Predicting the response to combination antiretroviral therapy: retrospective validation of geno2pheno-theo on a large clinical database

Abstract

Background. Expert-based genotypic interpretation systems are standard methods for guiding treatment selection for patients infected with human immunodeficiency virus type 1.Wepreviously introduced the software pipeline geno2pheno-THEO (g2p-THEO), which on the basis of viral sequence predicts the response to treatment with a combination of antiretroviral compounds by applying methods from statistical learning and the estimated potential of the virus to escape from drug pressure. Methods. We retrospectively validated the statistical model used by g2p-THEO in-7600 independent treatment-sequence pairs extracted from the EuResist integrated database, ranging from 1990 to 2007. Results were compared with the 3 most widely used expert-based interpretation systems: Stanford HIVdb, ANRS, and Rega. Results. The difference in receiver operating characteristic curves between g2p-THEO and expert-based approaches was significant (P