Long-lasting protection of activity of nucleoside reverse transcriptase inhibitors and protease inhibitors (PIs) by boosted PI containing regimens

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

Although combination antiretroviral therapies seem to be effective at controlling HIV-1 infections regardless of the viral subtype, there is increasing evidence for subtype-specific drug resistance mutations. The order and rates at which resistance mutations accumulate in different subtypes also remain poorly understood. Most of this knowledge is derived from studies of subtype B genotypes, despite not being the most abundant subtype worldwide. Here, we present a methodology for the comparison of mutational networks in different HIV-1 subtypes, based on Hidden Conjunctive Bayesian Networks (H-CBN), a probabilistic model for inferring mutational networks from cross-sectional genotype data. We introduce a Monte Carlo sampling scheme for learning H-CBN models for a larger number of resistance mutations and develop a statistical test to assess differences in the inferred mutational networks between two groups. We apply this method to infer the temporal progression of mutations conferring resistance to the protease inhibitor lopinavir in a large cross-sectional cohort of HIV-1 subtype C genotypes from South Africa, as well as to a data set of subtype B genotypes obtained from the Stanford HIV Drug Resistance Database and the Swiss HIV Cohort Study. We find strong support for different initial mutational events in the protease, namely at residue 46 in subtype B and at residue 82 in subtype C. The inferred mutational networks for subtype B versus C are significantly different sharing only five constraints on the order of accumulating mutations with mutation at residue 54 as the parental event. The results also suggest that mutations can accumulate along various alternative paths within subtypes, as opposed to a unique total temporal ordering. Beyond HIV drug resistance, the statistical methodology is applicable more generally for the comparison of inferred mutational networks between any two groups.

There is a disparity in the distribution of infections by HIV-1 subtype in the world. Subtype B is predominant in America, Australia and western and central Europe, and most therapeutic strategies are based on research and clinical studies on this subtype. However, non-B subtypes represent the majority of global HIV-1 infections; e.g., subtype C alone accounts for nearly half of all HIV-1 infections. We present a statistical framework enabling the comparison of patterns of accumulating mutations in different HIV-1 subtypes. Specifically, we compare the temporal ordering of lopinavir resistance mutations in HIV-1 subtypes B versus C. To this end, we combine the Hidden Conjunctive Bayesian Network (H-CBN) model with an approximate inference scheme enabling comparisons of larger networks. We show that the development of resistance to lopinavir differs significantly between subtypes B and C, such that findings based on subtype B sequences can not always be applied to sybtype C. The described methodology is suitable for comparing different subgroups in the context of other evolutionary processes.

Effectiveness of Transmitted Drug Resistance Testing Before Initiation of Antiretroviral Therapy in HIV-Positive Individuals

BACKGROUND

For people living with HIV, major guidelines in high-income countries recommend testing for transmitted drug resistance (TDR) to guide the choice of first-line antiretroviral therapy (ART). However, individuals who fail a first-line regimen can now be switched to one of several effective regimens. Therefore, the virological and clinical benefit of TDR testing needs to be evaluated.

METHODS

We included individuals from the HIV-CAUSAL Collaboration who enrolled <6 months of HIV diagnosis between 2006 and 2015, were ART-naive, and had measured CD4 count and HIV-RNA. Follow-up started at the date when all inclusion criteria were first met (baseline). We compared 2 strategies: (1) TDR testing within 3 months of baseline versus (2) no TDR testing. We used inverse probability weighting to estimate the 5-year proportion and hazard ratios (HRs) of virological suppression (confirmed HIV-RNA <50 copies/mL), and of AIDS or death under both strategies.

RESULTS

Of 25,672 eligible individuals (82% males, 52% diagnosed in 2010 or later), 17,189 (67%) were tested for TDR within 3 months of baseline. Of these, 6% had intermediate- or high-level TDR to any antiretroviral drug. The estimated 5-year proportion virologically suppressed was 77% under TDR testing and 74% under no TDR testing; HR 1.06 (95% confidence interval: 1.03 to 1.19). The estimated 5-year risk of AIDS or death was 6% under both strategies; HR 1.03 (95% confidence interval: 0.95 to 1.12).

CONCLUSIONS

TDR prevalence was low. Although TDR testing improved virological response, we found no evidence that it reduced the incidence of AIDS or death in first 5 years after diagnosis.

Third-line antiretroviral therapy in low-income and middle-income countries (ACTG A5288): a prospective strategy study

BACKGROUND

Antiretroviral therapy (ART) management is challenging for individuals in resource-limited settings presenting for third-line treatment because of complex resistance patterns, partly due to reduced access to viral load monitoring. We aimed to evaluate use of newer antiretroviral drugs and contemporary management approaches, including population-based sequencing, to select appropriate antiretrovirals, plasma viral load monitoring, and interventions to improve adherence in individuals presenting with second-line viral failure.

METHODS

A5288 was a phase 4, third-line ART strategy study done at 19 urban sites in ten countries that enrolled adult participants with confirmed plasma HIV-1 RNA (viral load) of 1000 copies per mL or more after more than 24 weeks of protease inhibitor-based second-line ART. The primary objective was to use antiretrovirals (raltegravir, etravirine, and ritonavir-boosted darunavir) and diagnostic monitoring technologies, including viral load, genotyping, and adherence support to achieve viral load suppression (defined as ≤200 copies per mL) in 65% or more of participants. ART history and real-time drug resistance genotypes were used to assign participants to one of four cohorts: cohort A (no lopinavir resistance) stayed on second-line ART and cohorts B (B1, best available nucleoside reverse transcriptase inhibitors [NRTIs] plus ritonavir-boosted darunavir plus raltegravir; B2, ritonavir-boosted darunavir plus raltegravir plus etravirine; B3, ritonavir-boosted darunavir, raltegravir, and either tenofovir plus emtricitabine or tenofovir plus lamivudine), C (ritonavir-boosted darunavir plus raltegravir plus tenofovir-emtricitabine or tenofovir plus lamivudine), and D (best available NRTIs plus ritonavir-boosted darunavir plus raltegravir) were defined by increasing levels of resistance and received appropriate regimens, including new antiretrovirals. Participants in Cohort B without detectable hepatitis B surface antigen were assigned by blocked randomisation to cohorts B1 and B2, and those with detectable hepatitis B surface antigen were assigned to cohort B3. The trial is registered with ClinicalTrials.gov, number NCT01641367.

FINDINGS

From Jan 10, 2013, to Sept 10, 2015, 545 participants were enrolled. 287 (53%) were assigned to cohort A, 74 (14%) to B1, 72 (13%) to B2, eight (1%) to B3, 70 (13%) to C, and 34 (6%) to D. Overall, 349 (64%, 95% CI 60-68) participants achieved viral suppression at week 48, with proportions varying from 125 (44%) of 287 in cohort A to 65 (88%) of 74 in cohort B1, 63 (88%) of 72 in B2, eight (100%) of eight in B3, 63 (90%) of 70 in C, and 25 (74%) of 34 in D. Participants in cohort A remained on their second-line protease inhibitor, and had the most participants with grade 3 or higher adverse events (147 [51%]).

INTERPRETATION

Targeted real-time genotyping to select third-line ART can appropriately allocate more costly antiretrovirals to those with greater levels of HIV drug resistance.

FUNDING

National Institutes of Health.

Brief Report: Assessing the Association Between Changing NRTIs When Initiating Second-Line ART and Treatment Outcomes

BACKGROUND

After first-line antiretroviral therapy failure, the importance of change in nucleoside reverse transcriptase inhibitor (NRTI) in second line is uncertain due to the high potency of protease inhibitors used in second line.

SETTING

We used clinical data from 6290 adult patients in South Africa and Zambia from the International Epidemiologic Databases to Evaluate AIDS (IeDEA) Southern Africa cohort.

METHODS

We included patients who initiated on standard first-line antiretroviral therapy and had evidence of first-line failure. We used propensity score-adjusted Cox proportional-hazards models to evaluate the impact of change in NRTI on second-line failure compared with remaining on the same NRTI in second line. In South Africa, where viral load monitoring was available, treatment failure was defined as 2 consecutive viral loads >1000 copies/mL. In Zambia, it was defined as 2 consecutive CD4 counts <100 cells/mm.

RESULTS

Among patients in South Africa initiated on zidovudine (AZT), the adjusted hazard ratio for second-line virologic failure was 0.25 (95% confidence interval: 0.11 to 0.57) for those switching to tenofovir (TDF) vs. remaining on AZT. Among patients in South Africa initiated on TDF, switching to AZT in second line was associated with reduced second-line failure (adjusted hazard ratio = 0.35 [95% confidence interval: 0.13 to 0.96]). In Zambia, where viral load monitoring was not available, results were less conclusive.

CONCLUSIONS

Changing NRTI in second line was associated with better clinical outcomes in South Africa. Additional clinical trial research regarding second-line NRTI choices for patients initiated on TDF or with contraindications to specific NRTIs is needed.

Rapid accumulation of HIV-1 thymidine analogue mutations and phenotypic impact following prolonged viral failure on zidovudine-based first-line ART in sub-Saharan Africa

Background: Lack of viral load monitoring of ART is known to be associated with slower switch from a failing regimen and thereby higher prevalence of MDR HIV-1. Many countries have continued to use thymidine analogue drugs despite recommendations to use tenofovir in combination with a cytosine analogue and NNRTI as first-line ART. The effect of accumulated thymidine analogue mutations (TAMs) on phenotypic resistance over time has been poorly characterized in the African setting.

Patients and methods: A retrospective analysis of individuals with ongoing viral failure between weeks 48 and 96 in the NORA (Nevirapine OR Abacavir) study was conducted. We analysed 36 genotype pairs from weeks 48 and 96 of first-line ART (14 treated with zidovudine/lamivudine/nevirapine and 22 treated with zidovudine/lamivudine/abacavir). Phenotypic drug resistance was assessed using the Antivirogram assay (v. 2.5.01, Janssen Diagnostics).

Results: At 96 weeks, extensive TAMs (≥3 mutations) were present in 50% and 73% of nevirapine- and abacavir-treated patients, respectively. The mean (SE) number of TAMs accumulating between week 48 and week 96 was 1.50 (0.37) in nevirapine-treated participants and 1.82 (0.26) in abacavir-treated participants. Overall, zidovudine susceptibility of viruses was reduced between week 48 [geometric mean fold change (FC) 1.3] and week 96 (3.4, P = 0.01). There was a small reduction in tenofovir susceptibility (FC 0.7 and 1.0, respectively, P = 0.18).

Conclusions: Ongoing viral failure with zidovudine-containing first-line ART is associated with rapidly increasing drug resistance that could be mitigated with effective viral load monitoring.

Evolution of gag and gp41 in Patients Receiving Ritonavir-Boosted Protease Inhibitors

Several groups have proposed that genotypic determinants in gag and the gp41 cytoplasmic domain (gp41-CD) reduce protease inhibitor (PI) susceptibility without PI-resistance mutations in protease. However, no gag and gp41-CD mutations definitively responsible for reduced PI susceptibility have been identified in individuals with virological failure (VF) while receiving a boosted PI (PI/r)-containing regimen. To identify gag and gp41 mutations under selective PI pressure, we sequenced gag and/or gp41 in 61 individuals with VF on a PI/r (n = 40) or NNRTI (n = 20) containing regimen. We quantified nonsynonymous and synonymous changes in both genes and identified sites exhibiting signal for directional or diversifying selection. We also used published gag and gp41 polymorphism data to highlight mutations displaying a high selection index, defined as changing from a conserved to an uncommon amino acid. Many amino acid mutations developed in gag and in gp41-CD in both the PI- and NNRTI-treated groups. However, in neither gene, were there discernable differences between the two groups in overall numbers of mutations, mutations displaying evidence of diversifying or directional selection, or mutations with a high selection index. If gag and/or gp41 encode PI-resistance mutations, they may not be confined to consistent mutations at a few sites.

Optimal antiretroviral therapy adherence as evaluated by CASE index score tool is associated with virological suppression in HIV-infected adults in Dakar, Senegal

OBJECTIVE

To determine the prevalence and factors associated with optimal antiretroviral therapy (ART) adherence and virological failure (VLF) among HIV-infected adults enrolled in the national ART programme at the teaching hospital of Fann, Dakar, Senegal.

METHODS

Cross-sectional study from 1 September 2013 to 30 January 2014.

OUTCOMES

(1) optimal ART adherence by the Center for Adherence Support Evaluation (CASE) Index Score (>10) and (2) VLF (HIV RNA > 1000 copies/ml). Diagnostic accuracy of CASE Index Score assessed using sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV) and corresponding 95% confidence intervals (CIs). Multivariate logistic regression analysis was performed to identify independent factors associated with optimal adherence and VLF.

RESULTS

Of 98 HIV-infected patients on ART, 68% were female. The median (IQR) age was 42 (20-50) years. A total of 57 of 98 (60%) were on ART more than 3 years, and majority (88%) were on NNRTI-based first-line ART regimen. A total of 79 of 98 (80%) patients reported optimal ART adherence, and only five of 84 (5.9%) had documented VLF. Patients with VLF were significantly more likely to have suboptimal ART adherence (17.7% vs. 2.9%; P = 0.02). CASE Index Score showed the best trade-off in Se (78.9%, 95% CI: 54.4-93.9%), Sp (20.0%, 95% CI: 11.1-31.7), PPV (22.4, 95% CI: 13.1-34.2%) and NPV (76.5%, 95% CI: 50.1-93.2), when used VLF threshold of HIV RNA >50 copies/ml. Factors independently associated with VLF were CASE Index Score <10 ([aOR] = 13.0, 95% CI: 1.1-147.9; P = 0.04) and being a boosted PI-based ART regimen ([aOR] = 27.0, 95% CI: 2.4-309.4; P = 0.008).

CONCLUSIONS

Optimal ART adherence is achievable in a high proportion of HIV-infected adults in this study population. CASE Index Score was independently associated with virological outcomes, supporting usefulness of this low-cost ART adherence monitoring tool in this setting.

HIV Prevention and Treatment: The Evolving Role of the Emergency Department

Historically, the role of the emergency physician in HIV care has been constrained to treating sick patients with opportunistic infections and postexposure prophylaxis for occupational exposures. However, advances in HIV care have led to medications that have substantially fewer issues with toxicity and resistance, opening up an exciting new opportunity for emergency physicians to participate in treating the HIV virus itself. With this new role, it is crucial that emergency physicians be familiar with the advances in testing and medications for HIV prevention and treatment. To our knowledge, to date there has not yet been an article addressing this expansion of practice. We have compiled a summary of what the emergency physician needs to know, including misconceptions associated with antiretroviral therapy, medication complexity, toxicity, resistance, and usability. Additionally, we review potential indications for prescribing these drugs in the emergency department, including the role of the emergency physician in postexposure prophylaxis, preexposure prophylaxis, and treatment of acute HIV, as well as how emergency physicians can engage with chronic HIV infection.

Marginal Structural Models to Assess Delays in Second-Line HIV Treatment Initiation in South Africa

Background

South African HIV treatment guidelines call for patients who fail first-line antiretroviral therapy (ART) to be switched to second-line ART, yet logistical issues, clinician decisions and patient preferences make delay in switching to second-line likely. We explore the impact of delaying second-line ART after first-line treatment failure on rates of death and virologic failure.

Methods

We include patients with documented virologic failure on first-line ART from an observational cohort of 9 South African clinics. We explored predictors of delayed second-line switch and used marginal structural models to analyze rates of death following first-line failure by categorical time to switch to second-line. Cox proportional hazards models were used to examine virologic failure on second-line ART among patients who switched to second-line.

Results

5895 patients failed first-line ART, and 63% switched to second-line. Among patients who switched, median time to switch was 3.4 months (IQR: 1.1–8.7 months). Longer time to switch was associated with higher CD4 counts, lower viral loads and more missed visits prior to first-line failure. Worse outcomes were associated with delay in second-line switch among patients with a peak CD4 count on first-line treatment ≤100 cells/mm³. Among these patients, marginal structural models showed increased risk of death (adjusted HR for switch in 6–12 months vs. 0–1.5 months = 1.47 (95% CI: 0.94–2.29), and Cox models showed increased rates of second-line virologic failure despite the presence of survivor bias (adjusted HR for switch in 3–6 months vs. 0–1.5 months = 2.13 (95% CI: 1.01–4.47)).

Conclusions

Even small delays in switch to second-line ART were associated with increased death and second-line failure among patients with low CD4 counts on first-line. There is opportunity for healthcare providers to switch patients to second-line more quickly.

Time to Viremia for Patients Taking their First Antiretroviral Regimen and the Subsequent Resistance Profiles

BACKGROUND

The resistance profiles for patients on first-line antiretroviral therapy (ART) regimens after viremia have not been well studied in community clinic settings in the modern treatment era.

OBJECTIVE

To determine time to viremia and the ART resistance profiles of viremic patients.

METHODS

HIV-positive patients aged ≥16 years initiating a three-drug regimen were retrospectively identified from 01/01/06 to 12/31/12. The regimens were a backbone of two nucleoside reverse transcriptase inhibitors (NRTIs) and a third agent: a protease inhibitor (PI), non-nucleoside reverse transcriptase inhibitor (NNRTI), or an integrase inhibitor (II). Time to viremia was compared using a proportional hazards model, adjusting for demographic and clinical factors. Resistance profiles were described in those with baseline and follow-up genotypes.

RESULTS

For 653 patients, distribution of third-agent use and viremia was: 244 (37%) on PIs with 80 viremia, 364 (56%) on NNRTIs with 84 viremia, and 45 (7%) on II with 11 viremia. Only for NNRTIs, time to viremia was longer than PIs (p = 0.04) for patients with a CD4 count ≥200 cells/mm(3). Of the 175 with viremia, 143 (82%) had baseline and 37 (21%) had follow-up genotype. Upon viremia, emerging ART resistance was rare. One new NNRTI (Y181C) mutation was identified and three patients taking PI-based regimens developed NRTI mutations (M184 V, M184I, and T215Y).

CONCLUSIONS

Time to viremia for NNRTIs was longer than PIs. With viremia, ART resistance rarely developed without PI or II mutations, but with a few NRTI mutations in those taking PI-based regimens, and NNRTI mutations in those taking NNRTI-based regimens.

HIV-1 Drug Resistance and Second-Line Treatment in Children Randomized to Switch at Low Versus Higher RNA Thresholds

BACKGROUND

The PENPACT-1 trial compared virologic thresholds to determine when to switch to second-line antiretroviral therapy (ART). Using PENPACT-1 data, we aimed to describe HIV-1 drug resistance accumulation on first-line ART by virologic threshold.

METHODS

PENPACT-1 had a 2 × 2 factorial design, randomizing HIV-infected children to start protease inhibitor (PI) versus nonnucleoside reverse transcriptase inhibitor (NNRTI)-based ART, and switch at a 1000 copies/mL versus 30,000 copies/mL threshold. Switch criteria were not achieving the threshold by week 24, confirmed rebound above the threshold thereafter, or Center for Disease Control and Prevention stage C event. Resistance tests were performed on samples ≥1000 copies/mL before switch, resuppression, and at 4-years/trial end.

RESULTS

Sixty-seven children started PI-based ART and were randomized to switch at 1000 copies/mL (PI-1000), 64 PIs and 30,000 copies/mL (PI-30,000), 67 NNRTIs and 1000 copies/mL (NNRTI-1000), and 65 NNRTI and 30,000 copies/mL (NNRTI-30,000). Ninety-four (36%) children reached the 1000 copies/mL switch criteria during 5-year follow-up. In 30,000 copies/mL threshold arms, median time from 1000 to 30,000 copies/mL switch criteria was 58 (PI) versus 80 (NNRTI) weeks (P = 0.81). In NNRTI-30,000, more nucleoside reverse transcriptase inhibitor (NRTI) resistance mutations accumulated than other groups. NNRTI mutations were selected before switching at 1000 copies/mL (23% NNRTI-1000, 27% NNRTI-30,000). Sixty-two children started abacavir + lamivudine, 166 lamivudine + zidovudine or stavudine, and 35 other NRTIs. The abacavir + lamivudine group acquired fewest NRTI mutations. Of 60 switched to second-line, 79% PI-1000, 63% PI-30,000, 64% NNRTI-1000, and 100% NNRTI-30,000 were <400 copies/mL 24 weeks later.

CONCLUSIONS

Children on first-line NNRTI-based ART who were randomized to switch at a higher virologic threshold developed the most resistance, yet resuppressed on second-line. An abacavir + lamivudine NRTI combination seemed protective against development of NRTI resistance.

First-line antiretroviral therapy with nevirapine versus lopinavir-ritonavir based regimens in a resource-limited setting

Objective:

To compare WHO first-line antiretroviral therapy (ART) with nonnucleoside reverse transcriptase inhibitors (NNRTI)-based regimen with a boosted protease inhibitor (bPI) regimen in a resource-limited setting regarding treatment outcome and emergence of drug resistance mutations (DRMs).

Methods:

Treatment-naive adults were randomized to nevirapine (NVP) or ritonavir-boosted lopinavir (LPV/r) regimens each in combination with tenofovir (TDF)/emtricitabine (FTC) or zidovudine (ZDV)/lamivudine (3TC). Primary endpoint was the incidence of therapeutical (clinical and/or virologic) failure at week 48 with follow-up till week 96.

Results:

Four hundred and twenty-five patients (120 men; 305 women) received at least one dose of the study drug. mITT analysis showed no difference in proportion of therapeutical failure between treatment arms [67/209 (32%) in NVP vs. 63/216 (29%) LPV/r at week 48 (P = 0.53); 88/209 (42%) in NVP vs. 83/216 (38%) in LPV/r at week 96 (P = 0.49)]. Per-protocol analysis demonstrated significantly more virologic failure with NVP than with LPV/r regimens [at week 48: 19/167 (11%) vs. 7/166 (4%), P = 0.014; at week 96: 27/158 (17%) vs. 13/159 (8%), P =  0.019)]. Drug resistance mutations to NNRTI were detected in 19 out of 22 (86.3%) and dual-class resistance to nucleoside reverse transcriptase inhibitor (NRTI) and NNRTI in 15 out of 27 (68.2%) of NVP failing patients. K65R mutation was present in seven out of 14 patients failing NVP-TDF/FTC regimen. No major protease inhibitor-DRM was detected among LPV/r failing patients. Discontinuation for adverse events was similar between treatment groups.

Conclusion:

In resource-limited settings, first-line NNRTI-NRTI regimen as compared with bPI-based regimen provides similar outcome but is associated with a significantly higher number of virologic failure and resistance mutations in both classes that jeopardize future options for second-line therapy.

Adherence as a predictor of the development of class-specific resistance mutations: the Swiss HIV Cohort Study

Background

Non-adherence is one of the strongest predictors of therapeutic failure in HIV-positive patients. Virologic failure with subsequent emergence of resistance reduces future treatment options and long-term clinical success.

Methods

Prospective observational cohort study including patients starting new class of antiretroviral therapy (ART) between 2003 and 2010. Participants were naïve to ART class and completed ≥1 adherence questionnaire prior to resistance testing. Outcomes were development of any IAS-USA, class-specific, or M184V mutations. Associations between adherence and resistance were estimated using logistic regression models stratified by ART class.

Results

Of 314 included individuals, 162 started NNRTI and 152 a PI/r regimen. Adherence was similar between groups with 85% reporting adherence ≥95%. Number of new mutations increased with increasing non-adherence. In NNRTI group, multivariable models indicated a significant linear association in odds of developing IAS-USA (odds ratio (OR) 1.66, 95% confidence interval (CI): 1.04-2.67) or class-specific (OR 1.65, 95% CI: 1.00-2.70) mutations. Levels of drug resistance were considerably lower in PI/r group and adherence was only significantly associated with M184V mutations (OR 8.38, 95% CI: 1.26-55.70). Adherence was significantly associated with HIV RNA in PI/r but not NNRTI regimens.

Conclusion

Therapies containing PI/r appear more forgiving to incomplete adherence compared with NNRTI regimens, which allow higher levels of resistance, even with adherence above 95%. However, in failing PI/r regimens good adherence may prevent accumulation of further resistance mutations and therefore help to preserve future drug options. In contrast, adherence levels have little impact on NNRTI treatments once the first mutations have emerged.