Critical analysis of the application of bayes' theorem to sequential testing in the noninvasive diagnosis of coronary artery disease

The utility of Bayes' theorem in the noninvasive diagnosis of coronary artery disease was analyzed in 147 patients who underwent electrocardiographic stress testing, thallium-201 perfusion imaging and coronary angiography, finding that it is useful clinically despite some evidence of test dependence.

Abstract

The utility of Bayes' theorem in the noninvasive diagnosis of coronary artery disease (CAD) was analyzed in 147 patients who underwent electrocardiographic stress testing, thallium-201 perfusion imaging and coronary angiography. Eighty-nine patients had typical anginal chest discomfort and 58 had atypical chest pain. Sensitivity and specificity of the tests and prevalence of CAD at each level of testing were tabulated and compared with the results generated from Bayes' theorem. The sensitivity of electrocardiographic stress was higher in patients with multivessel CAD than in patients with 1-vessel CAD. Sensitivity, but not specificity, of each test was dependent, in part, on the result of the other test. However, the probabilities calculated from Bayes' theorem when used for sequential testing are remarkably close to the tabulated data. Thus, Bayes' theorem is useful clinically despite some evidence of test dependence. Sequential test analysis by Bayes' theorem is most useful in establishing or ruling out a diagnosis when the pretest prevalence is approximately 50% and when the 2 tests are concordant.