Literature DB >> 15456091

Predictive value of HIV-1 protease genotype and virtual phenotype on the virological response to lopinavir/ritonavir-containing salvage regimens.

Mona R Loutfy1, Janet M Raboud, Sharon L Walmsley, Refik Saskin, Julio S Montaner, Robert S Hogg, Courtney A Thompson, P Richard Harrigan.   

Abstract

The predictive values of HIV-1 protease genotype and virtual phenotype (vPhenotype) results on the HIV-1 RNA response to lopinavir/ritonavir (LPV/r)-containing salvage regimens were assessed. Data were evaluated from patients with antiretroviral (ARV) resistance testing prior to initiating an LPV/r-containing salvage ARV regimen, from two independent cohorts from Toronto, Ontario and British Columbia, Canada. Multivariate logistic regression models controlling for previous non-nucleoside reverse transcriptase inhibitor use, baseline viral load and AIDS-defining illness were used to assess the impact of different protease genotypic mutations (individual and in combination) and lopinavir vPhenotyping on virological suppression to <50 copies/ml by 12 months. We confirmed that the 11-mutation 'lopinavir mutation score' (LMS) was significantly inversely associated with the probability of virological suppression within 12 months [odds ratio (OR)=0.91; P=0.02]. The only single specific protease mutation found to predict virological response in multivariate analyses was 461 (OR=0.55; P=0.02). The most predictive three-mutation combination was 10F/I/R/V, 461, 82A/F/T (OR=0.18; P=0.0004). We confirmed that a 10-fold increase of lopinavir IC50 is an appropriate clinical cut-off for lopinavir vPhenotype. In univariate analyses, a cut-off of the LMS as low as 3 was significantly associated with a lack of virological suppression (P=0.04). This finding, which is in contrast to those of other studies, may be due to the high degree of ARV experience of our population and lack of active agents in the salvage regimen. Selecting the 11 specific mutations to make the LMS is potentially arbitrary; we determined that when different combinations of 11 protease mutations were chosen randomly from a set of 30, similar associations with virological response were found, probably due to the co-linearity of these mutations.

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Year:  2004        PMID: 15456091

Source DB:  PubMed          Journal:  Antivir Ther        ISSN: 1359-6535


  7 in total

1.  HIV-1 Protease and reverse-transcriptase mutations: correlations with antiretroviral therapy in subtype B isolates and implications for drug-resistance surveillance.

Authors:  Soo-Yon Rhee; W Jeffrey Fessel; Andrew R Zolopa; Leo Hurley; Tommy Liu; Jonathan Taylor; Dong Phuong Nguyen; Sally Slome; Daniel Klein; Michael Horberg; Jason Flamm; Stephen Follansbee; Jonathan M Schapiro; Robert W Shafer
Journal:  J Infect Dis       Date:  2005-07-05       Impact factor: 5.226

Review 2.  Lopinavir/ritonavir: a review of its use in the management of HIV infection.

Authors:  Vicki Oldfield; Greg L Plosker
Journal:  Drugs       Date:  2006       Impact factor: 9.546

Review 3.  Lopinavir/Ritonavir: a review of its use in the management of HIV-1 infection.

Authors:  Jamie D Croxtall; Caroline M Perry
Journal:  Drugs       Date:  2010-10-01       Impact factor: 9.546

4.  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

5.  Can linear regression modeling help clinicians in the interpretation of genotypic resistance data? An application to derive a lopinavir-score.

Authors:  Alessandro Cozzi-Lepri; Mattia C F Prosperi; Jesper Kjær; David Dunn; Roger Paredes; Caroline A Sabin; Jens D Lundgren; Andrew N Phillips; Deenan Pillay
Journal:  PLoS One       Date:  2011-11-16       Impact factor: 3.240

6.  Predictive factors of virological success to salvage regimens containing protease inhibitors in HIV-1 infected children.

Authors:  Beatriz Larru; Carmen de Mendoza; José Ma Bellón; Ma Isabel de José; Ma José Mellado; Vincent Soriano; Ma Angeles Muñoz-Fernandez; José T Ramos
Journal:  BMC Infect Dis       Date:  2007-06-10       Impact factor: 3.090

7.  Temporal Trends in HIV-1 Mutations Used for the Surveillance of Transmitted Drug Resistance.

Authors:  Soo-Yon Rhee; Philip L Tzou; Robert W Shafer
Journal:  Viruses       Date:  2021-05-11       Impact factor: 5.048

  7 in total

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