Predicting a single HIV drug resistance measure from three international interpretation gold standards

ObjectiveTo investigate the possibility of combining the interpretation of three gold standard interpretation algorithms using weighted heuristics in order to produce a single resistance measure.MethodsThe outputs of HIVdb, Rega, ANRS were combined to obtain a single resistance profile using the equally weighted voting algorithm, accuracy based weighing voting algorithm and the Bayesian based weighted voting algorithm techniques.ResultsThe Bayesian based voting combination increased the accuracy of the resistance profile prediction compared to phenotype, from 58% to 69%. The equal weighted voting algorithm and the accuracy based algorithm both increased the prediction accuracy to 60%.ConclusionFrom the result obtained it is evident that combining the gold standard interpretation algorithms may increase the predictive ability of the individual interpretation algorithms.