Related Experiment Video
Updated: May 21, 2026
An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
Published on: March 30, 2014
Predicting a single HIV drug resistance measure from three international interpretation gold standards
1Department of Telehealth, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, 719 Umbilo Road, Umbilo, Durban, South Africa. singhy@ukzn.ac.za
Objective:
To investigate the possibility of combining the interpretation of three gold standard interpretation algorithms using weighted heuristics in order to produce a single resistance measure.
Methods:
The 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.
Results:
The 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%.
Conclusion:
From the result obtained it is evident that combining the gold standard interpretation algorithms may increase the predictive ability of the individual interpretation algorithms.
