Super Learner Analysis of Electronic Adherence Data Improves Viral Prediction and May Provide Strategies for Selective HIV RNA Monitoring. - Petersen, Maya L; LeDell, Erin; Schwab, Joshua; Sarovar, Varada; Gross, Robert; Reynolds, Nancy; Haberer, Jessica E; Goggin, Kathy; Golin, Carol; Arnsten, Julia; Rosen, Marc I; Remien, Robert H; et al. (Journal of acquired immune deficiency syndromes (1999), 2015)
Regular HIV RNA testing for all HIV-positive patients on antiretroviral therapy (ART) is expensive and has low yield since most tests are undetectable. Selective testing of those at higher risk of failure may improve efficiency. We investigated whether a novel analysis of adherence data could correctly classify virological failure and potentially inform a selective testing strategy.