2004-02-04       Impact factor: 13.506

3.  Prevalence effect in a laboratory environment.

Authors:  David Gur; Howard E Rockette; Derek R Armfield; Arye Blachar; Jennifer K Bogan; Giuseppe Brancatelli; Cynthia A Britton; Manuel L Brown; Peter L Davis; James V Ferris; Carl R Fuhrman; Sara K Golla; Sanj Katyal; Joan M Lacomis; Barry M McCook; F Leland Thaete; Thomas E Warfel
Journal:  Radiology       Date:  2003-07       Impact factor: 11.105

4.  Cognitive psychology: rare items often missed in visual searches.

Authors:  Jeremy M Wolfe; Todd S Horowitz; Naomi M Kenner
Journal:  Nature       Date:  2005-05-26       Impact factor: 49.962

5.  The prevalence effect in a laboratory environment: Changing the confidence ratings.

Authors:  David Gur; Andriy I Bandos; Carl R Fuhrman; Amy H Klym; Jill L King; Howard E Rockette
Journal:  Acad Radiol       Date:  2007-01       Impact factor: 3.173

6.  Priming makes a stimulus more salient.

Authors:  Jan Theeuwes; Erik Van der Burg
Journal:  J Vis       Date:  2013-08-02       Impact factor: 2.240

7.  Context bias. A problem in diagnostic radiology.

Authors:  T K Egglin; A R Feinstein
Journal:  JAMA       Date:  1996-12-04       Impact factor: 56.272

8.  Diagnostic performance of digital versus film mammography for breast-cancer screening.

Authors:  Etta D Pisano; Constantine Gatsonis; Edward Hendrick; Martin Yaffe; Janet K Baum; Suddhasatta Acharyya; Emily F Conant; Laurie L Fajardo; Lawrence Bassett; Carl D'Orsi; Roberta Jong; Murray Rebner
Journal:  N Engl J Med       Date:  2005-09-16       Impact factor: 91.245

9.  Performance benchmarks for diagnostic mammography.

Authors:  Edward A Sickles; Diana L Miglioretti; Rachel Ballard-Barbash; Berta M Geller; Jessica W T Leung; Robert D Rosenberg; Rebecca Smith-Bindman; Bonnie C Yankaskas
Journal:  Radiology       Date:  2005-06       Impact factor: 11.105

10.  Analysis of cancers missed at screening mammography.

Authors:  R E Bird; T W Wallace; B C Yankaskas
Journal:  Radiology       Date:  1992-09       Impact factor: 11.105

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