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What White Blood Cell Count Should Prompt Antibiotic Treatment in a Febrile Child? Tutorial on the Importance of Disease Likelihood to the Interpretation of Diagnostic Tests

Author

Listed:
  • Michael A. Kohn

    (Department of Epidemiology and Biostatistics, University of California, San Francisco)

  • Thomas B. Newman

    (Department of Epidemiology and Biostatistics, University of California, San Francisco)

Abstract

Most diagnostic tests are not dichotomous (negative or positive) but, rather, have a range of possible results (very negative to very positive). If the pretest probability of disease is high, the test result that prompts treatment should be any value that is even mildly positive. If the pretest probability of disease is low, the test result needed to justify treatment should be very positive. Simple decision rules that fix the cutpoint separating positive from negative test results do not take into account the individual patient’s pretest probability of disease. Allowing the cutpoint to change with the pretest probability of disease increases the value of the test. This is primarily an issue when the pretest probability of disease varies widely between patients and depends on characteristics that are not measured by the test. It remains an issue for decision rules based on multiple test results if these rules fail to account for important determinants of patient-specific risk. This tutorial demonstrates how the value of a diagnostic test depends on the ability to vary the cutpoint, using as an example the white blood cell count in febrile children at risk for bacteremia.

Suggested Citation

  • Michael A. Kohn & Thomas B. Newman, 2001. "What White Blood Cell Count Should Prompt Antibiotic Treatment in a Febrile Child? Tutorial on the Importance of Disease Likelihood to the Interpretation of Diagnostic Tests," Medical Decision Making, , vol. 21(6), pages 479-489, December.
  • Handle: RePEc:sae:medema:v:21:y:2001:i:6:p:479-489
    DOI: 10.1177/0272989X0102100606
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    Cited by:

    1. Bardey, David & De Donder , Philippe & Zaporozhets , Vera, 2024. "The Health Technology Assessment Approach of The Economic Value of Diagnostic Test: A Literature Review," Documentos CEDE 21041, Universidad de los Andes, Facultad de Economía, CEDE.
    2. Alexander J. Sutton & Nicola J. Cooper & Steve Goodacre & Matthew Stevenson, 2008. "Integration of Meta-analysis and Economic Decision Modeling for Evaluating Diagnostic Tests," Medical Decision Making, , vol. 28(5), pages 650-667, September.

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