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Comparing and Optimizing Diagnostic Tests

Author

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  • Eugene Somoza
  • Douglas Mossman

Abstract

An ideal method for assessing performance of non-binary diagnostic tests would specify each test's optimal operating point and would tell a diagnostician which of many tests was the best one to use in a particular clinical situation. This article shows how information theory and receiver operating characteristic (ROC) analysis can be combined to evaluate and compare diagnostic tests at their optimum cutoffs once disease prevalence and test properties are specified. Though it is not appropriate for all clinical situations, the method can be used for most diagnostic tests whenever information is desired for its own sake or when reducing uncertainty is the goal of testing. The method also is appropriate in those situations where benefits and costs cannot be specified precisely enough to permit test optimization based on a balancing of anticipated goods and evils. Key words: non-binary diagnostic tests; information theory; receiver operating characteristic curves. (Med Decis Making 1992;12:179- 188)

Suggested Citation

  • Eugene Somoza & Douglas Mossman, 1992. "Comparing and Optimizing Diagnostic Tests," Medical Decision Making, , vol. 12(3), pages 179-188, August.
    • Handle: RePEc:sae:medema:v:12:y:1992:i:3:p:179-188
    DOI: 10.1177/0272989X9201200303
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    Cited by:

    1. Jérôme Jund & Muriel Rabilloud & Martine Wallon & René Ecochard, 2005. "Methods to Estimate the Optimal Threshold for Normally or Log-Normally Distributed Biological Tests," Medical Decision Making, , vol. 25(4), pages 406-415, July.
    2. Martin MacDowell & Eugene Somoza & Kenneth Rothe & Richard Fry & Kim Brady & Albert Bocklet, 2001. "Understanding Birthing Mode Decision Making Using Artificial Neural Networks," Medical Decision Making, , vol. 21(6), pages 433-443, December.

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