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Raltegravir (RAL) is the first licensed antiretroviral integrase inhibitor that may be used both for treatment-naïve human immunodeficiency virus type 1 (HIV-1) patients and for salvage therapy. The Brazilian public free access programme limits its use for salvage therapy, with scarce information regarding RAL resistance from patients failing a RAL-containing salvage regimen. This study evaluated RAL resistance mutations detected by population sequencing in 69 HIV-infected patients with advanced disease failing a RAL-containing regimen in a real-world setting. RAL resistance mutations were identified in 47/69 patients (68%). The most common salvage regimen, used by 56/69 patients (81%), included lamivudine, tenofovir, darunavir/ritonavir and RAL. At failure, major RAL resistance mutations included Q148H/R/K (21/47; 45%), N155H (14/47; 30%), Y143R/H/C (3/47; 6%) and E92Q (1/47; 2%). Most samples with Q148H/R/K also showed G140S/A/C (21/47; 45%). RAL resistance was significantly associated with less than two active drugs in the optimised background therapy regimen at failure [39/39 (100%) vs. 9/17 (53%); P<0.001] and with a longer cumulative duration with detectable viraemia (viral load >50 copies/mL) (86 weeks vs. 32 weeks; P=0.001). A high frequency of RAL mutations was observed in this study. In addition, these results reinforce the importance of close monitoring of RAL-containing regimens to reduce the time of failure and consequent resistance accumulation., (Copyright © 2013 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.)

While human immunodeficiency virus (HIV)-1 chemokine co-receptors 5 tropism and the GWGR motif in the envelope third variable region (V3 loop) have been associated with a slower disease progression, their influence on antiretroviral response remains unclear. The impact of baseline V3 characteristics on treatment response was evaluated in a randomised, double blind, prospective cohort study with patients initiating highly active antiretroviral therapy with lopinavir or efavirenz plus azithothymidine/3TC (1:1) over 48 weeks. Similar virological and immunological responses were observed for both treatment regimens. The 43 individuals had a mean baseline CD4 T cell count of 119 cells/mm(3) [standard deviation (SD) = 99] and a mean viral load of 5.09 log(10) copies/mL (SD = 0.49). The GWGR motif was not associated with a CD4 T cell response, but predicted R5 tropism by the geno2pheno([clinical20%]) algorithm correlated with higher CD4 T cell levels at all monitoring points (p < 0.05). Moreover, higher false-positive rates (FPR) values from this analysis revealed a strong correlation with CD4 T cell recovery (p < 0.0001). Transmitted drug resistance mutations, documented in 3/41 (7.3%) cases, were unrelated to the assigned antiretroviral regimen and had no impact on patient outcomes. In conclusion, naÏve HIV-1 R5 infected patients exhibited higher CD4 T cell counts at baseline; this difference was sustained throughout therapy. The geno2pheno([clinical]) option FPR positively correlated with CD4 T cell gain and may be useful in predicting CD4 T cell recovery.

The objective of this study was to assess if a simple evaluation, adherence to antiretroviral therapy, would correlate to clinical and laboratory outcomes. We followed an open cohort of patients from a public teaching hospital AIDS outpatient clinic. Patients were categorized according to adherence as: regular (Reg), optimal, all doses all days, tolerating only irregular timing (+/- 2 hours) of intake; quasi-regular (qReg), those missing up to four doses or 1 full day during a month; irregular (Irreg), all other irregular regimens, and ignored (Ign), those without information. The results from a simple questionnaire were compared to CD4+ cell counts and human immunodeficiency virus type 1 (HIV-1) RNA plasma viremia. One hundred eighty-two HIV-1-infected patients (126 males, 69%; 56 females, 31%) were analyzed. Information on adherence was available for 168 (90%). Reg adherence was reported by 75 (41%) patients, qReg adherence by 35 (19%), and Irreg by 53 (29%) of patients. The main reasons for nonadherence were forgetfulness, intolerance, use of alcohol, and misunderstanding of prescription. A significant increase of CD4+ T-cell counts and absolute gain were only observed among Reg and qReg users (p < 0.001). The median viral RNA load log10 decreases were -1.68, -1.45, -0.9 log, respectively, for Reg, qReg, and Irreg patients (p = 0.043, Kruskal-Wallis). Development of and death from AIDS occurred almost exclusively among those with Ign or Irreg adherence. Previous use of antiretroviral therapy may have had an impact in treatment response. Individuals who were treatment-naive were more likely to be Reg users (41%). Although more refined methods to assess adherence should be implemented when available, the inability to do so should not prevent simple, albeit subjective measurements that also correlate with favorable outcome. Mechanisms to improve adherence should be considered an integral part of antiretroviral therapy.