Literature DB >> 17885293

The ability of four genotypic interpretation systems to predict virological response to ritonavir-boosted protease inhibitors.

Zoe V Fox1, Anna Maria Geretti, Jesper Kjaer, Ulrik Bak Dragsted, Andrew N Phillips, Jan Gerstoft, Schlomo Staszewski, Bonaventura Clotet, Viktor von Wyl, Jens D Lundgren.   

Abstract

BACKGROUND: : Limited information exists on the prognostic value of genotypic interpretation systems (GISs) for ritonavir-boosted protease inhibitors (PI/rs). We compared PI/r resistance levels ascribed by four GIS and examined their abilities to predict HIV-RNA reductions after starting a PI/r-based regimen (baseline).
METHODS: : Data on viraemic (HIV-RNA > 500 copies/ml) patients starting a PI/r with a baseline resistance test were combined from an observational cohort study (EuroSIDA) and three randomized trials (MaxCmin1; MaxCmin2 and COLATE). The GIS surveyed were ANRS, DMC, REGA and Stanford. Factors associated with HIV-RNA change were identified through censored regression analysis.
RESULTS: : We included 744 patients, of whom 67% were PI experienced. At baseline 12-28% (depending on the GIS) patients had a virus with predicted resistance/intermediate resistance to the PI/r initiated. Concordance between GISs on ascribed PI/r resistance levels was moderate: kappa values ranged from 0.01 to 1.00, with the lowest kappas seen for amprenavir. The median (interquartile range) baseline HIV-RNA was 4.4 (3.5-5.1) log10 and was reduced by 2.2 (2.1-2.3) log10 12 (9-13) weeks after baseline. GIS consistently showed greater HIV-RNA reductions as the ascribed level of sensitivity to the PI/r increased. Conversely, the number of other active drugs in the rest of the regimen, according to each GIS did not predict HIV-RNA reductions consistently.
CONCLUSION: : Despite large variations in how GIS classify HIV susceptibility to PI/r, all GIS predicted HIV-RNA reductions of a similar magnitude. The ascribed level of susceptibility to other drugs in the regimen did not predict HIV-RNA decline.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17885293     DOI: 10.1097/QAD.0b013e32825a69e4

Source DB:  PubMed          Journal:  AIDS        ISSN: 0269-9370            Impact factor:   4.177


  9 in total

1.  Predicting tipranavir and darunavir resistance using genotypic, phenotypic, and virtual phenotypic resistance patterns: an independent cohort analysis of clinical isolates highly resistant to all other protease inhibitors.

Authors:  Annie Talbot; Philip Grant; Jonathan Taylor; Jean-Guy Baril; Tommy Fulisma Liu; Hugues Charest; Bluma Brenner; Michel Roger; Robert Shafer; Régis Cantin; Andrew Zolopa
Journal:  Antimicrob Agents Chemother       Date:  2010-04-05       Impact factor: 5.191

2.  Virologic response to lopinavir-ritonavir-based antiretroviral regimens in a multicenter international clinical cohort: comparison of genotypic interpretation scores.

Authors:  Philip Grant; Eric C Wong; Richard Rode; Robert Shafer; Andrea De Luca; Jeffrey Nadler; Trevor Hawkins; Calvin Cohen; Robert Harrington; Dale Kempf; Andrew Zolopa
Journal:  Antimicrob Agents Chemother       Date:  2008-08-18       Impact factor: 5.191

3.  Genotypic resistance profiles associated with virological failure to darunavir-containing regimens: a cross-sectional analysis.

Authors:  G Sterrantino; M Zaccarelli; G Colao; F Baldanti; S Di Giambenedetto; T Carli; F Maggiolo; M Zazzi
Journal:  Infection       Date:  2012-01-12       Impact factor: 3.553

4.  Postpartum viral load rebound in HIV-1-infected women treated with highly active antiretroviral therapy: AIDS Clinical Trials Group Protocol A5150.

Authors:  Beverly E Sha; Camlin Tierney; Susan E Cohn; Xin Sun; Robert W Coombs; Lisa M Frenkel; Spyros A Kalams; Francesca T Aweeka; Barbara Bastow; Arlene Bardeguez; Anne Kmack; Alice Stek
Journal:  HIV Clin Trials       Date:  2011 Jan-Feb

5.  Comparison of HIV-1 genotypic resistance test interpretation systems in predicting virological outcomes over time.

Authors:  Dineke Frentz; Charles A B Boucher; Matthias Assel; Andrea De Luca; Massimiliano Fabbiani; Francesca Incardona; Pieter Libin; Nino Manca; Viktor Müller; Breanndán O Nualláin; Roger Paredes; Mattia Prosperi; Eugenia Quiros-Roldan; Lidia Ruiz; Peter M A Sloot; Carlo Torti; Anne-Mieke Vandamme; Kristel Van Laethem; Maurizio Zazzi; David A M C van de Vijver
Journal:  PLoS One       Date:  2010-07-09       Impact factor: 3.240

6.  Predictive value of HIV-1 genotypic resistance test interpretation algorithms.

Authors:  Soo-Yon Rhee; W Jeffrey Fessel; Tommy F Liu; Natalia M Marlowe; Charles M Rowland; Richard A Rode; Anne-Mieke Vandamme; Kristel Van Laethem; Françoise Brun-Vezinet; Vincent Calvez; Jonathan Taylor; Leo Hurley; Michael Horberg; Robert W Shafer
Journal:  J Infect Dis       Date:  2009-08-01       Impact factor: 5.226

7.  Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes.

Authors:  Soo-Yon Rhee; Jose Luis Blanco; Tommy F Liu; Iñaki Pere; Rolf Kaiser; Maurizio Zazzi; Francesca Incardona; William Towner; Josep Maria Gatell; Andrea De Luca; W Jeffrey Fessel; Robert W Shafer
Journal:  AIDS Res Ther       Date:  2012-05-03       Impact factor: 2.250

8.  TREAT Asia Quality Assessment Scheme (TAQAS) to standardize the outcome of HIV genotypic resistance testing in a group of Asian laboratories.

Authors:  Sally Land; Philip Cunningham; Jialun Zhou; Kevin Frost; David Katzenstein; Rami Kantor; Yi-Ming Arthur Chen; Shinichi Oka; Allison DeLong; David Sayer; Jeffery Smith; Elizabeth M Dax; Matthew Law
Journal:  J Virol Methods       Date:  2009-03-26       Impact factor: 2.623

9.  Clinical evaluation of Rega 8: an updated genotypic interpretation system that significantly predicts HIV-therapy response.

Authors:  Jurgen Vercauteren; Gertjan Beheydt; Mattia Prosperi; Pieter Libin; Stijn Imbrechts; Ricardo Camacho; Bonaventura Clotet; Andrea De Luca; Zehava Grossman; Rolf Kaiser; Anders Sönnerborg; Carlo Torti; Eric Van Wijngaerden; Jean-Claude Schmit; Maurizio Zazzi; Anna-Maria Geretti; Anne-Mieke Vandamme; Kristel Van Laethem
Journal:  PLoS One       Date:  2013-04-17       Impact factor: 3.240

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.