BACKGROUND: We assessed the association of baseline HIV-1 mutations, phenotypic sensitivity and pharmacokinetics with virological failure (VF) at week 12 (W12) after onset of a darunavir/ritonavir (DRV/r)-based regimen in a cohort of 67 antiretroviral-experienced HIV-patients failing on highly active antiretroviral therapy (HAART). METHODS: VF was defined as HIV RNA >2.3 log10copies/ml at W12. HIV reverse transcriptase and protease sequencing was performed at WO; mutations with a P-value <0.25 in univariable analyses were used for a backward selection to find the best mutation set for VF prediction. Genotypic and phenotypic sensitivity scores were calculated and virtual phenotype predicted fold change (FC) assessed. DRV Cmin, Cmax, AUC(0-->12 h) and genotypic inhibitory quotient (GIQ) were determined. RESULTS: Patients had a median of 15 previous treatments for 10 years. Median W0 values included a T-cell count of 129 cells/microl, 4.7 log10 HIV RNA copies/ml, four major protease and six nucleoside reverse transcriptase inhibitor resistance mutations. At W12, median HIV RNA decrease was -2.1 log10 copies/ml with a gain of +67 CD4+ T-cells/microl; 40% of patients failed. We determined the genotypic score I13V+V32I+L33F/I/V+E35D+ M361/L/V+I47V+F53L+I62V. According to <4, 4-5 and >5 mutations, failure occurred in 11%, 48% and 100% of patients. Failure was associated with CDC stage, baseline CD4+ T-cell count, number of major protease inhibitor resistance mutations, FC and DRV/r score. Pharmacokinetics were not associated with failure, but GIQ was. CONCLUSION: At W12, 60% of heavily pretreated patients responded on DRV/r-based HAART. Genotypic and phenotypic information constituted the main virological response determinant in patients with optimal drug concentrations.
BACKGROUND: We assessed the association of baseline HIV-1 mutations, phenotypic sensitivity and pharmacokinetics with virological failure (VF) at week 12 (W12) after onset of a darunavir/ritonavir (DRV/r)-based regimen in a cohort of 67 antiretroviral-experienced HIV-patients failing on highly active antiretroviral therapy (HAART). METHODS:VF was defined as HIV RNA >2.3 log10copies/ml at W12. HIV reverse transcriptase and protease sequencing was performed at WO; mutations with a P-value <0.25 in univariable analyses were used for a backward selection to find the best mutation set for VF prediction. Genotypic and phenotypic sensitivity scores were calculated and virtual phenotype predicted fold change (FC) assessed. DRV Cmin, Cmax, AUC(0-->12 h) and genotypic inhibitory quotient (GIQ) were determined. RESULTS:Patients had a median of 15 previous treatments for 10 years. Median W0 values included a T-cell count of 129 cells/microl, 4.7 log10 HIV RNA copies/ml, four major protease and six nucleoside reverse transcriptase inhibitor resistance mutations. At W12, median HIV RNA decrease was -2.1 log10 copies/ml with a gain of +67 CD4+ T-cells/microl; 40% of patients failed. We determined the genotypic score I13V+V32I+L33F/I/V+E35D+ M361/L/V+I47V+F53L+I62V. According to <4, 4-5 and >5 mutations, failure occurred in 11%, 48% and 100% of patients. Failure was associated with CDC stage, baseline CD4+ T-cell count, number of major protease inhibitor resistance mutations, FC and DRV/r score. Pharmacokinetics were not associated with failure, but GIQ was. CONCLUSION: At W12, 60% of heavily pretreated patients responded on DRV/r-based HAART. Genotypic and phenotypic information constituted the main virological response determinant in patients with optimal drug concentrations.
Authors: Sanjay Pujari; Preeyaporn Srasuebkul; Somnuek Sungkanuparph; Poh Lian Lim; Nagalingeswaran Kumarasamy; John Chuah; Ritesh N Kumar; Yi-Ming A Chen; Shinichi Oka; Jun Yong Choi; Man-Po Lee; Praphan Phanuphak; Adeeba Kamarulzaman; Christopher Lee; Zhang Fujie; Rosanna Ditangco; Vonthanak Saphonn; Thira Sirisanthana; Tuti Parwati Merati; Jeff Smith; Matthew G Law Journal: J Antivir Antiretrovir Date: 2009-11-01
Authors: M Fabbiani; L Bracciale; E Ragazzoni; R Santangelo; P Cattani; S Di Giambenedetto; G Fadda; P Navarra; R Cauda; A De Luca Journal: Infection Date: 2011-08-25 Impact factor: 3.553
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
Authors: 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 Roca; Peter Reiss; Eugen Schülter; Carlo Torti; Ard van Sighem; Robert Zangerle; Diane Descamps Journal: J Antimicrob Chemother Date: 2016-01-28 Impact factor: 5.790