Literature DB >> 17576846

Predictive genotypic algorithm for virologic response to lopinavir-ritonavir in protease inhibitor-experienced patients.

Martin S King1, Richard Rode, Isabelle Cohen-Codar, Vincent Calvez, Anne-Geneviève Marcelin, George J Hanna, Dale J Kempf.   

Abstract

Several genotypic resistance algorithms have been proposed for quantitation of the degree of phenotypic resistance to the human immunodeficiency virus (HIV) protease inhibitor (PI) lopinavir (LPV), including the original LPV mutation score. In this study, we retrospectively evaluated 21 codons in HIV protease known to be associated with PI resistance in a large antiretroviral agent-experienced observational patient cohort, "Autorisation Temporaire d'Utilization" (ATU), to assess whether a more optimal algorithm could be derived by using virologic response data from patients treated with LPV in combination with ritonavir (LPV/r). Five of the 11 mutations constituting the LPV mutation score were not associated with a virologic response, while 4 additional mutations not included in this score demonstrated an association. Therefore, the LPV ATU score, which includes mutations at codons 10, 20, 24, 33, 36, 47, 48, 54, 82, and 84, was constructed and shown in two different types of multivariable analyses of the ATU cohort to be a better predictor of the virologic response than the LPV mutation score. The LPV ATU score was also more strongly associated with a virologic response when it was applied to independent clinical trial populations of PI-experienced patients receiving LPV/r. This study provides the basis for a new genotypic resistance algorithm that is useful for predicting the antiviral activities of LPV/r-based regimens in PI-experienced patients. The refined algorithm may be useful in making clinical treatment decisions and in refining genetic and pharmacologic methods for assessing the activity of LPV/r.

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Year:  2007        PMID: 17576846      PMCID: PMC2043245          DOI: 10.1128/AAC.00388-07

Source DB:  PubMed          Journal:  Antimicrob Agents Chemother        ISSN: 0066-4804            Impact factor:   5.191


  18 in total

1.  Analysis of the virological response with respect to baseline viral phenotype and genotype in protease inhibitor-experienced HIV-1-infected patients receiving lopinavir/ritonavir therapy.

Authors:  Dale J Kempf; Jeffrey D Isaacson; Martin S King; Scott C Brun; Jacquelyn Sylte; Bruce Richards; Barry Bernstein; Richard Rode; Eugene Sun
Journal:  Antivir Ther       Date:  2002-09

2.  Enhanced prediction of lopinavir resistance from genotype by use of artificial neural networks.

Authors:  Dechao Wang; Brendan Larder
Journal:  J Infect Dis       Date:  2003-08-14       Impact factor: 5.226

Review 3.  Resistance to HIV protease inhibitors: mechanisms and clinical consequences.

Authors:  Carmen de Mendoza; Vincent Soriano
Journal:  Curr Drug Metab       Date:  2004-08       Impact factor: 3.731

4.  Selection of resistance in protease inhibitor-experienced, human immunodeficiency virus type 1-infected subjects failing lopinavir- and ritonavir-based therapy: mutation patterns and baseline correlates.

Authors:  Hongmei Mo; Martin S King; Kathryn King; Akhteruzzaman Molla; Scott Brun; Dale J Kempf
Journal:  J Virol       Date:  2005-03       Impact factor: 5.103

5.  Improving lopinavir genotype algorithm through phenotype correlations: novel mutation patterns and amprenavir cross-resistance.

Authors:  Neil T Parkin; Colombe Chappey; Christos J Petropoulos
Journal:  AIDS       Date:  2003-05-02       Impact factor: 4.177

6.  Clinically relevant interpretation of genotype and relationship to plasma drug concentrations for resistance to saquinavir-ritonavir in human immunodeficiency virus type 1 protease inhibitor-experienced patients.

Authors:  Anne-Geneviève Marcelin; Cécile Dalban; Gilles Peytavin; Claire Lamotte; Rachid Agher; Constance Delaugerre; Marc Wirden; Françoise Conan; Sylvie Dantin; Christine Katlama; Dominique Costagliola; Vincent Calvez
Journal:  Antimicrob Agents Chemother       Date:  2004-12       Impact factor: 5.191

7.  Zidovudine resistance predicted by direct detection of mutations in DNA from HIV-infected lymphocytes.

Authors:  B A Larder; P Kellam; S D Kemp
Journal:  AIDS       Date:  1991-02       Impact factor: 4.177

8.  Antiretroviral drug resistance testing in adults infected with human immunodeficiency virus type 1: 2003 recommendations of an International AIDS Society-USA Panel.

Authors:  Martin S Hirsch; Françoise Brun-Vézinet; Bonaventura Clotet; Brian Conway; Daniel R Kuritzkes; Richard T D'Aquila; Lisa M Demeter; Scott M Hammer; Victoria A Johnson; Clive Loveday; John W Mellors; Donna M Jacobsen; Douglas D Richman
Journal:  Clin Infect Dis       Date:  2003-06-23       Impact factor: 9.079

9.  Stochastic processes strongly influence HIV-1 evolution during suboptimal protease-inhibitor therapy.

Authors:  M Nijhuis; C A Boucher; P Schipper; T Leitner; R Schuurman; J Albert
Journal:  Proc Natl Acad Sci U S A       Date:  1998-11-24       Impact factor: 11.205

10.  Susceptibility of HIV-1 isolates to zidovudine: correlation between widely applicable culture test and PCR analysis.

Authors:  M Jung; H Agut; D Candotti; D Ingrand; C Katlama; J M Huraux
Journal:  J Acquir Immune Defic Syndr (1988)       Date:  1992
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  10 in total

1.  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

Review 2.  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

3.  Two different patterns of mutations are involved in the genotypic resistance score for atazanavir boosted versus unboosted by ritonavir in multiple failing patients.

Authors:  M M Santoro; A Bertoli; P Lorenzini; F Ceccherini-Silberstein; N Gianotti; C Mussini; C Torti; G Di Perri; G Barbarini; T Bini; S Melzi; P Caramello; R Maserati; P Narciso; V Micheli; A Antinori; C F Perno
Journal:  Infection       Date:  2009-01-23       Impact factor: 3.553

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

Review 6.  HIV-1 drug resistance and resistance testing.

Authors:  Dana S Clutter; Michael R Jordan; Silvia Bertagnolio; Robert W Shafer
Journal:  Infect Genet Evol       Date:  2016-08-29       Impact factor: 3.342

7.  Scoring methods for building genotypic scores: an application to didanosine resistance in a large derivation set.

Authors:  Allal Houssaini; Lambert Assoumou; Veronica Miller; Vincent Calvez; Anne-Geneviève Marcelin; Philippe Flandre
Journal:  PLoS One       Date:  2013-03-21       Impact factor: 3.240

8.  Phenotypic characterization of virological failure following lopinavir/ritonavir monotherapy using full-length Gag-protease genes.

Authors:  Katherine A Sutherland; Jean L Mbisa; Jade Ghosn; Marie-Laure Chaix; Isabelle Cohen-Codar; Stephane Hue; Jean-Francois Delfraissy; Constance Delaugerre; Ravindra K Gupta
Journal:  J Antimicrob Chemother       Date:  2014-08-04       Impact factor: 5.790

Review 9.  Modifying Antiretroviral Therapy in Virologically Suppressed HIV-1-Infected Patients.

Authors:  Sean E Collins; Philip M Grant; Robert W Shafer
Journal:  Drugs       Date:  2016-01       Impact factor: 9.546

10.  Collaborative update of a rule-based expert system for HIV-1 genotypic resistance test interpretation.

Authors:  Roger Paredes; Philip L Tzou; Gert van Zyl; Geoff Barrow; Ricardo Camacho; Sergio Carmona; Philip M Grant; Ravindra K Gupta; Raph L Hamers; P Richard Harrigan; Michael R Jordan; Rami Kantor; David A Katzenstein; Daniel R Kuritzkes; Frank Maldarelli; Dan Otelea; Carole L Wallis; Jonathan M Schapiro; Robert W Shafer
Journal:  PLoS One       Date:  2017-07-28       Impact factor: 3.752

  10 in total

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