Surveillance of HIV antiretroviral drug resistance in treated individuals in England: 1998–2000

Paul Scott1, Eve Arnold2, Barry Evans3, Anton Pozniak4, Graeme Moyle4, Mohsen Shahmenesh5, David White6, Jane Shirley1, Patricia Cane1 and Deenan Pillay1,*

1 PHLS Antiviral Susceptibility Reference Unit, Birmingham; 2 Statistics Unit and 3 HIV Division, Communicable Disease Surveillance Centre, Colindale, London; 4 Department of HIV and GUM, Chelsea and Westminster Hospital, London; 5 University Hospital NHS Trust Birmingham, Birmingham; 6 Department of Sexual Medicine, Birmingham Heartlands Hospital, Birmingham, UK

Received 20 May 2003; returned 24 June 2003; revised 7 November 2003; accepted 8 December 2003


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Objectives: To establish a surveillance programme for HIV drug resistance within the UK covering the years from 1998 to 2000, following the introduction of triple combination antiretroviral therapy.

Methods: Sentinel sites included large, medium sized and small clinical centres. Data were analysed until December 2000.

Results: Of nearly 300 samples tested, results from 91, 92 and 92 patients, respectively in 1998, 1999 and 2000, who were receiving HIV therapy with a viral load >2000 copies/mL, the majority had viruses with some degree of drug resistance. Overall, the presence of any resistance increased between 1998 and 1999, and fell again in 2000 (69% versus 88% versus 55%). However, major differences were observed between drug classes, such that non-nucleoside analogue reverse transcriptase inhibitor (NNRTI) resistance rose dramatically over the period studied. We show that this correlated with increased NNRTI prescribing. Furthermore, an overall increase in prevalence of viruses with resistance to one or more drugs within all three available classes was observed. A higher prevalence of drug resistance was observed in patients from smaller clinical centres.

Conclusions: This is the first such sentinel surveillance dataset from the UK, and is unique in correlating these data with national antiretroviral prescribing patterns. Our findings are relevant to the increased transmission of HIV drug resistance observed over this period.

Keywords: HIV-1, resistance, surveillance


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
The use of combination antiretroviral drug therapy for treatment of HIV-1 infection has had a dramatic impact in reducing the incidence of AIDS and HIV-related death within Europe and the USA.1,2 Currently, some 16 drugs are licenced within the UK, falling into the following classes: nucleoside analogue reverse transcriptase inhibitors (NRTIs), non-nucleoside analogue reverse transcriptase inhibitors (NNRTIs) and protease inhibitors (PIs). The latter were introduced in 1996/7, becoming a key component of triple therapy, and NNRTIs were introduced 2 years later. The efficacy of these drugs used in combination to suppress viral replication, and thus prevent disease progression, is measured by plasma viral RNA quantification, and the virological goal of therapy is therefore to reduce viraemia to undetectable levels (currently at 50 copies RNA/mL).35 Virus eradication is not possible with currently available therapies, as a result of the existence of long-lived cellular reservoirs of virus.5 Thus, viral rebound during therapy remains a risk. The most important single factor determining such rebound is poor drug adherence, although many other factors may also be involved.3,4

Such rebound of virus is often associated with the emergence of drug-resistant virus in plasma. This is measured by phenotypic or genotypic methods, the latter involving sequencing of the viral reverse transcriptase and protease genes to identify the presence of key mutations known to confer, either alone or in conjunction with others, reduced drug susceptibility to one or more drugs.6,7 Clearly, the major clinical impact of such resistance is that subsequent therapies with alternate drugs may be compromised. Thus, HIV resistance testing has become routine practice for patients failing on therapy over the last 2–3 years.

A further consequence of drug resistance within the population of treated patients is that such viruses may be transmitted to others. Indeed, since the treated patient cohort is, by definition, growing owing to longer survival, and the number of new infections within the UK is not decreasing, it is possible that such transmission will occur. Indeed, studies in the USA and Europe demonstrate a prevalence of drug-resistant virus in new infections of up to 20% over the period 1998–2000.8,9

Although a number of studies have been undertaken to determine the prevalence and characteristics of resistance in large collections of specimens, or in particular cohorts of patients, such analyses are not informative at a population level, especially with regard to changes over time. Since routine HIV resistance testing was not widely available within the UK in 1998, we initiated a prospective study at that time to assess the prevalence of specific resistance- associated mutations within plasma virus from patients receiving therapy, with a viral load >2000 copies/mL. These were derived randomly from three different clinic population sizes (large, medium and small), over the years 1998, 1999 and 2000. We did not seek to correlate resistance with therapy. Rather, since those with detectable viral load are likely to be more infectious, they represent a population from which transmission of resistant virus could occur. Since we were concerned that antiretroviral drug use may, in part, be determined by the numbers of patients attending clinical centres, we also sampled from a variety of such centres. Thus, we have attempted to generate a dataset representative of national patterns of resistance over the time period studied, correlated with the drugs available at the time, which can then be utilized to understand some of the characteristics of transmission of HIV drug resistance.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Sample selection

Three different types of source clinics were identified, according to their size: large (one clinic caring for >2500 patients), medium (two clinics caring for >200 patients each) and small (multiple clinics caring for <50 patients each). In one specific month for each of the calendar years 1998, 1999 and 2000, 33 successive plasma samples taken for routine viral load testing conforming to the criteria below were identified for each clinic-type population for genotypic resistance testing. Thus 99 plasma samples were tested for each calendar year. This way of sampling from a population of interest may limit the validity of generalizing results from this study; however, we can see no strong reason why this set of patients would not form a representative sample.

Criteria for selection were: (a) receiving antiretroviral drug therapy, and (b) a viral load >2000 copies/mL, and selection of samples was undertaken within the local laboratory undertaking viral load determinations, rather than the clinic itself. Sequential samples conforming to these criteria were selected from samples received in the laboratory serving the particular clinics starting at the beginning of one particular month until 33 specimens had been identified. The same process was undertaken in the same month for the three successive years covered by this surveillance programme. Patient identifiers were removed before allocation for testing, and therefore we could not correlate results with therapy, or link data to particular patients. For the majority of patients selected, resistance testing was not undertaken for routine clinical care, either because such testing was yet to enter clinical protocols in those centres, or because clinicians may not have identified these patients as appropriate for testing.

Laboratory methods

Sequencing of the reverse transcriptase gene (codons 1–230) and protease gene (codons 1–99) from plasma virus was undertaken by in- house methodologies, as previously described.10 Interpretation of the generated sequence was undertaken via the Stanford website (http://hivdb.stanford.edu/), and all changes from the consensus sequence were identified. We used a modification of the Journal of the American Medical Association guidelines to allocate mutations to major or secondary categories. Thus, NRTI resistance mutations included: M41L, K43E/N, E44D/A, A62V, K65R, D67N, T69S/N/D/insertion, K70R, L74V, V75M/T/A, Y115F, V118I, Q151M, M184V/I, H208Y, L210W, T215Y/F/D/S and K219Q/E/N; NNRTI mutations included: A98G, K101E., K103N, V106A, V108I, V179D, Y181C, Y188C and G190A/S; primary PI mutations included: D30N, V32I, G48V, V82A/T, I84V, N88S/D and L90M; and secondary PI mutations included: L10I/V/F, K20R/M/I, L24I, L33F/V, M36I, M46I, I54V, Q58E, L63A/P/H/T/S/C/Q, A71V/T, G73S/C, T74S/A, V77I and I93L.6

Antiretroviral drug use

Data on the prescribing of antiretroviral therapy within the UK over the period studied were kindly provided by IMS Health. These data were derived from a national UK Pharmacy Prescription audit.

Statistical analysis

The data were analysed using SAS 8.2. Ordinal logistic regression techniques were used to analyse the number of mutations across time and centres. Where data were very sparse, we grouped response levels and in one instance (NNRTIs) dichotomized between 0 and 1–4 mutations per virus.

To explore patterns between combinations of drug class resistances generalized logit models were applied, the response variables taking as levels the drug class combinations. This approach could not be applied when analysing individual mutations and drug classes, as levels of the response variables are not mutually exclusive, but each mutation/drug class to be studied had to be analysed separately via logistic regression. Explanatory variables for all analyses were year and centre. Reference categories of the explanatory variables were 1998—year, large—centre.

Findings from analyses involving multi level response variables are particularly affected by the small sample size, which may lead to insufficient power to detect results that are clinically important but will not achieve statistical significance. However, this study is regarded as exploratory rather than confirmatory, and therefore no adjustment has been made to keep the false error rate at 5% as this will have a detrimental effect on the false negative rate.


    Results
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Resistance testing

Ninety-nine samples were tested for each of the calendar years 1998, 1999 and 2000. Overall, results were obtained for 91, 92 and 92 samples for each year, respectively. This represents a failure rate of approximately 10%, which is comparable to other studies of HIV drug resistance.

Resistance for each class of drug, and combinations of classes

We investigated the presence or not of any key resistance mutation for each of the three classes of drug over time and between centres.

The overall prevalence of patients with no resistance-associated mutations in their plasma virus fell sharply between 1998 and 1999, but then increased in 2000 (31% versus 12% versus 45%) (P < 0.0001) (Figure 1). Thus, at each time period, the majority of patients had virus containing key resistance mutations. Of interest, the prevalence of patients with no resistance was higher in the small centres (odds ratio = 0.47; CI 0.22–0.98).



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Figure 1. Percentage of patients with resistance in any class.

 
For primary protease mutations, there appeared to be a time effect (P = 0.03), with a prevalence of 27% in 1998, 41% in 1999 and 21% in 2000. For any NNRTI resistance, significant increases were observed over time (P < 0.0001), with prevalences in 1998, 1999 and 2000 being 14%, 57% and 38%, respectively, representing a significant increase in both 1999 and 2000 over 1998. However, no centre size differences were noted. In a pattern we noted for both PI and NNRTI resistance, key mutations to nucleoside analogues were present at levels of 66%, 82% and 44% over the 3 years, representing a significant fall between 1999 and 2000. There appeared to be a centre size impact on nucleoside analogue resistance, with the large centre having less resistance (P < 0.01). Odds ratios with their 95% confidence intervals and P values are shown in Table 1.


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Table 1. Odds ratios with confidence intervals for factors associated with antiretroviral class resistance
 
Because of these complex drug class specific patterns of changes over time, we assessed the changes in particular combinations of resistance. Although the prevalence of patients with NRTI + PI resistant virus decreased over time (19% versus 16% versus 7% over the 3 years), there was an increase in those patients with NRTI + NNRTI resistant virus, particularly between 1998 and 1999 (4% versus 27% versus 15%). Of concern, the prevalence of viruses with resistance to drugs within all three classes also demonstrated an overall increase over time, albeit with a peak in 1999 (5% versus 24% versus 13%) (Figure 2). Odds ratios with their 95% confidence intervals and P values are shown in Table 2.



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Figure 2. Percentage of patients with multiclass resistance.

 

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Table 2. Odds ratios with confidence intervals and P values for factors associated with combinations of antiretroviral class resistance
 
Specific resistance-associated mutations

We assessed changes in the number of and nature of mutations conferring reduced susceptibility to each of the three classes of drugs.

Numbers of PI mutations showed a weak time effect (P = 0.05), with an odds ratio of 1.71 (CI: 0.90–3.30) for 1999 versus 1998, but no significant differences between centre size. For the most prevalent of primary mutations, the proportions of patients with L90M were 16%, 23% and 15%, and for V82A/T, 9%, 16% and 5%, over the 3 years. L90M was identified more frequently in smaller clinical centres, compared with the large centre (odds ratio = 2.84; CI: 1.3–6.22). Changes in number of secondary protease mutations (0–8 mutations) mirrored those for primary mutations (see above).

In contrast, numbers of NNRTI mutations increased over time (P < 0.0001), again, with no difference between centre size. Increases over the 3 years were noted for the individual RT mutations K103N (9% versus 25% versus 25%), and G190A/S (3% versus 16% versus 13%), for years 1998, 1999 and 2000, respectively. The prevalence of Y181C increased only between 1998 and 1999 and then fell (9% versus 21% versus 9%).

Significant differences in the number of NRTI mutations were observed over time (P = 0.0002), indicating a more complex pattern of change with an overall increase between 1998 and 1999 (odds ratio = 1.49; CI: 0.99–2.27) followed by a relative decrease (odds ratio = 0.57; CI: 0.35–0.92). There were no significant differences between centre size. Complex patterns of change were apparent for individual mutations, with the prevalence of mutations for 1998, 1999 and 2000 as follows: M184V (29% versus 45% versus 27%); M41L (38% versus 37% versus 22%); L210W (20% versus 23% versus 12%) and T215F/Y (44% versus 43% versus 28%). Of note, many NRTI resistance mutations were more prevalent in patients from small-sized centres, in comparison with the large centre, namely those at positions 41, 44, 69, 70, 74, 75, 184, 215 and 219.

Use of antiretroviral drugs

In order to place patterns of antiretroviral resistance into the context of the overall drug selective pressure, we identified shifts in the proportions of the three classes of antiretroviral therapy prescribed over a similar time span within the UK as a whole. This showed that 1998–2000 represented a period of rapid growth of NNRTI use, at the expense of protease inhibitors, whereas the proportion of prescribed nucleoside analogue drugs used remained stable (Figure 3).



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Figure 3. Antiretroviral prescriptions within the UK.

 

    Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
The overall burden of antiretroviral drug resistance within the population is a function of the following parameters: (a) rate of failure of therapy, (b) the resistance patterns with which such failure occurs, and (c) the rate of transmission of resistant virus.8,9 Good estimates of all three parameters are required for appropriate models to be developed for predicting future responses to therapy at a population level.11

Previous attempts to estimate the characteristics of resistance in patients failing on therapy have generally utilized specific clinical cohorts of patients, or opportunistically generated databases, both of which may not be a true representation of the population.12,13

For this reason, we established this surveillance programme soon after the widespread uptake of triple therapy protocols within the UK, but before such time that drug resistance testing had become routine. We have shown that most patients receiving therapy, with a viral load >2000 copies/mL have at least one key resistance-associated mutation. A number of interesting changes are apparent over the period studied. The overall prevalence of resistance decreases over time, however most apparent is that NNRTI resistance increases. This parallels the shift in prescribing practices over this time, and demonstrates the clear and direct relationship between drug use and emergence of resistance. This has previously been shown for antibiotic usage. This phenomenon is of particular relevance for NNRTI resistance, since single mutations confer broad cross-class resistance.14

We did not seek to match resistance patterns to particular therapies, since this was not the primary goal of the study. Nevertheless, the heterogeneity of treatment histories of patients must be appreciated. Our study will include some patients failing on first line therapy and others who have received multiple drug regimens. In general, the success of therapy diminishes with each successive regimen, with a corresponding increase in the risk of emergence of resistance. This is pertinent to the introduction of a new class of HIV drug, which will initially be utilized preferentially in patients in whom resistance to existing drugs has already occurred. This may have been the case for NNRTI use during the period of our study, although they rapidly replaced PIs as the preferred components of first line therapy within the UK. We do not have data on nevirapine against efavirenz use, so cannot conclude anything about the particular characteristics of NNRTI resistance observed. However, over time this may diminish the rate of emergence of NNRTI resistance in relation to the amount of drug prescribed, i.e. NNRTI use will be more effective at virological suppression, and hence avoidance of resistance, when used within first line therapy. Other changes in clinical practice that would increase successful suppression of virus replication include improvements in adherence, and an improved evidence base to improve clinical management. Nevertheless, these data are sobering in the context of ongoing drug development. Fusion inhibitors, such as T-20 will become widely available in 2004,15 and are likely to be used predominantly within salvage drug regimens. We must expect resistance to this class to rapidly increase within the HIV population, mirroring our data on NNRTI resistance.

We noted higher prevalence of resistance in patients cared for in small-sized centres compared with a large centre. The possible reasons for this include the use of more recently available drugs in larger centres, or wider availability of therapeutic trials, and also a more effective use of therapies in larger centres, thus reducing the risk of broad resistance patterns at time of failure. Also, differences in the proportion of patients initiating first line therapy between centres may impact on such resistance patterns and this could reflect differences in the populations served by different sized clinics. It is inappropriate to draw any firm conclusions about causality, and we suggest that further work is undertaken to assess the utilization of antiretroviral therapies across centres. Within the UK, the British HIV Association is currently undertaking an audit of clinical care, and adherence to clinical guidelines, and this should yield useful information (http://www.bhiva-clinical-audit.org.uk).

A number of studies show an increasing transmission of drug-resistant HIV over the period of our study. Within the UK, the number of new diagnoses has risen continuously from 1998, with a proportion of these acquired within the UK (http://www.hpa.org.uk/infections/topics_az/hiv_and_sti/hiv/hiv.htm). In view of the success of HAART, leading to an extension in the healthy lifespan of infected individuals, it is likely that treated patients represent the source of some of these new infections. In this context, our data are important, since infectiousness will be increased in those with virological rebound, i.e. those represented in the study. In particular, we note the increase over time (at least between 1998 and 1999) of the prevalence of patients with resistance to all three classes of drugs. This pool of individuals will be cumulative, since they are most likely to have initiated therapy some years previously, and are increasingly likely to fail new regimens of treatment. Transmission of such multidrug-resistant HIV is well documented,16 and is associated with suboptimal response to therapy.8 Therefore, there is a public health impetus to identify new therapeutic paradigms to use for these individuals.

Finally, these data are relevant to post-exposure prophylaxis (PEP) strategies, since recommended protocols need to consider the prevalent drug resistance patterns within the population at the time.


    Acknowledgements
 
We thank Daina Ratcliffe and Judith Workman for technical assistance, and the UK Department of Health for financial support for this work.


    Footnotes
 
* Corresponding author. Present address: Department of Virology, Windeyer Institute, Royal Free and University College Medical School, University College London, 46 Cleveland St, London W1T 4JF, UK. E-mail: D.Pillay{at}ucl.ac.uk Back


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
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15 . Greenberg, M. L., Sista, P., Miralles, G. D. et al. (2002). Characterisation of baseline and treatment-emergent resistance to T-20 (enfuvirtide) observed in Phase II clinical trials: substitutions in gp41 amino acids 36–45 and enfuvirtide susceptibility of virus isolates. Antiviral Therapy 7, Suppl. 1, S16 (abstract 21).

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