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Emergence of Drug Resistance in HIV Type 1-Infected Patients after Receipt of First-Line Highly Active Antiretroviral Therapy: A Systematic Review of Clinical Trials

  1. Ravindra Gupta1,
  2. Andrew Hill2,
  3. Anthony W. Sawyer4, and
  4. Deenan Pillay1,3
  1. 1Division of Infection and Immunity, University College London, London
  2. 2Pharmacology Research Laboratories, University of Liverpool, Liverpool
  3. 3Centre for Infectious, Health Protection Agency, United Kingdom
  4. 4SEARCH, Thai Red Cross AIDS Research Centre, Bangkok, Thailand
  1. Reprints or correspondence: Dr. Ravindra Gupta, University College London, Windeyer Bldg., 46 Cleveland St., London W1T 4JF, United Kingdom (Rgupta2{at}nhs.net).
 
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Abstract

Background. Resistance to antiretroviral combination therapy is associated with increased mortality. Understanding the relative risks of emerging resistance to first-line therapy is of importance for both resource-rich and resource-poor settings.

Methods. We undertook an overview of clinical trials of adults receiving first-line highly active antiretroviral therapy (HAART), which consisted of dual nucleoside reverse-transcriptase inhibitors (NRTIs) combined with a third agent (either a nonnucleoside reverse-transcriptase inhibitor [NNRTI] or a ritonavir-boosted protease inhibitor [bPI]). The primary outcome measures were incidences of mutations conferring resistance to key drugs (NRTIs, NNRTIs, or bPIs) per trial at week 48. For meta-analysis, inverse-variance weighting was used to create estimates of overall incidences per group, with exact 95% confidence intervals (95% CIs).

Results. The study included 20 clinical trials that comprised 30 treatment arms and 7970 patients. Virologic failure at 48 weeks occurred in 4.9% (95% CI, 3.9%–6.1%) of NNRTI recipients, compared with 5.3% (95% CI, 4.4%–6.4%; P=.50) of bPI recipients. Of failures that were successfully genotyped, the M184V mutation in the HIV reverse transcriptase (lamivudine resistance) occurred in 35.3% (95% CI, 29.3%–41.6%) of patients who started NNRTI-based HAART, compared with 21.0% (95% CI, 14.4%–28.8%; P<.001) for those who received a bPI. For the K65R mutation in the HIV reverse transcriptase (multinucleoside resistance), incidences were 5.3% (95% CI, 2.4%–9.9%) and 0.0% (95% CI, 0.0%–3.6%; P=.01), respectively, in patients treated with non-zidovudine-containing regimens. Resistance to the third agent (an NNRTI or PI) occurred in 53% (95% CI, 46%–60%) and 0.9% (95% CI, 0.0%–6.2%; P<.001) of such patients, respectively.

Conclusions. Initial therapy with bPI-based regimens resulted in less resistance within and across drug classes. This finding is of particular significance for the developing world, where rates of resistance to NRTIs and NNRTIs at 48 weeks are much higher than has been seen in both cohorts and clinical trials in well-resourced countries.

HAART, consisting of combinations of 3 antiretroviral drugs from 2 or 3 classes, has reduced morbidity and mortality due to HIV infection since its introduction into clinical use [1]. Current standard-of-care HAART consists of 2 nucleoside reverse-transcriptase inhibitors (NRTIs) or nucleotide reverse-transcriptase inhibitors plus a third agent (either a non-NRTI [NNRTI] or ritonavir-boosted protease inhibitor [bPI]) [2–4]. Other combinations, such as unboosted protease inhibitors (PIs), triple-NRTI-containing regimens, or PI-NNRTI combinations are no longer recommended in resource-rich regions, either because of suboptimal virologic outcomes or insufficient evidence of efficacy [5]. However, triple-NRTI regimens continue to be cited as possible first-line regimens in resource-limited settings by the World Health Organization [4].

Emergence of drug resistance is associated with increased mortality in patients who receive first-line HAART, with NNRTI resistance representing the highest risk [6, 7]. Conservative estimates show that ∼10% of patients who commence HAART develop some form of genotypic drug resistance after 2 years, and almost 30% of patients develop viral failure with ⩾1 major resistance mutation ⩽6 years after starting HAART [8], representing a threat to the control of transmitted multiple-class resistance [9].

Previous studies have suggested that genotypic resistance is detected more frequently after failure of NNRTI-based HAART than after failure of bPI-based HAART [5, 8, 10, 11]. However, these studies did not include large numbers of patients taking more-modern, coformulated NRTI and bPI combinations, and they could not draw conclusions regarding the impact of NRTI backbones because of the limited sample sizes.

We conducted a comprehensive and standardized meta-analysis of clinical trials of HAART to compare the resistance profiles after virologic failure of first-line HAART that contained NNRTIs versus HAART that contained bPIs. By using the most recent trials data in a standardized analysis, we aimed to generate more-reliable estimates of the incidence of emergence of genotypic resistance during first-line therapies currently in clinical use.

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Methods

Search strategy. In November 2007, we searched the Medline electronic database via PubMed for articles published during the period January 1994 through November 2007, as well as abstracts (for the period 1999–2007) from the following conferences: Conference on Retroviruses and Opportunistic Infections, Interscience Conference on Antimicrobial Agents and Chemotherapy, International AIDS Society, European AIDS Clinical Society, International Congress on Drug Therapy in HIV Infection, and the International Drug Resistance Workshop. We constructed the following 2 search strings to identify as many relevant studies as possible: (1) HAART (“highly active antiretroviral therapy AND resistance AND naive” and “antiretroviral AND resistance AND naive”) and (2) HIV (“human immunodeficiency virus OR HIV AND naïve”). Each string was then combined with terms for the following currently US Food and Drug Administration-licensed antiretrovirals [12] with an “OR” operator separating the terms: zidovudine, stavudine, abacavir, tenofovir, nevirapine, efavirenz, lopinavir, saquinavir, fosamprenavir, amprenavir, atazanavir, and darunavir.

Two independent reviewers judged the eligibility of the search results on the basis of inclusion and exclusion criteria (figure 1), and full-length articles that met the criteria were subsequently reviewed. In the event of a disagreement, a third investigator made the final decision. Reference lists from included studies were used to identify additional publications. The trial coordinators or study authors were contacted, as necessary, to obtain additional data, if sources identified from the databases were missing key data.

Figure 1
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Figure 1

Inclusion criteria, exclusion criteria, and criteria for virologic failure. CDC, Centers for Disease Control and Prevention; ddC, zalcitabine; NNRTI, nonnucleoside reverse-transcriptase inhibitor; NRTI, nucleoside reverse-transcriptase inhibitor; PI, protease inhibitor; VL, viral load.

Data extraction. Two independent reviewers extracted data from the literature identified by the search strategy. We extracted data on the study's name and authors, antiretroviral combinations used, year of publication or presentation, study design, characteristics of participants, baseline median and/or mean CD4 cell count and log10 viral load, viral suppression rates (i.e., viral load <50 and <400 copies/mL at weeks 48 and 96) in the intention-to-treat (ITT) population (i.e., all randomized patients who received ⩾1 dose of the study drug), increases in the CD4 cell count, definition of virologic failure, number of virologic failures, and number of genotypes successfully determined for patients who experienced virologic failures. The importance of the proportion of individuals who achieved viral loads of <400 copies/mL lies in the fact that genotype determination is frequently unsuccessful for patients with viral loads less than this threshold.

We subsequently collected data on the number of patients with virologic failure and genotypic resistance data in the following categories: patients infected with wild-type virus or who experienced no change from the baseline genotype; patients with treatment-emergent, major HIV reverse-transcriptase mutations (at amino acid positions 100, 103, 106, 108, 181, 188, 190, and 225; hereafter referred to as “NNRTI mutations”); patients with treatment-emergent major HIV protease mutations (at amino acid positions 20, 30, 33, 46, 48, 50, 54, 82, 84, and 90; hereafter referred to as “PI mutations”) [13]; and patients with the following 3 measures of NRTI resistance: (1) the M184V mutation in the HIV reverse transcriptase, (2) at least 1 thymidine analogue mutation (TAM; M41L, D67N, K70R, L210W, T215Y/F, or K219Q/E mutation in the HIV reverse transcriptase), and (3) the K65R mutation in the HIV reverse transcriptase. Definitions of virologic failure varied among the studies and are categorized in figure 1.

Statistical methods. Estimates of group mean values (and SEs) of baseline variables (age, sex, CD4 cell count, and log10 viral load) were calculated using inverse-variance weights. These were compared between groups using Student's t test. The main analysis compared rates of specific resistance mutations across treatment groups (NNRTI-based regimens vs. bPI regimens): the number of patients with M184V, at least 1 TAM, and ⩾1 major NNRTI or PI mutation (as defined by the International AIDS Society-USA) per treatment arm at week 48. The 2 main populations for analysis were (1) genotype analysis (i.e., the total number of patients with genotypic resistance data available after they experienced virologic failure) and (2) ITT analysis (i.e., the total number of patients who had been randomized).

The incidence of different genotypes was calculated for individual trials using the 2 populations. If only a subset of viruses obtained from patients with virologic failure were sequenced, the rates of genotype analysis were calculated, but such studies were not included in the ITT analysis. Next, to make group comparisons between NNRTI-based and PI-based regimens, we used inverse-variance weighting and a calculation of effective sample size to create robust estimates of prevalence of major PI mutations, major NNRTI mutations, TAMs, the M184I/V mutation, and the K65R mutation, accompanied by exact 95% CIs [14], for each of the groups. With this method, the 95% confidence limits were produced for each of the individual studies. The “exact” interval (also called the “Clopper-Pearson interval”) was used instead of the normal approximation, because the latter can yield confidence limits of <0% or >100%. The contribution of each study (bPI studies and NNRTI studies) to the group estimate was weighted by a factor of 1/variance. Finally, the 95% CI for the group estimate was determined using the concept of effective sample size.

It was important to ensure that resistance comparisons were not biased; therefore, we only analyzed resistance mutations and particular regimens that were known to be related. For example, we analyzed rates of K65R mutation by excluding studies from the analyses that involved use of zidovudine as the NRTI; this is because of well-established data regarding protection against K65R mutations associated with use of zidovudine. Similarly, we examined the prevalence of treatment-emergent TAMs only in patients exposed to zidovudine or stavudine (i.e., thymidine analogues).

We performed additional analyses using the same statistical methodology, to examine the impact of NRTI backbone on the development of resistance. We compared the newer NRTIs (abacavir or tenofovir) to the older agents (stavudine or zidovudine) in terms of resistance rates to lamivudine and NNRTIs. Statistical analyses were performed using Excel (Microsoft).

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Results

Of the 1782 abstracts identified through the search strategy, 123 full-text articles or posters were obtained and further assessed; the other 1659 abstracts were excluded because they did not meet eligibility criteria. Of the full-text articles obtained, 35 were selected for inclusion (figure 2). Common reasons for exclusion were that the articles described cohort studies (n=12), studied nonrecommended regimens or dosages (n=18), or involved use of a triple-nucleoside analogue combination (n=10). There were 20 clinical trials, and all but 1 were randomized trials with a control arm. Fifteen trials were open label, and 5 were double-blind. It was possible for there to be >1 publication for a particular study if week 48 and week 96 results or resistance data were separately reported.

Figure 2
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Figure 2

Flow diagram of reviewed literature. PK, pharmacokinetic.

Eight studies of NNRTI-based treatment (with 4212 patients) contained virologic failure and resistance data up to week 48, and 4 studies (with 1457 patients) included such data up to week 96. Ten studies of bPI-based treatment (with 3063 patients) provided virologic failure and resistance data up to week 48, and 4 studies (with 884 patients) provided such data up to week 96. In total, 4560 patients had received NNRTI-based regimens, and 3410 patients had received bPI-based regimens.

The included studies were conducted and presented or published during the period 2001–2007. The baseline characteristics of patients in these studies are summarized in table 1, which contains 48-week data for HIV RNA levels and CD4 cell responses, as available, although some studies provided 96-week and not 48-week data (e.g., AIDS Clinical Trials Group [ACTG] 5142). The mean baseline CD4 cell count for patients in studies of NNRTI- and bPI-based regimens was 250 and 202 cells/μL, respectively (P=.52); the mean log10 viral load was 4.89 and 4.85 log10 copies/mL, respectively (P=.85); mean ages were 35.5 and 37.3 years (P=.30), respectively; and the percentage of female trial participants was 22.7% and 22.4%, respectively (P=.98).

Figure 3
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Figure 3

Virologic failures in studies of nonnucleoside reverse-transcriptase inhibitor (NNRTI) and ritonavir-boosted protease inhibitor (bPI) HAART.

Figure 4
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Figure 4

Week 48 incidence of genotypic resistance at virologic failure. A, Intention-to-treat analysis. B, Genotype analysis. NNRTI, nonnucleoside reverse-transcriptase inhibitor; PI, protease inhibitor; TAM, thymidine analogue mutation.

Figure 5
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Figure 5

Week 96 incidence of genotypic resistance at virologic failure. A, Intention-to-treat analysis). B, Genotype analysis. NNRTI, nonnucleoside reverse-transcriptase inhibitor; PI, protease inhibitor; TAM, thymidine analogue mutation.

Table 1
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Table 1

Characteristics of the study and intention-to-treat (ITT) populations.

The clinical trial analysis included 30 independent treatment arms, comprising 16 combinations of antiretrovirals with week 48 or week 96 data on genotypic resistance after failure of the first-line HAART regimen. The distribution of NRTI use is summarized in table 2. It appears that bPI studies were more likely to use newer NRTIs, such as tenofovir and abacavir, compared with NNRTI studies. The percentage of patients in the NNRTI and bPI groups treated with thymidine analogue-containing regimens was 60.8% and 15.4%, respectively.

Table 2
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Table 2

Nucleoside reverse-transcriptase inhibitor (NRTI) backbone distribution and pooled resistance data at week 48 for ritonavir-boosted protease inhibitor (PI)- and non-NRTI (NNRTI)-based HAART regimens.

We reported virologic efficacy as percentages of randomized patients who received at least 1 dose of the study drug with a viral load <50 or <400 copies/mL, with missing values and switches counted as failures (table 1). We did not attempt to compare overall efficacy rates because of interstudy variability in the viral load cutoff values used, because some studies permitted switches in the regimen without counting the need for a switch as a failure, and because some studies excluded patients with baseline resistance from the efficacy analysis. A viral load threshold of 50 copies/mL (the limit of detection by current assays) is the standard used to reliably compare regimens, although we also reported rates for viral loads <400 copies/mL, because this value is commonly reported and is nearer to the lower limit of detection used for resistance testing (i.e., 1000 copies/mL). With use of a threshold of 50 copies/mL, virologic efficacy rates in NNRTI-based regimens ranged from 67% in the abacavir-lamivudine-efavirenz arm of CNA 30021 [20] to 80% in the stavudine-lamivudine-efavirenz arm of GS903 [15] at week 48. For bPI-based regimens, rates ranged from 65% in the tenofovir-emtricitabine-saquinavir-ritonavir arm of the Gemini study [30] to 67% in the abacavir-lamivudine-fosamprenavir-ritonavir and abacavir-lamivudine-lopinavir-ritonavir arms of the KLEAN study [31].

Virologic failure (using definition 2 from figure 1) at week 48 occurred in 4.9% (95% CI, 3.9%–6.1%) of patients receiving 2 NRTIs and an NNRTI and 5.3% (95% CI, 4.4%–6.4%; P=.50) of those treated with 2 NRTIs and a bPI (figure 3); a weighted comparison was not undertaken for week 96 data because of excessive variability in the definition of virologic failure in the few studies that contributed to this dataset. The percentages of viruses that were successfully genotyped for patients with virologic failure at week 48 were 80% for studies of NNRTI-based regimens and 83% for studies of bPI-based regimens. Very few studies determined the genotypes at baseline for all patients, and none excluded patients with baseline resistance from the resistance analysis.

The results of analysis for specific resistance mutations at week 48 are illustrated in figures 4 and 5 for both ITT and genotype analysis populations. For genotype analysis, the prevalence of the M184V mutation (which confer high-level resistance to lamivudine) at the time of virologic failure was 35.3% (95% CI, 29.3%–41.6%) in patients who started first-line NNRTI treatment, compared with 21.0% (95% CI, 14.4%–28.8%; P<.001) for those who received bPI-based HAART. When considering patients at risk of developing multiple-nucleoside resistance (i.e., resistance to tenofovir, abacavir, and didanosine) associated with the K65R mutation, we found that NNRTI-based regimens resulted in higher rates of such resistance: 5.3% (95% CI, 2.4%–9.9%) versus 0.0% (95% CI, 0.0%–3.6%; P=.01). The percentage of patients with ⩾1 TAM (which confers resistance to zidovudine and stavudine) was 1.5% (95% CI, 0.3%–4.1%) and 0.6% (95% CI, 0.0%–5.8%; P=.627), respectively. Resistance to a third agent (either an NNRTI or a PI) occurred in 53% (95% CI, 46.0%–60.0%) and 0.9% (95% CI, 0.0%–6.2%; P<.001) of patients, respectively, at virologic failure at 48 weeks. The statistically significant associations held for week 96 data as well (data not shown).

We found that use of newer NRTIs (tenofovir and abacavir) in combination with an NNRTI was not associated with lower rates of NNRTI resistance, compared with use of older thymidine analogues (zidovudine or stavudine); the rates were 35.8% (95% CI, 25.2%–47.5%) and 35.1% (95% CI, 28.2%–42.5%; P=.91) respectively. The rate of lamivudine resistance did not differ either (54.0% [95% CI, 42.2%–65.5%] vs. 52.6% [95% CI, 44.1%–60.9%]; P=.82). The low number of bPI-treated individuals who received older NRTIs precluded a similar analysis for this group.

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Discussion

Minimizing drug resistance to HAART is important. First, it maximizes the opportunity for successful second-line and subsequent therapies after viral rebound during first-line treatment; second, it limits the transmission of drug-resistant viruses. In this analysis of clinical trials involving nearly 8000 patients, the prevalence of M184V and K65R mutations at the time of virologic failure is significantly higher in patients using first-line NNRTI versus bPI-based HAART. Resistance to the third agent is also much more prevalent at time of failure in studies of NNRTI regimens, at ∼50% of patients for whom genotypes were determined both at weeks 48 and 96, with virtually no PI resistance seen over the same time period among patients for whom bPI treatment fails.

Notably, the overall prevalence of resistance in treated populations appears relatively low at present, despite virologic failure rates of up to 10% per year [8]; this was reflected in our study, which found no detectable resistance in ∼30% of all patients who experienced virologic failure. It should be borne in mind that current population genotyping methods underestimate the prevalence of resistance by up to 50%. This may be due to levels of resistance that are less than the limit of detection of currently available assays or to the presence of resistance determinants outside of the areas of the viral genome commonly sequenced for resistance detection [48–50]. Perhaps most importantly, our data from clinical trials substantially underestimate resistance rates seen in clinical practice. The UK Collaborative Cohort study reported substantially higher week 96 ITT rates of resistance to NNRTI (8% vs. 5.0%) and higher prevalence of the M184V mutation (6% vs. 2.3%) at virologic failure [8].

ACTG 5142 [29], the only randomized trial directly comparing the most commonly used NNRTI (efavirenz) and bPI (lopinavir-ritonavir), provided week 96 genotype analysis resistance data in a total of 500 patients; their results did not differ significantly from our overall week 96 estimates (figure 5). The general finding of our study that NNRTI-based regimens result in higher rates of resistance is also consistent with a meta-analysis undertaken in early 2004 by Bartlett et al. [5]. However, key data from a number of major trials were not available for their study, with data on <500 recipients of bPI regimens and no data on tenofovir recipients available for analysis. Notably, none of these cohort studies or meta-analyses were able to detect statistically significant differences in K65R-related cross-nucleoside resistance or compared newer versus older NRTI backbones.

The findings of this study are intriguing. Although the absence of PI mutations at the time of viral rebound during bPI treatment can be explained by the high genetic barrier of these drugs, this does not explain the lack of resistance to coadministered drugs—;particularly the NRTI lamivudine. We speculate that, because bPIs retain activity despite low-level emergence or preexistence of NRTI-resistant species, then such resistant species will remain suppressed. Thus, a larger proportion of failures during bPI treatment will be associated with poor adherence (in which case, there is no selective drug pressure from the NRTI component), compared with failures during NNRTI treatment. Unfortunately, assessment of adherence was not systematic across trials; therefore, we were unable to analyze its impact on virologic failure and resistance rates.

Limitations of the study include the potential for selection bias associated with the search strategy and the potential for confounding factors because this was not a randomized study. However, our results were consistent with resistance data from direct comparisons of NNRTIs versus bPIs (for example, the ACTG 5142 study). There was also a general lack of heterogeneity between trials, adding weight to the view that the statistically significant findings of this study were not significantly biased or confounded. The limited heterogeneity between genotype analysis and ITT estimates was most likely due to variation in definitions of virologic failure and thresholds for genotyping across trials.

It is important to appreciate that resistance at failure is only one factor to consider when choosing an initial HAART regimen. Coformulation, simplicity of administration, price, drug interactions (particularly with tuberculosis therapy), and toxicity and adverse events are all important considerations and will differ between patient populations. It should be borne in mind that virologic failure rates were low in both groups analyzed in this study, highlighting the excellent efficacy of all regimens studied.

No discussion of the wider context of resistance and first-line HAART can be complete without addressing the 9 million patients in resource-poor settings who required treatment based on World Health Organization guidelines by June 2006. Of these, one-third (3 million) are receiving HAART, and nearly all are using NNRTI-based regimens [51]. Unfortunately, virologic failure rates at 48 weeks in resource-poor settings are almost double those seen in the clinical trials reported in this study, with much higher rates of resistance to NNRTIs (>90%) and NRTIs (>70% for lamivudine and up to 10% for prevalences of TAMs and the K65R mutation) at the time of virologic failure [52, 53]. The markedly increased resistance rates in the developing world may be the result of less-intensive virologic monitoring, leading to prolonged viremia.

We have demonstrated that use of bPIs leads to lower rates of resistance to key components of second-line therapy—;namely, lamivudine, didanosine, tenofovir, and abacavir. Furthermore, resistance to the bPI itself occurs rarely, as opposed to NNRTIs, for which the genetic barrier to resistance is low. Therefore, the former agents may be more appropriate for use in resource-poor settings, where drug supplies are frequently erratic and where patients may continue to use failing regimens for longer periods of time. bPIs also produce greater increases in the CD4 cell count than do NNRTIs [29], and this could be important in the developing world, where HAART is initiated for patients with very low CD4 cell counts [4]. Generic bPIs are now available, and their use in first-line regimens should be assessed as part of a global public health approach to HAART.

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Acknowledgments

Financial support. British Infection Society Clinical Research Training Fellowship (R.G.), UCLH/UCL Comprehensive Biomedical Research Centre (D.P.), and Wellcome Trust (R.G.).

Potential conflicts of interest. R.G. has received travel grants from Gilead Sciences, Bristol-Myers Squibb, and Boehringer-Ingelheim. A.H. has received consultancy fees from Tibotec. D.P. has acted as a consultant for Bristol-Myers Squibb, Johnson & Johnson, Boehringer-Ingelheim, Roche, and Gilead Sciences. A.W.S.: no conflicts.

  • Received March 4, 2008.
  • Accepted April 1, 2008.
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  1. Clin Infect Dis. (2008) 47 (5): 712-722. doi: 10.1086/590943
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