Prediction of the virological response to etravirine in clinical practice: Comparison of three genotype algorithms

• Published in: Journal of medical virology 2009-04, Vol.81 (4), p.672-677
• Main Authors: Cotte, Laurent, Trabaud, Mary-Anne, Tardy, Jean-Claude, Brochier, Corinne, Gilibert, René-Pierre, Miailhes, Patrick, Trépo, Christian, André, Patrice
• Format: Article
• Language: English
• Subjects: Algorithms; Anti-HIV Agents - pharmacology; Anti-HIV Agents - therapeutic use; Biological and medical sciences; Databases, Genetic; Drug Resistance, Viral - genetics; etravirine; Fundamental and applied biological sciences. Psychology; Genotype; HIV Infections - drug therapy; HIV Infections - virology; HIV Reverse Transcriptase - genetics; HIV-1; HIV-1 - drug effects; HIV-1 - enzymology; HIV-1 - genetics; Human immunodeficiency virus; Human viral diseases; Humans; Infectious diseases; Medical sciences; Microbiology; Miscellaneous; Mutation; NNRTI; Predictive Value of Tests; Pyridazines - pharmacology; Pyridazines - therapeutic use; resistance algorithm; Reverse Transcriptase Inhibitors - pharmacology; Reverse Transcriptase Inhibitors - therapeutic use; Sida; Treatment Outcome; Viral diseases; Virology
• ISSN: 0146-6615; 1096-9071
• DOI: 10.1002/jmv.21461

The current Agence Nationale de Recherche sur le SIDA (ANRS)/International AIDS Society (IAS) algorithm predicts resistance to etravirine for viruses harboring greater-than-or-equal3 mutations from a list of 13 reverse transcriptase (RT) mutations. Two weighted algorithms, best correlated with fold changes to etravirine, have been described recently. A retrospective virological analysis of a major French city HIV sequences database was undertaken to assess the proportion of etravirine resistant viruses according to these three algorithms and the correlations between them. Two thousand six hundred eighty RT sequences were analyzed, including 749 from naive patients and 926 from patients previously treated with non-nucleoside reverse transcriptase inhibitor (NNRTI). Combinations of mutations associated with etravirine resistance according to the three algorithms were found in 0%, 2.3%, and 3.6% of naive patients, and in 2.4%, 20.4%, and 19.3% of patients previously treated with NNRTIs. Concordance between the algorithms was weak (2 x 2 Kendall's tau: 0.787, 0.395, and 0.584). Most of the discordance was due to the differential weights attributed to Y181C/V, L100I, and K101P in the two weighted algorithms. It is concluded that the current ANRS/ IAS algorithm probably underestimates the proportion of viruses partially resistant to etravirine in NNRTI-experienced patients. Improvements in algorithms are needed to take into account the partial resistance associated with some mutation patterns, and should include either additional mutations to the current list and/or differential weights for specific mutations. Surveys of naive patients should be conducted to estimate the risk of primary resistance to etravirine in a minority of cases. J. Med. Virol. 81:672-677, 2009