Improved darunavir genotypic mutation score predicting treatment response for patients infected with HIRaben-1 subtype B and non-subtype B receiving a salvage regimen

A. De Luca, Philippe Flandre, D. Dunn, Maurizio Zazzi, Annemarie M J Wensing, Maria Mercedes Santoro, Huldrych F. Günthard, Linda Wittkop, T. Kordossis, Federico García, Antonella Castagna, Alessandro Cozzi-Lepri, Duncan Churchill, Stéphane De Wit, Norbert Brockmeyer, Arkaitz Imaz, Cristina Mussini, Niels Obel, Carlo Federico Perno, Bernardino RocaPeter Reiss, E. Schülter, C. Torti, Ard Van Sighem, Robert Zangerle, Diane Descamps, Amanda Mocroft, O. Kirk, Caroline Sabin, Stéphane de Wit, J. Casabona, Jose Miro, Giota Touloumi, Myriam Garrido, Ramon Teira, Ferdinand Wit, Josiane Warszawski, Laurence Meyer, Murielle Mary Krause, Murielle Mary Krause, Jade Ghosn, Catherine Leport, Maria Prins, Heiner C. Bucher, Diana Gibb, Gerd Fätkenheuer, Julia Del Amo, Claire Thorne, Christoph Stephan, Antoni Noguera-Julian, Barbara Bartmeyer, Barbara Bartmeyer, N. Chkhartishvili, Antoni Noguera-Julian, Andrea Antinori, A. D'Arminio Monforte, Luis Prieto, Pablo Rojo Conejo, Antoni Soriano-Arandes, Manuel Battegay, Roger Kouyos, Pat Tookey, Deborah Konopnick, Tessa Goetghebuer, Anders Sönnerborg, David Haerry, Stéphane de Wit, Dominique Costagliola, D. Raben, Genevieve Chene, F. Ceccherini-Silberstein, Huldrych Günthard, Ali Judd, Diana Barger, Christine Schwimmer, Monique Termote, Maria Campbell, Casper M. Frederiksen, Nina Friis-Møller, Jesper Kjaer, Rikke Salbøl Brandt, Juan Berenguer, Julia Bohlius, Vincent Bouteloup, Mary Anne Davies, Maria Dorrucci, Matthias Egger, Hansjakob Furrer, M. Guiguet, S. Grabar, Olivier Lambotte, Valériane Leroy, Sara Lodi, Sophie Matheron, Susana Monge, Fumiyo Nakagawa, Roger Paredes, A. N. Phillips, M. Puoti, Michael Schomaker, Colette Smit, Rodolphe Thiebaut, Rodolphe Thiebaut, Marc Van Der Valk, Natasha Wyss, Vincent Aubert, Manuel Battegay, E. Bernasconi, Jurg Boni, C. Burton-Jeangros, A. Calmy, M. Cavassini, G. Dollenmaier, Frederik Engsig, L. Elzi, Jan Fehr, Jacques Fellay, Hansjakob Furrer, C. Fux, Meri Gorgievski, H. Günthard, D. Haerry, Barbara Hasse, H. H. Hirsch, Matthias Hoffmann, Irene Hösli, C. Kahlert, L. Kaiser, Olivia Keiser, T. Klimkait, Roger Kouyos, H. Kovari, B. Ledergerber, G. Martinetti, B. Martinez de Tejada, Karin J. Metzner, N. Müller, D. Nadal, D. Nicca, Giuseppe Pantaleo, Andri Rauch, Stephan Regenass, Martin Rickenbach, C. Rudin, F. Schöni-Affolter, P. Schmid, J. Schüpbach, R. Speck, Philip E. Tarr, A. Telenti, A. Trkola, P. Vernazza, R. Weber, S. Yerly

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: The objective of this studywas to improve the prediction of the impact of HIV-1 protease mutations in different viral subtypes on virological response to darunavir. Methods: Darunavir-containing treatment change episodes (TCEs) in patients previously failing PIs were selected from large European databases. HIV-1 subtype B-infected patients were used as the derivation dataset and HIV- 1 non-B-infected patients were used as the validation dataset. The adjusted association of each mutation with week 8 HIV RNA change from baseline was analysed by linear regression. A prediction model was derived based on best subset least squares estimation with mutational weights corresponding to regression coefficients. Virological outcome prediction accuracy was compared with that from existing genotypic resistance interpretation systems (GISs) (ANRS 2013, Rega 9.1.0 and HIVdb 7.0). Results: TCEs were selected from 681 subtype B-infected and 199 non-B-infected adults. Accompanying drugs were NRTIs in 87%, NNRTIs in 27%and raltegravir ormaraviroc or enfuvirtide in 53%. The predictionmodel included weighted protease mutations, HIV RNA, CD4 and activity of accompanying drugs. The model's association with week 8 HIV RNA change in the subtype B (derivation) set was R2=0.47 [average squared error (ASE)=0.67, P>10-6]; in the non-B (validation) set, ASE was 0.91. Accuracy investigated by means of area under the receiver operating characteristic curves with a binary response (above the threshold value of HIV RNA reduction) showed that our finalmodel outperformed models with existing interpretation systems in both training and validation sets. Conclusions: A model with a new darunavir-weighted mutation score outperformed existing GISs in both B and non-B subtypes in predicting virological response to darunavir.

Original languageEnglish
Article numberdkv465
Pages (from-to)1352-1360
Number of pages9
JournalJournal of Antimicrobial Chemotherapy
Volume71
Issue number5
DOIs
Publication statusPublished - May 1 2016

ASJC Scopus subject areas

  • Pharmacology
  • Pharmacology (medical)
  • Infectious Diseases

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