Literature DB >> 15577415

Selection of antiretroviral therapy guided by genotypic or phenotypic resistance testing: an open-label, randomized, multicenter study (PhenGen).

Annalisa Saracino1, Laura Monno, Sergio Locaputo, Carlo Torti, Luigia Scudeller, Nicoletta Ladisa, Andrea Antinori, Laura Sighinolfi, Antonio Chirianni, Francesco Mazzotta, Gianpiero Carosi, Gioacchino Angarano.   

Abstract

The phenotype/genotype (PhenGen) open-label, randomized, multicenter study evaluated the genotype/virtual phenotype (vPt) and real phenotype (rPt) for choosing a new highly active antiretroviral therapy regimen at failure. Patients with a plasma viral load (pVL) between 2000 and 200,000 copies/mL and a CD4 cell count >200/microL, failing > or =2 regimens (<6 drugs), were randomized for vPt or rPt. Three hundred three patients were enrolled: 111 and 108 patients received a new treatment in the vPt and rPt arms, respectively. The 2 groups were comparable for baseline patient characteristics and treatment history. The new therapy was in agreement with expert advice in 58.5% of cases. After 6 months, no statistical differences were found in the mean absolute change from baseline CD4 cells (+55 and +46 cells/muL; P = 0.7), mean pVL log decrease (-1.35 and -1.37; P = 0.8), or proportion of patients with a pVL <400 copies/mL (54.8% in vPt arm and 52.6% in rPt arm; P = 0.9). At multivariate analysis, variables independently associated with failure of the new regimen were: pVL at baseline (odds ratio [OR] = 1.81; P < 0.021), number of nucleoside reverse transcriptase inhibitor-associated mutations (OR = 1.21; P = 0.001), number of protease mutations (OR = 1.15; P < 0.001), and recycling of indinavir (OR = 4.63; P = 0.019). Patients' adherence to the prescribed regimen (OR = 0.23; P < 0.001), number of active drugs in the new regimen (OR = 0.55; P = 0.001), and adherence to expert advice (OR = 0.37; P < 0.001) predicted virologic response. The vPt is as predictive of treatment outcome as the rPT. Use of expert advice significantly improved the response to therapy.

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Year:  2004        PMID: 15577415     DOI: 10.1097/00126334-200412150-00011

Source DB:  PubMed          Journal:  J Acquir Immune Defic Syndr        ISSN: 1525-4135            Impact factor:   3.731


  5 in total

1.  Genotypic susceptibility scores and HIV type 1 RNA responses in treatment-experienced subjects with HIV type 1 infection.

Authors:  Jeffrey A Anderson; Hongyu Jiang; Xiao Ding; Leslie Petch; Terri Journigan; Susan A Fiscus; Richard Haubrich; David Katzenstein; Ronald Swanstrom; Roy M Gulick
Journal:  AIDS Res Hum Retroviruses       Date:  2008-05       Impact factor: 2.205

Review 2.  Clinical management of HIV drug resistance.

Authors:  Karoll J Cortez; Frank Maldarelli
Journal:  Viruses       Date:  2011-04-14       Impact factor: 5.048

3.  Automated prediction of HIV drug resistance from genotype data.

Authors:  ChenHsiang Shen; Xiaxia Yu; Robert W Harrison; Irene T Weber
Journal:  BMC Bioinformatics       Date:  2016-08-31       Impact factor: 3.169

4.  Antiretroviral resistance testing in HIV-positive people.

Authors:  Theresa Aves; Joshua Tambe; Reed Ac Siemieniuk; Lawrence Mbuagbaw
Journal:  Cochrane Database Syst Rev       Date:  2018-11-09

5.  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

  5 in total

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