A perspective on standardizing the predictive power of noninvasive cardiovascular tests by likelihood ratio computation: 2. Clinical applications

Authors
Citation
Am. Weissler, A perspective on standardizing the predictive power of noninvasive cardiovascular tests by likelihood ratio computation: 2. Clinical applications, MAYO CLIN P, 74(11), 1999, pp. 1072-1087
Citations number
54
Categorie Soggetti
General & Internal Medicine","Medical Research General Topics
Journal title
MAYO CLINIC PROCEEDINGS
ISSN journal
00256196 → ACNP
Volume
74
Issue
11
Year of publication
1999
Pages
1072 - 1087
Database
ISI
SICI code
0025-6196(199911)74:11<1072:APOSTP>2.0.ZU;2-I
Abstract
Likelihood ratio measures may be used as a standard far expressing the pred ictive power of noninvasive cardiovascular tests, calculated from sensitivi ty and specificity measures or as ratios of the predictive value odds to pr etest odds for positive and negative test results. The positive likelihood ratio, (+)LR, expresses the power of a positive test result to augment an e stimate of disease probability independent of the pretest prevalence of dis ease in a given population; the negative likelihood ratio, (-)LR, expresses the power of a negative test result to augment an estimate of the probabil ity of no disease independent of the pretest prevalence of no disease in th e same population. The likelihood ratio principle is applicable to the eval uation of the predictive poser of single or combined test results reported for either dichotomous or continuous end points. This part of the perspecti ve exemplifies application of the likelihood ratio principle in a wide vari ety of testing conditions for coronary artery disease followed by a discuss ion of the limitations of likelihood ratio computation in test poser evalua tion. Likelihood ratios provide a more concise and unambiguous standard for calibrating the predictive power of single and combined noninvasive cardio vascular test results than are provided by measures of sensitivity, specifi city, and predictive value.