Bayes' theorem was published posthumously by The Reverend Thomas Bayes in 1763.1 This formula, which allows one to calculate predictability "in the doctrine of chance," has been of interest to mathematicians and statisticians ever since that time, although its value has only recently been emphasized in medicine, particularly in laboratory science. Galen and Gambino2 have stressed the importance of the Bayes' equation and have prepared tables for determining the predictive value of any laboratory test.
The predictability of a measurement can be estimated with precision if its sensitivity (true positives/all diseased patients), specificity (true negatives/all subjects without disease), and the prevalence of the disease under question are known. The predictive value of a positive test is the percent of all positive tests that are true positives: it can be shown to equal the product of prevalence and sensitivity divided by a denominator of that same product plus the
Jones RJ. Bayes' Theorem, the Exercise ECG, and Coronary Artery Disease. JAMA. 1979;242(10):1067–1068. doi:10.1001/jama.1979.03300100045024