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Diagnostic Tests Distinguishing Good Tests From Bad and Even Ugly Ones

Published online by Cambridge University Press:  02 January 2015

David Birnbaum ,
Barry M. Farr  and
David E. Shapiro
Barry M. Farr*
Affiliation:
University of Virginia Health System, Charlottesville, Virginia, Harvard School of Public Health, Boston, Massachusetts
David E. Shapiro
Affiliation:
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts
*
University of Virginia Health System, Box 800473, Charlottesville, VA 22908-0473
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Abstract

This article focuses on the selection and interpretation of diagnostic tests, emphasizing the importance of understanding how their mathematical parameters affect the information they provide in various settings. The utility and limitations of sensitivity, specificity, predictive value, and receiver operating characteristic (ROC) curves are discussed using catheter-related bloodstream infections as an example. ROC curves have been used for selecting optimal cutoff values for a positive result and for selecting among several alternative diagnostic tests. For example, 16 different tests have been proposed for diagnosis of catheter-related bloodstream infection; ROC analysis provides an effective way to determine which test offers the best overall performance.

Information

Type
Statistics for Hospital Epidemiology
Information
Infection Control & Hospital Epidemiology , Volume 21 , Issue 4 , April 2000 , pp. 278 - 284
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2000

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