ROC methodology within a monitoring framework

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Abstract
Receiver operating characteristic (ROC) methodology is widely used to evaluate and compare diagnostic tests. Generally, each diagnostic test is applied once to each subject in a population and the results, reported on a continuous scale, are used to construct the ROC curve. We extend the standard method to accommodate a framework in which the diagnostic test is repeated over time to monitor for occurrence of an event. Unlike the usual situation in which event status is static, the problem we address involves event status that is not constant over the monitoring period. Subjects generally are classified as non‐events, or controls, until they experience events that convert them to cases. Viewing the data as incomplete discrete failure time data with time‐varying covariates, potentially useful diagnostic markers can be related appropriately in time with the true condition and varying amounts of information per individual can be taken into account. The ROC curve provides an assessment of the performance of the test in combination with the schedule of testing. Within this framework, a computational simplification is introduced to calculate variances and covariances for the areas under the ROC curves. Periodic monitoring for reperfusion following thrombolytic treatment for acute myocardial infarction provides a detailed example, whereby the lengths of the testing interval combined with different diagnostic markers are compared. Copyright © 2003 John Wiley & Sons, Ltd.