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

Andrea De Luca, Philippe Flandre, David Dunn, Maurizio Zazzi, Annemarie Wensing, Maria Mercedes Santoro, Huldrych F. Günthard, Linda Wittkop, Theodoros Kordossis, Federico Garcia, Antonella Castagna, Alessandro Cozzi-Lepri, Duncan Churchill, Stéphane De Wit, Norbert H. Brockmeyer, Arkaitz Imaz, Cristina Mussini, Niels Obel, Carlo Federico Perno, Bernardino RocaPeter Reiss, Eugen Schülter, Carlo Torti, Ard Van Sighem, Robert Zangerle, Diane Descamps, Amanda Mocroft, Ole Kirk, Caroline Sabin, W. Casadi, Jordi Casabona, Jose M. Miró, Giota Touloumi, Myriam Garrido, Ramon Teira, Ferdinand Wit, Josiane Warszawski, Laurence Meyer, François Dabis, Murielle Mary Krause, Jade Ghosn, Catherine Leport, Maria Prins, Heiner Bucher, Diana Gibb, Gerd Fätkenheuer, Julia Del Amo, Claire Thorne, Christoph Stephan, Santiago Pérez-Hoyos, Osamah Hamouda, Barbara Bartmeyer, Nikoloz Chkhartishvili, Antoni Noguera-Julian, Andrea Antinori, Antonella 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, Dorthe Raben, Geneviève Chêne, Francesca 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, Marguerite Guiguet, Sophie Grabar, Olivier Lambotte, Valériane Leroy, Sara Lodi, Sophie Matheron, Susana Monge, Fumiyo Nakagawa, Roger Paredes, Andrew Phillips, Massimo Puoti, Michael Schomaker, Colette Smit, Jonathan Sterne, Rodolphe Thiebaut, Marc Van Der Valk, Natasha Wyss, V. Aubert, M. Battegay, E. Bernasconi, J. Böni, C. Burton-Jeangros, A. Calmy, M. Cavassini, G. Dollenmaier, M. Egger, L. Elzi, J. Fehr, J. Fellay, H. Furrer, C. A. Fux, M. Gorgievski, H. Günthard, D. Haerry, B. Hasse, H. H. Hirsch, M. Hoffmann, I. Hösli, C. Kahlert, L. Kaiser, O. Keiser, T. Klimkait, R. Kouyos, H. Kovari, B. Ledergerber, G. Martinetti, B. Martinez De Tejada, K. Metzner, N. Müller, D. Nadal, D. Nicca, G. Pantaleo, A. Rauch, S. Regenass, M. Rickenbach, C. Rudin, F. Schöni-Affolter, P. Schmid, J. Schüpbach, R. Speck, P. Tarr, A. Telenti, A. Trkola, P. Vernazza, R. Weber, S. Yerly

Risultato della ricerca: Contributo in rivistaArticolo in rivista

3 Citazioni (Scopus)

Abstract

OBJECTIVES: The objective of this study was 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 or maraviroc or enfuvirtide in 53%. The prediction model 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 R(2) = 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 final model 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.
Lingua originaleEnglish
pagine (da-a)1352-60-1360
RivistaJournal of Antimicrobial Chemotherapy
Volume71
DOI
Stato di pubblicazionePubblicato - 2016

Keywords

  • genotypic
  • hiv-1

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