Sensitivity and specificity define the discriminative power of a diagnostic procedure, whereas predictive values relate to the predictive ability of a test to identify disease or its absence in individuals. Predictive values are greatly influenced by the prevalence of the disease and should not be generalized beyond the studied population.
Likelihood ratios are very helpful statistics used to combine the information of the result of a diagnostic test and knowledge about the diagnostic accuracy of the test in order to update the pre-test probability of a disease in a certain patient. As opposed to predictive values, likelihood ratios are not affected by the disease prevalence and are therefore used to adopt the results from other investigators to your own patient population. A simple tool for revising probabilities according to the likelihood ratio and a test result is the Fagan nomogram. This article describes the basics on predictive values and likelihood ratios and gives simple instructions on how to use the Fagan nomogram.