The indication area of a diagnostic test. Part I- discounting gain and loss in diagnostic certainty

L.J.A. Stalpers, P.J. Nelemans, S.M.E. Geurts, E. Jansen, P. de Boer, A.L.M. Verbeek

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Objectives: Test performance is conventionally expressed by gain in diagnostic certainty. We propose net diagnostic gain and indication area as more appropriate measures of test performance; then, the loss in certainty due to misclassification and the information of "no test" would be performed are taken into account.

Study Design and Setting: A decision analytical model was developed in which two alternative strategies were compared: testing and no testing. Correct diagnostic test results received a positive value; undesired test results received a negative value. Within the "no test" scenario, it was assumed that physicians are more prone to treat as the probability of disease is higher.

Results: Discounting gain and loss in diagnostic certainty results in a concave function of the prior. The indication area is the range of priors with a net diagnostic gain; testing is deleterious beyond this range. The net diagnostic gain reaches a maximum at a specific prior. A freely available Web site-based calculator was developed for easy calculation of the indication area and the maximum diagnostic gain for each combination of sensitivity and specificity.

Conclusion: Medical testing is not indicated when the prior disease probabilities are low (as to screening for a condition) or high (for diagnostic confirmation). Published by Elsevier Inc.

Original languageEnglish
Pages (from-to)1120-1128
Number of pages9
JournalJournal of Clinical Epidemiology
Volume68
Issue number10
DOIs
Publication statusPublished - Oct 2015

Keywords

  • Sensitivity
  • Specificity
  • Prevalence
  • Indication area
  • Maximum diagnostic gain
  • Diagnostic test
  • CLINICAL DECISION-MAKING
  • HOME PREGNANCY TESTS
  • OVER-THE-COUNTER
  • TEST ACCURACY
  • LYMPH-NODES
  • SENSITIVITY
  • PREVALENCE
  • CANCER
  • SPECIFICITY
  • PERFORMANCE

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