Using observational data to emulate a randomized trial of dynamic treatment switching strategies

BACKGROUND: When a clinical treatment fails or shows suboptimal results, the question of when to switch to another treatment arises. Treatment switching strategies are often dynamic because the time of switching depends on the evolution of an individual's time-varying covariates. Dynamic strategies can be directly compared in randomized trials. For example, HIV-infected individuals receiving antiretroviral therapy could be randomized to switching therapy within 90 days of HIV-1 RNA crossing above a threshold of either 400 copies/ml (tight-control strategy) or 1000 copies/ml (loose-control strategy).METHODS: We review an approach to emulate a randomized trial of dynamic switching strategies using observational data from the Antiretroviral Therapy Cohort Collaboration, the Centers for AIDS Research Network of Integrated Clinical Systems and the HIV-CAUSAL Collaboration. We estimated the comparative effect of tight-control vs. loose-control strategies on death and AIDS or death via inverse-probability weighting.RESULTS: Of 43 803 individuals who initiated an eligible antiretroviral therapy regimen in 2002 or later, 2001 met the baseline inclusion criteria for the mortality analysis and 1641 for the AIDS or death analysis. There were 21 deaths and 33 AIDS or death events in the tight-control group, and 28 deaths and 41 AIDS or death events in the loose-control group. Compared with tight control, the adjusted hazard ratios (95% confidence interval) for loose control were 1.10 (0.73, 1.66) for death, and 1.04 (0.86, 1.27) for AIDS or death.CONCLUSIONS: Although our effective sample sizes were small and our estimates imprecise, the described methodological approach can serve as an example for future analyses

Increasing prevalence of non-clade B HIV-1 strains in heterosexual men and women, as monitored by analysis of reverse transcriptase and protease sequences

OBJECTIVE: We evaluated the prevalence of HIV-1 non-clade B over time in a formerly clade B-restricted area. Protease and reverse transcriptase regions of the pol gene were used for phylogenetic and recombination analysis and for clade assignment to HIV-1 A-D, F-H, J, and K strains of the M group. METHODS: The pol gene of 349 HIV-1 patients belonging to the Italian Cohort Naive for Antiretrovirals (ICONA) were genotypically analyzed to study the prevalence of antiretroviral-associated resistance mutations. All HIV-1 pol sequences and 32 HIV reference strains were analyzed, including the reference strains for the major HIV-1 subtypes. The non-clade B sequences according to the HIV-1 Subtyping Tool program were further studied by a bootscan analysis (SimPlot) to investigate the likelihood of recombination between subtypes. RESULTS: Phylogenetic analysis detected 19 of 349 (5.4%) non-clade B subtypes. The proportions of patients carrying non-clade B virus before and after 1997 were 1.9% and 8.4%, respectively (p =.008). Among whites, heterosexual infection and female gender were significantly associated with the presence of non-clade B subtypes (p =.001 and.005, respectively). Non-clade B HIV-1 was harbored by 14.5% of the heterosexuals who were found to be HIV-1 positive after 1997, 60% of whom were women. Bootscan analysis identified four strains as F, two as A, one as C, one as G, and 11 (57.9 %) as non-clade B recombinant subtypes. CONCLUSION: Detection of HIV-1 subtypes and intersubtype recombinants in a previously clade B-homogeneous area indicates that the HIV-1 epidemic is evolving in Italy and that heterosexuals and women are at increased risk of infection with non-clade B HIV-1 subtypes. Sequences inferred from the pol gene yield to establish the subtype of circulating HIV-1 strains. As a consequence, genotyping of pol gene for testing resistance to antiretrovirals warrants concomitant surveillance of non-clade B subtypes.status: publishe

J Antimicrob Chemother

Objectives NEAT001/ANRS143 demonstrated non-inferiority of once-daily darunavir/ritonavir (800/100 mg) + twice-daily raltegravir (400 mg) versus darunavir/ritonavir + tenofovir disoproxil fumarate/emtricitabine (245/200 mg once daily) in treatment-naive patients. We investigated the population pharmacokinetics of darunavir, ritonavir, tenofovir and emtricitabine and relationships with demographics, genetic polymorphisms and virological failure. Methods Non-linear mixed-effects models (NONMEM v. 7.3) were applied to determine pharmacokinetic parameters and assess demographic covariates and relationships with SNPs (SLCO3A1, SLCO1B1, NR1I2, NR1I3, CYP3A5*3, CYP3A4*22, ABCC2, ABCC10, ABCG2 and SCL47A1). The relationship between model-predicted darunavir AUC0–24 and C24 with time to virological failure was evaluated by Cox regression. Results Of 805 enrolled, 716, 720, 347 and 361 were included in the darunavir, ritonavir, tenofovir and emtricitabine models, respectively (11% female, 83% Caucasian). No significant effect of patient demographics or SNPs was observed for darunavir or tenofovir apparent oral clearance (CL/F); coadministration of raltegravir did not influence darunavir or ritonavir CL/F. Ritonavir CL/F decreased by 23% in NR1I2 63396C>T carriers and emtricitabine CL/F was linearly associated with creatinine clearance (P<0.001). No significant relationship was demonstrated between darunavir AUC0–24 or C24 and time to virological failure [HR (95% CI): 2.28 (0.53–9.80), P=0.269; and 1.82 (0.61–5.41), P=0.279, respectively]. Conclusions Darunavir concentrations were unaltered in the presence of raltegravir and not associated with virological failure. Polymorphisms investigated had little impact on study-drug pharmacokinetics. Darunavir/ritonavir + raltegravir may be an appropriate option for patients experiencing NRTI-associated toxicity