Literature DB >> 24594418

Comparative statistical properties of expected utility and area under the ROC curve for laboratory studies of observer performance in screening mammography.

Craig K Abbey1, Brandon D Gallas2, John M Boone3, Loren T Niklason4, Lubomir M Hadjiiski5, Berkman Sahiner2, Frank W Samuelson2.   

Abstract

RATIONALE AND
OBJECTIVES: Our objective is to determine whether expected utility (EU) and the area under the receiver operator characteristic (AUC) are consistent with one another as endpoints of observer performance studies in mammography. These two measures characterize receiver operator characteristic performance somewhat differently. We compare these two study endpoints at the level of individual reader effects, statistical inference, and components of variance across readers and cases.
MATERIALS AND METHODS: We reanalyze three previously published laboratory observer performance studies that investigate various x-ray breast imaging modalities using EU and AUC. The EU measure is based on recent estimates of relative utility for screening mammography.
RESULTS: The AUC and EU measures are correlated across readers for individual modalities (r = 0.93) and differences in modalities (r = 0.94 to 0.98). Statistical inference for modality effects based on multi-reader multi-case analysis is very similar, with significant results (P < .05) in exactly the same conditions. Power analyses show mixed results across studies, with a small increase in power on average for EU that corresponds to approximately a 7% reduction in the number of readers. Despite a large number of crossing receiver operator characteristic curves (59% of readers), modality effects only rarely have opposite signs for EU and AUC (6%).
CONCLUSIONS: We do not find any evidence of systematic differences between EU and AUC in screening mammography observer studies. Thus, when utility approaches are viable (i.e., an appropriate value of relative utility exists), practical effects such as statistical efficiency may be used to choose study endpoints.
Copyright © 2014 AUR. All rights reserved.

Entities:  

Keywords:  Expected utility; area under the ROC curve; observer performance studies

Mesh:

Year:  2014        PMID: 24594418      PMCID: PMC3952000          DOI: 10.1016/j.acra.2013.12.011

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


  33 in total

Review 1.  ROC analysis in medical imaging: a tutorial review of the literature.

Authors:  Charles E Metz
Journal:  Radiol Phys Technol       Date:  2007-10-27

2.  Evaluating imaging and computer-aided detection and diagnosis devices at the FDA.

Authors:  Brandon D Gallas; Heang-Ping Chan; Carl J D'Orsi; Lori E Dodd; Maryellen L Giger; David Gur; Elizabeth A Krupinski; Charles E Metz; Kyle J Myers; Nancy A Obuchowski; Berkman Sahiner; Alicia Y Toledano; Margarita L Zuley
Journal:  Acad Radiol       Date:  2012-02-03       Impact factor: 3.173

3.  Comparison of soft-copy and hard-copy reading for full-field digital mammography.

Authors:  Robert M Nishikawa; Suddhasatta Acharyya; Constantine Gatsonis; Etta D Pisano; Elodia B Cole; Helga S Marques; Carl J D'Orsi; Dione M Farria; Kalpana M Kanal; Mary C Mahoney; Murray Rebner; Melinda J Staiger
Journal:  Radiology       Date:  2009-04       Impact factor: 11.105

4.  Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis.

Authors:  Stephen L Hillis; Kevin S Berbaum; Charles E Metz
Journal:  Acad Radiol       Date:  2008-05       Impact factor: 3.173

5.  Experimental design and data analysis in receiver operating characteristic studies: lessons learned from reports in radiology from 1997 to 2006.

Authors:  Junji Shiraishi; Lorenzo L Pesce; Charles E Metz; Kunio Doi
Journal:  Radiology       Date:  2009-10-28       Impact factor: 11.105

6.  Assessing radiologist performance using combined digital mammography and breast tomosynthesis compared with digital mammography alone: results of a multicenter, multireader trial.

Authors:  Elizabeth A Rafferty; Jeong Mi Park; Liane E Philpotts; Steven P Poplack; Jules H Sumkin; Elkan F Halpern; Loren T Niklason
Journal:  Radiology       Date:  2012-11-20       Impact factor: 11.105

7.  Estimating the relative utility of screening mammography.

Authors:  Craig K Abbey; Miguel P Eckstein; John M Boone
Journal:  Med Decis Making       Date:  2013-01-07       Impact factor: 2.583

8.  Statistical power considerations for a utility endpoint in observer performance studies.

Authors:  Craig K Abbey; Frank W Samuelson; Brandon D Gallas
Journal:  Acad Radiol       Date:  2013-04-20       Impact factor: 3.173

9.  Power estimation for multireader ROC methods an updated and unified approach.

Authors:  Stephen L Hillis; Nancy A Obuchowski; Kevin S Berbaum
Journal:  Acad Radiol       Date:  2011-02       Impact factor: 3.173

10.  An equivalent relative utility metric for evaluating screening mammography.

Authors:  Craig K Abbey; Miguel P Eckstein; John M Boone
Journal:  Med Decis Making       Date:  2009-08-25       Impact factor: 2.583

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  2 in total

Review 1.  The Reproducibility of Changes in Diagnostic Figures of Merit Across Laboratory and Clinical Imaging Reader Studies.

Authors:  Frank W Samuelson; Craig K Abbey
Journal:  Acad Radiol       Date:  2017-06-27       Impact factor: 3.173

2.  A Utility/Cost Analysis of Breast Cancer Risk Prediction Algorithms.

Authors:  Craig K Abbey; Yirong Wu; Elizabeth S Burnside; Adam Wunderlich; Frank W Samuelson; John M Boone
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2016-03-24
  2 in total

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