ObjectivesTo evaluate the pharmacokinetics, tolerability and safety of 300 mg of atazanavir boosted with 100 or 50 mg of ritonavir, both once daily, at steady state.
Optimizing antiretroviral drug combination on an individual basis can be challenging, particularly in settings with limited access to drugs and genotypic resistance testing. Here we describe our latest computational models to predict treatment responses, with or without a genotype, and compare their predictive accuracy with that of genotyping.
With the goal of facilitating the use of HIV-TRePS to optimize therapy in settings with limited healthcare resources, we aimed to develop computational models to predict treatment responses accurately in the absence of commonly used baseline data.Twelve sets of random forest models were trained using very large, global datasets to predict either the probability of virological response (classifier models) or the absolute change in viral load in response to a new regimen (absolute models) following virological failure. Two 'standard' models were developed with all baseline variables present and 10 others developed without HIV genotype, time on therapy, CD4 count or any combination of the above.The standard classifier models achieved an AUC of 0.89 in cross-validation and independent testing. Models with missing variables achieved AUC values of 0.78-0.90. The standard absolute models made predictions that correlated significantly with observed changes in viral load with a mean absolute error of 0.65 log10 copies HIV RNA/mL in cross-validation and 0.69 log10 copies HIV RNA/mL in independent testing. Models with missing variables achieved values of 0.65-0.75 log10 copies HIV RNA/mL. All models identified alternative regimens that were predicted to be effective for the vast majority of cases where the new regimen prescribed in the clinic failed. All models were significantly better predictors of treatment response than genotyping with rules-based interpretation.These latest models that predict treatment responses accurately, even when a number of baseline variables are not available, are a major advance with greatly enhanced potential benefit, particularly in resource-limited settings. The only obstacle to realizing this potential is the willingness of healthcare professions to use the system.
Etravirine is approved for use in treatment-experienced patients at a dose of 200 mg twice daily. Efavirenz has been associated with greater increases in serum lipids compared with other non-nucleosides in randomized trials of first-line treatment. In this double-blind, placebo-controlled trial, 157 treatment-naive patients with HIV RNA >5000 copies/mL were randomized 1 : 1 to either 400 mg of etravirine once daily (n = 79) or 600 mg of efavirenz once daily (n = 78) plus two nucleoside analogues (either abacavir/lamivudine, zidovudine/lamivudine or tenofovir/emtricitabine) for 48 weeks. Lipids were measured under fasting conditions at baseline and all visits to Week 48. Clinicaltrials.gov identifier: NCT00903682. Overall, the patients had a median baseline CD4 count of 302 cells/mm3 (range 74–722) and a median HIV RNA of 4.8 log10 copies/mL (range 3.5–6.6). Both the non-nucleosides and the nucleoside analogues used caused changes in serum lipids. In the efavirenz arm, patients showed significantly larger increases in high-density lipoprotein (HDL) (+0.15 mmol/L, P = 0.004), low-density lipoprotein (LDL) (+0.35 mmol/L, P = 0.005), total cholesterol (+0.61 mmol/L, P < 0.0001) and triglycerides (+0.33 mmol/L, P = 0.03) at Week 48 compared with the etravirine arm. Across the two arms, patients taking abacavir/lamivudine showed greater increases in total cholesterol (+0.47 mmol/L, P = 0.005) compared with patients taking tenofovir/emtricitabine. There were fewer grade 3/4 elevations in total cholesterol, LDL and triglycerides in the etravirine arm (2 patients, 1 patient and 0 patients, respectively) versus the efavirenz arm (8 patients, 6 patients and 2 patients, respectively). In the SENSE trial, first-line treatment with 400 mg of etravirine once daily plus two nucleoside analogues led to fewer grade 3 or 4 lipid elevations compared with efavirenz plus two nucleoside analogues.
ObjectivesThe optimal individualized selection of antiretroviral drugs in resource-limited settings is challenging because of the limited availability of drugs and genotyping. Here we describe the development of the latest computational models to predict the response to combination antiretroviral therapy without a genotype, for potential use in such settings.
A workshop was organized in Madrid on March 2000 to update recommendations for the use of drug resistance testing in HIV infection in Spain, based on new information and tests currently available. A panel of 30 physicians with wide experience in the field of antiretroviral therapy and/or resistance testing convened in a full-day session. Available clinical and laboratory data reported in the medical literature, conferences, and panel expert opinion were presented and discussed in an open fashion. The panel agreed to identify situations in which resistance testing should be recommended, others in which it might be considered, and others in which it should not be used. In summary, drug resistance testing should be recommended in HIV-positive pregnant women, in children (infected) born to treated mothers, in primary HIV infection or recent seroconversion, in early virological treatment failures, and before introducing a salvage regimen in heavily pre-treated subjects. Two situations were recognized in which resistance testing might be considered: in chronic naive infected subjects before beginning therapy, and in post-exposure prophylaxis. Lastly, testing should not be recommended when no treatment options exist for a given patient, or when plasma viremia is below the limit of detection. In summary, specific situations have been identified in which drug resistance testing might be of value for choosing antiretroviral therapy either in naive or pre-treated subjects. The advantages of this new tool remain controversial in any other circumstances.
Alternation of antiretroviral drug regimens has been proposed as a novel treatment strategy for HIV infection. However, some concerns persist regarding antiviral efficacy, adherence, toxicity and resistance evolution in the long term.A total of 161 antiretroviral-naive HIV-1-infected patients were randomized to receive stavudine/didanosine/efavirenz (group A) or zidovudine/lamivudine/ nelfinavir (group B) or to alternate between the two regimens every 3 months starting with regimen A (group C). Antiviral efficacy, adherence, safety and tolerability were analysed every 12 weeks.After 96 weeks, time to virological failure was significantly delayed in the alternating regimen compared with the standards of care regimens. Virological suppression was seen in 46%, 48% and 58% of patients in groups A, B and C, respectively, in the intention-to-treat analysis and in 75%, 76% and 97% in the on-treatment analysis (A vs C: P=0.014; B vs C: P=0.016; A vs B: P=0.849). At the end of the study, 94% of patients in group A and 92% in groups B and C reported an adherence greater than 95%. Alternating therapy was associated with a similar impact on CD4+ counts in comparison with the standards of care regimens, as well as a lower mitochondrial DNA/nuclear DNA (mtDNA/nDNA) ratio decrease in the mitochondrial substudy performed on 37 patients. The frequency and intensity of adverse events in the alternating group decreased during subsequent cycles.Our results favour the hypothesis that proactive therapy switching may delay the accumulation of resistance mutations. Moreover, the alternating regimen was well tolerated and adherence remained comparably high in all treatment groups. The lower mtDNA/nDNA ratio decrease observed in this group may imply a lower impact on mitochondrial toxicity than in standard regimens.
Etravirine (ETR) is a next generation non‐nucleoside reverse transcriptase inhibitor (NNRTI). The studies for ETR EMA approval were almost exclusively performed together with the protease inhibitor (PI) darunavir. However the fact that ETR can be active against NNRTI‐pretreated HIV variants and that it is well tolerated suggests its application in PI‐free antiretroviral combination therapies. Although approved only for PI‐containing therapies, a number of ETR treatments without PIs are performed currently. To evaluate the performance of ETR in PI‐free regimens, we analyzed the EURESIST database. We observed a total of 70 therapy switches to a PI‐free, ETR containing antiretroviral combination with detectable baseline viral load. 50/70 switches were in male patients and 20/70 in females. The median of previous treatments was 10. The following combinations were detected in the EURESIST database: ETR+MVC+RAL (20.0%); ETR+FTC+TDF (18.6%); 3TC+ETR+RAL (7.1%); 3TC+ABC+ETR (5.7%); other combinations (31.4%). A switch was defined as successful when either ≤50 copies/mL or a decline of the viral load of 2 log 10 , both at week 24 (range 18–30) were achieved. The overall success rate (SR) was 77% (54/70), and for the different combinations: ETR+MVC+RAL=78.6% (11/14); ETR+FTC+TDF=92.3% (12/13); 3TC+ETR+RAL =80.0% (4/5), 3TC+ABC+ETR=100% (SR 4/4); and for other combinations=67.6% (23/34). These SR values are comparable to those for other therapy combinations in such pretreated patients.
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