Predicting Virological Response to HIV Treatment Over Time: A Tool for Settings With Different Definitions of Virological Response.

OBJECTIVE: Definitions of virological response vary from <50 up to 1000 copies of HIV-RNA/mL. Our previous models estimate the probability of HIV drug combinations reducing the viral load to <50 copies/mL, with no indication of whether higher thresholds of response may be achieved. Here, we describe the development of models that predict absolute viral load over time. METHODS: Two sets of random forest models were developed using 50,270 treatment change episodes from more than 20 countries. The models estimated viral load at different time points following the introduction of a new regimen from variables including baseline viral load, CD4 count, and treatment history. One set also used genotypes in their predictions. Independent data sets were used for evaluation. RESULTS: Both models achieved highly significant correlations between predicted and actual viral load changes (r = 0.67-0.68, mean absolute error of 0.73-0.74 log10 copies/mL). The models produced curves of virological response over time. Using failure definitions of <100, 400, or 1000 copies/mL, but not 50 copies/mL, both models were able to identify alternative regimens they predicted to be effective for the majority of cases where the new regimen prescribed in the clinic failed. CONCLUSIONS: These models could be useful for selecting the optimum combination therapy for patients requiring a change in therapy in settings using any definition of virological response. They also give an idea of the likely response curve over time. Given that genotypes are not required, these models could be a useful addition to the HIV-TRePS system for those in resource-limited settings.

Limited overlap between phylogenetic HIV and hepatitis C virus clusters illustrates the dynamic sexual network structure of Dutch HIV-infected MSM.

OBJECTIVE: MSM are at increased risk for infection with HIV-1 and hepatitis C virus (HCV). Is HIV/HCV coinfection confined to specific HIV transmission networks? DESIGN AND METHODS: A HIV phylogenetic tree was constructed for 5038 HIV-1 subtype B polymerase (pol) sequences obtained from MSM in the AIDS therapy evaluation in the Netherlands cohort. We investigated the existence of HIV clusters with increased HCV prevalence, the HIV phylogenetic density (i.e. the number of potential HIV transmission partners) of HIV/HCV-coinfected MSM compared with HIV-infected MSM without HCV, and the overlap in HIV and HCV phylogenies using HCV nonstructural protein 5B sequences from 183 HIV-infected MSM with acute HCV infection. RESULTS: Five hundred and sixty-three of 5038 (11.2%) HIV-infected MSM tested HCV positive. Phylogenetic analysis revealed 93 large HIV clusters (≥10 MSM), 370 small HIV clusters (2-9 MSM), and 867 singletons with a median HCV prevalence of 11.5, 11.6, and 9.3%, respectively. We identified six large HIV clusters with elevated HCV prevalence (range 23.5-46.2%). Median HIV phylogenetic densities for MSM with HCV (3, interquartile range 1-7) and without HCV (3, interquartile range 1-8) were similar. HCV phylogeny showed 12 MSM-specific HCV clusters (clustersize: 2-39 HCV sequences); 12.7% of HCV infections were part of the same HIV and HCV cluster. CONCLUSION: We observed few HIV clusters with elevated HCV prevalence, no increase in the HIV phylogenetic density of HIV/HCV-coinfected MSM compared to HIV-infected MSM without HCV, and limited overlap between HIV and HCV phylogenies among HIV/HCV-coinfected MSM. Our data do not support the existence of MSM-specific sexual networks that fuel both the HIV and HCV epidemic.

An update to the HIV-TRePS system: the development of new computational models that do not require a genotype to predict HIV treatment outcomes.

OBJECTIVES: The 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. METHODS: Random forest models were trained to predict the probability of a virological response to therapy (<50 copies HIV RNA/mL) following virological failure using the following data from 22,567 treatment-change episodes including 1090 from southern Africa: baseline viral load and CD4 cell count, treatment history, drugs in the new regimen, time to follow-up and follow-up viral load. The models were assessed during cross-validation and with an independent global test set of 1000 cases including 100 from southern Africa. The models' accuracy [area under the receiver-operating characteristic curve (AUC)] was evaluated and compared with genotyping using rules-based interpretation systems for those cases with genotypes available. RESULTS: The models achieved AUCs of 0.79-0.84 (mean 0.82) during cross-validation, 0.80 with the global test set and 0.78 with the southern African subset. The AUCs were significantly lower (0.56-0.57) for genotyping. CONCLUSIONS: The models predicted virological response to HIV therapy without a genotype as accurately as previous models that included a genotype. They were accurate for cases from southern Africa and significantly more accurate than genotyping. These models will be accessible via the online treatment support tool HIV-TRePS and have the potential to help optimize antiretroviral therapy in resource-limited settings where genotyping is not generally available.

Single nucleotide polymorphism in gene encoding transcription factor Prep1 is associated with HIV-1-associated dementia.

BACKGROUND: Infection with HIV-1 may result in severe cognitive and motor impairment, referred to as HIV-1-associated dementia (HAD). While its prevalence has dropped significantly in the era of combination antiretroviral therapy, milder neurocognitive disorders persist with a high prevalence. To identify additional therapeutic targets for treating HIV-associated neurocognitive disorders, several candidate gene polymorphisms have been evaluated, but few have been replicated across multiple studies. METHODS: We here tested 7 candidate gene polymorphisms for association with HAD in a case-control study consisting of 86 HAD cases and 246 non-HAD AIDS patients as controls. Since infected monocytes and macrophages are thought to play an important role in the infection of the brain, 5 recently identified single nucleotide polymorphisms (SNPs) affecting HIV-1 replication in macrophages in vitro were also tested. RESULTS: The CCR5 wt/Δ32 genotype was only associated with HAD in individuals who developed AIDS prior to 1991, in agreement with the observed fading effect of this genotype on viral load set point. A significant difference in genotype distribution among all cases and controls irrespective of year of AIDS diagnosis was found only for a SNP in candidate gene PREP1 (p = 1.2 × 10(-5)). Prep1 has recently been identified as a transcription factor preferentially binding the -2,518 G allele in the promoter of the gene encoding MCP-1, a protein with a well established role in the etiology of HAD. CONCLUSION: These results support previous findings suggesting an important role for MCP-1 in the onset of HIV-1-associated neurocognitive disorders.

Effect of transmitted drug resistance on virological and immunological response to initial combination antiretroviral therapy for HIV (EuroCoord-CHAIN joint project): a European multicohort study.

BACKGROUND: The effect of transmitted drug resistance (TDR) on first-line combination antiretroviral therapy (cART) for HIV-1 needs further study to inform choice of optimum drug regimens. We investigated the effect of TDR on outcome in the first year of cART within a large European collaboration. METHODS: HIV-infected patients of any age were included if they started cART (at least three antiretroviral drugs) for the first time after Jan 1, 1998, and were antiretroviral naive and had at least one sample for a genotypic test taken before the start of cART. We used the WHO drug resistance list and the Stanford algorithm to classify patients into three resistance categories: no TDR, at least one mutation and fully-active cART, or at least one mutation and resistant to at least one prescribed drug. Virological failure was defined as time to the first of two consecutive viral load measurements over 500 copies per mL after 6 months of therapy. FINDINGS: Of 10,056 patients from 25 cohorts, 9102 (90·5%) had HIV without TDR, 475 (4·7%) had at least one mutation but received fully-active cART, and 479 (4·8%) had at least one mutation and resistance to at least one drug. Cumulative Kaplan-Meier estimates for virological failure at 12 months were 4·2% (95% CI 3·8-4·7) for patients in the no TDR group, 4·7% (2·9-7·5) for those in the TDR and fully-active cART group, and 15·1% (11·9-19·0) for those in the TDR and resistant group (log-rank p<0·0001). The hazard ratio for the difference in virological failure between patients with TDR and resistance to at least one drug and those without TDR was 3·13 (95% CI 2·33-4·20, p<0·0001). The hazard ratio for the difference between patients with TDR receiving fully-active cART and patients without TDR was 1·47 (95% CI 0·19-2·38, p=0·12). In stratified analysis, the hazard ratio for the risk of virological failure in patients with TDR who received fully-active cART that included a non-nucleoside reverse transcriptase inhibitor (NNRTI) compared with those without TDR was 2·0 (95% CI 0·9-4·7, p=0·093). INTERPRETATION: These findings confirm present treatment guidelines for HIV, which state that the initial treatment choice should be based on resistance testing in treatment-naive patients. FUNDING: European Community's Seventh Framework Programme FP7/2007-2013 and Gilead.

Comparison of the risks of atherosclerotic events versus death from other causes associated with antiretroviral use.

BACKGROUND: Studies considering the risk of atherosclerotic disease (AtD) associated with the use of HAART have reported inconsistent results. METHODS: Data on antiretroviral therapy (ART) use, risk factors for cardiovascular disease (CVD), AtD and death from other causes in 18 603 HIV-infected patients from two established cohorts were evaluated. The relative hazards of AtD and death from other causes were calculated using a proportional hazards competing risks framework. The impact of protease inhibitor (PI)-containing, non-nucleoside reverse transcriptase inhibitor (NNRTI)-containing or PI + NNRTI-containing regimens on these outcomes were compared to nucleoside reverse transcriptase inhibitor (NRTI)-only regimens or stopping therapy, adjusting for known CVD risk factors. RESULTS: In 77 480 person-years of follow-up (median duration 3.49 years) there were 318 AtD events including 92 myocardial infarctions and 2044 deaths. Older age, hypertension, diabetes mellitus, having smoked and HIV disease stage were significantly associated with increased risk of AtD. PI- and NNRTI-containing regimens significantly reduced the joint risk of either AtD or death from other causes compared to NRTI-only or stopping therapy [hazard ratio (HR) for PI-containing ART, 0.76, 95% confidence interval (CI), 0.73-0.78, P< 0.001; NNRTI-containing ART, 0.69, 95% CI, 0.65-0.74; P< 0.001). PI-containing ART was associated with a borderline significant increased risk of myocardial infarction (cause-specific HR for PI-containing ART 1.19, 95% CI, 1.01-1.40, P = 0.04) but not with increased risk of AtD compared to NRTI-only regimens or stopping therapy (cause-specific HR for PI-containing ART, 1.03, 95% CI, 0.95-1.13, P = 0.44). CONCLUSIONS: Overall benefits of PI- and NNRTI-based ART in reducing mortality significantly outweigh any risks of AtD in the "short-term" follow-up of this study. Traditional cardiac risk factors play an important role in determining AtD risk status.