Beyond the Usual Prediction Accuracy Metrics: Reporting Results for Clinical Decision Making
Editorials21 August 2012Beyond the Usual Prediction Accuracy Metrics: Reporting Results for Clinical Decision MakingA. Russell Localio, PhD and Steven Goodman, MD, MHS, PhDA. Russell Localio, PhDFrom University of Pennsylvania, Philadelphia, PA 19104, and Stanford University School of Medicine, Stanford, CA 94305. and Steven Goodman, MD, MHS, PhDFrom University of Pennsylvania, Philadelphia, PA 19104, and Stanford University School of Medicine, Stanford, CA 94305.Author, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-157-4-201208210-00014 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail How well an algorithm or a test predicts or diagnoses disease is not an adequate determination of its clinical usefulness. The relevant question is, are people better or worse off if the test is used as part of clinical care? Stock measures of prediction accuracy, such as sensitivity, specificity, area under the receiver-operating characteristic (ROC) curve, Brier scores, or predicted-versus-observed tests for model calibration, do not measure patient outcomes after a test. Derived measures, such as likelihood ratios, or traditional association measures, such as odds ratios, also do not serve that purpose. Fortunately, a large and growing body of analytic ...References1. Steyerberg EW, Vickers AJ, Cook NR, Gerds T, Gonen M, Obuchowski N, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010;21:128-38. [PMID: 20010215] CrossrefMedlineGoogle Scholar2. Raji OY, Duffy SW, Agbaje OF, Baker SG, Christiani DC, Cassidy A, et al. Predictive accuracy of the Liverpool Lung Project risk model for stratifying patients for computed tomography screening for lung cancer. A case-control and cohort validation study. Ann Intern Med. 2012;157:242-50. 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[PMID: 17099194] CrossrefMedlineGoogle Scholar8. Helfand M, Berg A, Flum D, Gabriel S, Normand SL, eds; PCORI Methodology Committee. Draft Methodology Report: Our Questions, Our Decisions: Standards for Patient-Centered Outcomes Research. Patient-Centered Outcomes Research Institute; 23 July 2012. Google Scholar9. Pepe MS, Janes H, Longton G, Leisenring W, Newcomb P. Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker. Am J Epidemiol. 2004;159:882-90. [PMID: 15105181] CrossrefMedlineGoogle Scholar10. Software for Decision Curve Analysis. Memorial Sloan-Kettering Cancer Center; 2012. Accessed at www.mskcc.org/research/epidemiology-biostatistics/health-outcomes/collaborative/decision-curve-analysis on 16 July 2012. Google Scholar11. Vickers AJ, Cronin AM, Elkin EB, Gonen M. Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers. BMC Med Inform Decis Mak. 2008;8:53. [PMID: 19036144] CrossrefMedlineGoogle Scholar12. Baker SG. Putting risk prediction in perspective: relative utility curves. J Natl Cancer Inst. 2009;101:1538-42. [PMID: 19843888] CrossrefMedlineGoogle Scholar13. Pepe M, Longton G, Janes H. Estimation and comparison of receiver operating characteristic curves. Stata J. 2009;9:1. [PMID: 20161343] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: From University of Pennsylvania, Philadelphia, PA 19104, and Stanford University School of Medicine, Stanford, CA 94305.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-1744.Corresponding Author: A. Russell Localio, PhD, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, 635 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104; e-mail, [email protected].Current Author Addresses: Dr. Localio: Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, 635 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104.Dr. Goodman: Stanford University, 259 Campus Drive, HRP/Redwood Building, Stanford, CA 94305. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoPredictive Accuracy of the Liverpool Lung Project Risk Model for Stratifying Patients for Computed Tomography Screening for Lung Cancer Olaide Y. Raji , Stephen W. Duffy , Olorunshola F. Agbaje , Stuart G. Baker , David C. Christiani , Adrian Cassidy , and John K. 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Vickers, PhD and Margaret Pepe, PhDPrediction of 1-Year Mortality in Patients With Acute Coronary Syndromes Undergoing Percutaneous Coronary InterventionComparative Effectiveness Research in OncologyIntroducing, OncoTarget 21 August 2012Volume 157, Issue 4Page: 294-295KeywordsCancer screeningClinical epidemiologyComputed axial tomographyDecision analysisDecision makingLung and intrathoracic tumorsLungsSpecificity ePublished: 21 August 2012 Issue Published: 21 August 2012 Copyright & PermissionsCopyright © 2012 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
