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Test-indication Curves

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  • Joseph Bernstein

Abstract

Test-indication curves (TiCs) are tools for determining whether a test is indicated for a given patient. They apply the threshold approach of Pauker and Kassirer in graphic form. These curves are composed of two parts: the raw curve, which plots posttest probability versus pretest probability (given values for specificity and sensitivity); and the final curve, in which three straight lines are added to the raw curve by the clinician to generate a TIC for a given treatment threshold. In the final curve, the complete range of pretest probability is segregated into three zones, corresponding to the three groups described by Pauker and Kassirer: those patients in whom disease is assumed to be present and who are thus best treated empirically; at the other extreme, those who require neither testing nor treatment; and, finally, those in the middle, for whom the test is indicated, since the decision to treat would be based on the test result. Thus the clinician could consult the TIC and determine with certainty whether the test should be employed for a given patient. It also could be modified with ease for a different patient, with a different set of threshold values. TICs provide a complete, visual inter pretation of a test's diagnostic power, in the context of a given treatment threshold. They foster an intuitive comprehension of Pauker and Kassirer's method, and offer the clinician a facile means to prove that a test is indicated in a given setting. By promoting the use of exactly those tests that are indicated, TICs can help spare the patient the cost, burden, and risk of unnecessary testing, and help spare the physician the cost, burden, and risk of interpreting inconclusive test results. Key words: test-indication curves; treatment thresholds; laboratory tests. (Med Decis Making 1997;17:103-106)

Suggested Citation

  • Joseph Bernstein, 1997. "Test-indication Curves," Medical Decision Making, , vol. 17(1), pages 103-106, February.
    • Handle: RePEc:sae:medema:v:17:y:1997:i:1:p:103-106
    DOI: 10.1177/0272989X9701700112
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    References listed on IDEAS

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    1. Paul Glasziou, 1991. "Threshold Analysis via the Bayes' Nomogram," Medical Decision Making, , vol. 11(1), pages 61-62, February.
    2. Bruce L. Daniel & Thomas M. Daniel, 1993. "Graphic Representation of Numerically Calculated Predictive Values," Medical Decision Making, , vol. 13(4), pages 355-358, December.
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