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Clinical Chemistry 50: 1118-1125, 2004. First published May 13, 2004; 10.1373/clinchem.2004.031823
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(Clinical Chemistry. 2004;50:1118-1125.)
© 2004 American Association for Clinical Chemistry, Inc.


Reviews

ROC Curves in Clinical Chemistry: Uses, Misuses, and Possible Solutions

Nancy A. Obuchowski1,a, Michael L. Lieber1 and Frank H. Wians, Jr.2

1 Departments of Biostatistics and Epidemiology and the Division of Radiology-Wb4, The Cleveland Clinic Foundation, Cleveland, OH. 2 Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX.

aAddress correspondence to this author at: Department of Biostatistics, The Cleveland Clinic Foundation, 9500 Euclid Ave., Cleveland, OH 44195-5196. Fax 216-444-3466; e-mail nobuchow{at}bio.ri.ccf.org.

Background: ROC curves have become the standard for describing and comparing the accuracy of diagnostic tests. Not surprisingly, ROC curves are used often by clinical chemists. Our aims were to observe how the accuracy of clinical laboratory diagnostic tests is assessed, compared, and reported in the literature; to identify common problems with the use of ROC curves; and to offer some possible solutions.

Methods: We reviewed every original work using ROC curves and published in Clinical Chemistry in 2001 or 2002. For each article we recorded phase of the research, prospective or retrospective design, sample size, presence/absence of confidence intervals (CIs), nature of the statistical analysis, and major analysis problems.

Results: Of 58 articles, 31% were phase I (exploratory), 50% were phase II (challenge), and 19% were phase III (advanced) studies. The studies increased in sample size from phase I to III and showed a progression in the use of prospective designs. Most phase I studies were powered to assess diagnostic tests with ROC areas ≥0.70. Thirty-eight percent of studies failed to include CIs for diagnostic test accuracy or the CIs were constructed inappropriately. Thirty-three percent of studies provided insufficient analysis for comparing diagnostic tests. Other problems included dichotomization of the gold standard scale and inappropriate analysis of the equivalence of two diagnostic tests.

Conclusion: We identify available software and make some suggestions for sample size determination, testing for equivalence in diagnostic accuracy, and alternatives to a dichotomous classification of a continuous-scale gold standard. More methodologic research is needed in areas specific to clinical chemistry.




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