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Keywords:

  • antiretroviral treatment;
  • drug resistance;
  • HIV;
  • mutations;
  • treatment failure

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Objective

The Honduran HIV/AIDS Program began to scale up access to HIV therapy in 2002. Up to May 2008, more than 6000 patients received combination antiretroviral therapy (cART). As HIV drug resistance is the major obstacle for effective treatment, the purpose of this study was to assess the prevalence of antiretroviral drug resistance in Honduran HIV-1-infected individuals.

Methods

We collected samples from 138 individuals (97 adults and 41 children) on cART with virological, immunological or clinical signs of treatment failure. HIV-1 pol sequences were obtained using an in-house method. Resistance mutations were identified according to the 2007 International AIDS Society (IAS)-USA list and predicted susceptibility to cART was scored using the anrs algorithm.

Results

Resistance mutations were detected in 112 patients (81%), 74% in adults and 98% in children. Triple-, dual- and single-class drug resistance was documented in 27%, 43% and 11% of the study subjects, respectively. Multiple logistic regression showed that resistance was independently associated with type of treatment failure [virological failure (odds ratio (OR)=1) vs. immunological failure (OR=0.11; 95% confidence interval (CI) 0.030–0.43) vs. clinical failure (OR=0.037; 95% CI 0.0063–0.22)], route of transmission (OR=42.8; 95% CI 3.73–491), and years on therapy (OR=1.81; 95% CI 1.11–2.93).

Conclusion

The prevalence of antiretroviral resistance was high in Honduran HIV-infected patients with signs of treatment failure. A majority of study subjects showed dual- or triple-class resistance to nucleoside reverse transcriptase inhibitors, nonnucleoside reverse transcriptase inhibitors and protease inhibitors. Virologically defined treatment failure was a strong predictor of resistance, indicating that viral load testing is needed to correctly identify patients with treatment failure attributable to resistance.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

The mortality of HIV-1 infection has decreased dramatically in the developed parts of the world following the introduction of combination antiretroviral therapy (cART) in 1996 [1–3]. cART typically involves therapy with two nucleoside reverse transcriptase inhibitors (NRTIs) and a protease inhibitor (PI) or a nonnucleoside reverse transcriptase inhibitor (NNRTI) [3,4]. Considerable efforts are being made to improve access to cART in developing countries. It is estimated that more than 9 million adults in low- and middle-income countries with advanced stages of HIV infection are in urgent need of cART. By December 2007, only about 3 million of these patients were actually receiving therapy. Currently, it is estimated that 390 000 individuals (62%) of those in medical need of cART in Latin America and the Caribbean are provided with medication by established treatment programmes [5].

Honduras is estimated to have one of the highest HIV-1 prevalences (0.7%; range 0.4–1.4%) in Latin America [6]. Of the large number of HIV-positive individuals, 12 000 are estimated to be in need of cART (Table 1). The National HIV/AIDS Program in Honduras began to scale up access to therapy in 2002, and since then many patients have gained access to cART. At present approximately 6000 patients have been under treatment, of whom around 700 have interrupted therapy and more than 800 have died [7].

Table 1.   HIV and AIDS in Honduras, update December 2007 (from the Department of STD/HIV/AIDS of Honduras)
Descriptionn
  • *

    Dr Elsa Palou, Minister of Health, and HIV National Program, 2008 report.

  • cART, combination antiretroviral therapy.

The HIV and AIDS epidemic
 Estimated prevalence56 000 (0.7%)
 Cumulative HIV-positive cases24 868
 Cumulative AIDS cases18 738
 Asymptomatic cases6130
 Male10 764
 Female7819
 Children under 15 years1331
Antiretroviral therapy (until May 2008)
 In need of cART12 000
 Receiving cART5800
  Adults5095
  Children705
 On first- or second-line therapy*5568 (96%)
 In need of salvage therapy*232 (4%)

The goal of modern cART is to suppress viral replication and maintain plasma HIV-1 RNA levels in treated patients below the detection limit of sensitive assays (i.e. <50 HIV-1 RNA copies/mL plasma) [3,4]. Treatment failure during cART is a significant clinical problem. Poor adherence is the most common cause of treatment failure, but failure can also be caused by other factors such as pharmacological interactions and infection with drug-resistant virus. Regardless of its cause, treatment failure is frequently associated with progressive development of resistance to the antiretroviral drugs used. Resistance is caused by mutations in the HIV-1 genome, for example in the protease (PR) and reverse transcriptase (RT) regions of the polymerase (pol) gene [8–12]. Thus, routine genotypic HIV resistance assays are based on the detection of mutations in PR and RT, which are known to be associated with resistance. HIV drug resistance poses a major obstacle for effective treatment; when resistance mutations emerge, patients often display virological, immunological and clinical failure. There is no precise information on the proportion of Honduran HIV-infected patients on cART who fail treatment, but the National HIV/AIDS Program in Honduras reported an estimated proportion of 2% (Dr Palou, Honduran Ministry of Health, personal communication).

We investigated the prevalence of resistance in a group of adult and paediatric Honduran HIV-infected patients with treatment failure.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Patients

Patients were invited to participate in the study by their medical doctors. After they had consented, whole blood was collected in BD Vacutainer® Cell Preparation Tubes (Becton Dickinson, Franklin Lakes, NJ, USA) to obtain plasma and peripheral blood mononuclear cells (PBMCs). The study samples were collected between June 2004 and April 2007. Our patients were selected from the two major medical facilities in the country, Instituto Nacional del Tórax in Tegucigalpa and Hospital Mario Catarino Rivas in San Pedro Sula, but are likely to be representative of patients failing cART in the country. The inclusion criterion was signs of treatment failure after more than 6 months of therapy. Treatment failure was divided into three hierarchical categories (virological, immunological and clinical treatment failure) because access to plasma HIV-1 RNA and CD4 T-lymphocyte quantification was irregular during the study period. Thus, virological treatment failure was defined as plasma viral load (VL) >1000 copies/mL (VL determined a maximum of 6 months prior to the resistance test). For patients who did not fulfil the criteria for virological treatment failure, immunological treatment failure was defined as CD4 <250 cells/μL (CD4 count determined a maximum of 6 months prior to the resistance test). For patients who did not fulfil the criteria for virological or immunological treatment failure, clinical treatment failure was defined as the development of opportunistic infection or other clinical symptoms indicating disease progression.

The ethics committee at the National Autonomous University of Honduras and the Regional Medical Ethics Board in Stockholm, Sweden approved the study (Dnr. 21/2007-77).

Measurements of plasma HIV-1 RNA levels and CD4 cell counts

Plasma HIV-1 RNA levels (VL) were measured using an Amplicor HIV-1 monitor system (Roche, Rotkreuz, Switzerland) or the Real-Time PCR HIV-1 system (Abbott Laboratories, Des Plaines, IL). CD4 cell counts were measured using the Dynal® T4 Quant Kit (Dynal Biotech ASA, Oslo, Norway).

Estimation of adherence

Adherence to HIV therapy was scored as good, intermediate or poor by self-reporting by the patients in face-to-face interviews during ordinary clinical visits and from the medical records. The scoring system has been established by the Ministry of Health in Honduras following the Spanish recommendations [13]. Thus, adherence was scored as good when the patients reported having missed fewer than three doses in the last month; intermediate when three to 12 doses had been missed, and poor when more than 12 doses had been missed.

Genotypic HIV-1 resistance testing

Blood samples (10–20 mL of sodium citrate-treated whole blood) for genotypic resistance testing were collected in Honduras. Plasma and PBMCs were separated in a polyester gel and a density gradient liquid (BD Vacutainer CPT Tube) and stored at −80 °C in Honduras before shipment to Sweden for genotypic resistance testing.

Resistance testing was carried out on plasma RNA or PBMC DNA using an in-house method. Briefly, RNA or DNA was extracted from plasma or PBMCs using the QIAmp RNA or DNA kit (Qiagen, Hilden, Germany). The RNA was used to generate cDNA, whereas the DNA was directly used for polymerase chain reaction (PCR). A nested PCR for the pol gene was performed for sequencing using a reaction mixture and cycling conditions as described previously [14], with some modification of primers. The PCR primers were JA269 (outer forward AGGAAGGACACCARATGAARGA), JA272 (outer reverse GGATAAATCTGA CTTGCCCART), JA270 (inner forward GCTTCCCTCARATCACTCTT) and JA271 (inner reverse CCACTAAYTTCTGTATRTCATTGAC). The sequencing primers were JA273 (outer forward CCCTCAAATCACTCTTTGGC), JA274 (inner forward AAAATC CATACAATACTCCA), JA275 (inner reverse TTATTGAGTTCTCTGAAATC) and JA276 (outer reverse TGTATATCATTGACAGTCCA). DNA sequencing was performed on an ABI Prism 3100 Genetic Analyser (Applied Biosystems, Stockholm, Sweden). The sequence fragments were assembled and analysed using the software program sequencher (Gene Codes Corporation, Ann Arbor, MI, USA). The HIV-1 pol sequences have been submitted to GenBank under accession numbers FJ800379–FJ800386, FJ800388–FJ800438, FJ800440–FJ800505 and FJ823645–FJ823657.

Major and minor resistance mutations according to the 2007 list of the International AIDS Society–USA Panel Guidelines [9] were identified using the Stanford hivdb program (http://hivdb.stanford.edu). The predicted susceptibilities of the viruses to NRTIs, NNRTIs and PIs were estimated using the ANRS algorithm (July 2008, version 17; http://www.medpocket.com). The resistance profiles were used together with clinical data and other laboratory data to provide individualized expert advice on possible treatment modifications, taking into account the fact that some registered antiretroviral drugs are not available in Honduras.

The pol gene sequences and recommended subtype reference sequences (http://www.hiv.lanl.gov) were also used to construct neighbour-joining phylogenetic trees using the mega 4 software [15]. Phylogenetic tree analysis was used to determine the subtype of the pol gene sequence and to facilitate detection of possible PCR contamination and sample mix-up.

Statistical methods

The prevalence of drug resistance mutations was calculated with a 95% confidence interval (CI) based on the binomial distribution. Univariable and multivariable logistic regression analyses were used to estimate odds ratios (ORs) with 95% CIs for the association between resistance status and various factors. Statistical analyses were carried out using statistica version 8.0 (StatSoft Inc., Tulsa, OK, USA) and stata version 8.2 (StataCorp LP, College Station, TX, USA).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

A total of 138 HIV-1-infected individuals with treatment failure were included in the study (Table 2); 97 were adults and 41 were children under 18 years of age. A little more than half of the study subjects were male (57%). The median age was 38 years for the adults and 10 years for the children. All individuals were native Hondurans; the most frequent route of transmission was heterosexual transmission (66%), followed by mother-to-child transmission (28%), blood products (3%) and homosexual transmission (3%). The severity of disease according to the Centers for Disease Control and Prevention (CDC) Classification System [16] was stage A for 12 patients, stage B for 60 patients and stage C for 66 patients. Adherence was scored as good in 99 patients (72%), intermediate in 26 patients (19%) and poor in 13 patients (9%). The median time on antiretroviral therapy was 3.2 years (range 1–12 years). The median CD4 count was 185 cells/μL and the median VL was 4.5 log10 copies/mL (Table 2). The median time span between sampling for the resistance test and the last available CD4 cell count was 5 months (range 0–36 months); one patient had never undergone CD4 cell count measurements. The median time span between the last VL measurement and sampling for resistance was 5 months (range 0–25 months); seven patients had never undergone VL testing. Only 37 patients (28%) had CD4 cell counts and VL determined simultaneously with the resistance test.

Table 2.   Demographics and characteristics of the study population
CharacteristicTotalResistance*No resistanceOR (95% CI)OR (95% CI)
UnivariableMultivariable
  • *

    Predicted susceptibility to antiretroviral therapy (ART) was scored using the anrs algorithm (July 2008, version 17).

  • Treatment change because of suspected treatment failure or drug toxicity.

  • Treatment change because of cost or interrupted drug supplies.

  • §

    § CD4 cell counts were available for 137 patients; 29 of these were obtained on current combination ART (cART) and <6 months prior to resistance testing.

  • Plasma HIV RNA levels were available for 131 patients; 71 of these were obtained on current ART and <6 months prior to the time for resistance testing. Only 37 patients had CD4 cell counts and HIV RNA levels determined simultaneously with resistance testing.

  • CDC, Centers for Disease Control and Prevention; CI, confidence interval; OR, odds ratio.

Patients [n (%)]138112 (81)26 (19)  
Sex [n (%)]
 Male7863 (81)15 (19)1 
 Female6049 (82)11 (18)1.06 (0.44–2.51) 
Age [n (%)]
 Adults9772 (74)25 (26)1 
 Children under 18 years4140 (98)1 (2)13.8 (1.81–106) 
Probable route of infection [n (%)]
 Heterosexual9166 (73)25 (27)11
 Mother-to-child3938 (97)1 (3)14.3 (1.87–110)42.8 (3.73–491)
 Blood products44 (100)0 
 Male–male sex44 (100)0 
Years on ART
 Median (range)3.2 (1–12)4 (1–12)2.5 (1–7)1.64 (1.21–2.23)1.80 (1.11–2.93)
Start of therapy [n (%)]
 In national cART programme8060 (75)20 (25)10.33 (0.06–1.65)
 Before national programme5852 (90)6 (10)2.89 (1.08–7.74) 
Number of ART regimens [n (%)]   1.82 (1.20–2.77)1.30 (0.76–2.24)
 One3020 (67)10 (33)  
 Two4333 (77)10 (23)  
 Three2926 (90)3 (10)  
 Four2118 (86)3 (14)  
 ≥Five1515 (100)0  
Main reason for ART change [n (%)]
 No change3020 (67)10 (33)1 
 Rational change6857 (84)11 (16)2.60 (0.96–7.02) 
 Irrational change1716 (94)1 (6)8.00 (0.92–69.2) 
 Interrupted therapy2319 (83)4 (17)2.40 (0.64–8.88) 
Type of failure [n (%)]
 Virological7166 (93)5 (7)11
 Immunological2917 (59)12 (41)0.11 (0.03–0.35)0.11 (0.03–0.43)
 Clinical3829 (76)9 (24)0.24 (0.08–0.80)0.03 (0.01–0.22)
Clinical CDC stage [n (%)]
 Stage A1211 (92)1 (8)1 
 Stage B6048 (80)12 (20)0.40 (0.04–3.10) 
 Stage C6653 (80)13 (20)0.40 (0.04–3.13) 
Reported adherence level [n (%)]
 Good9982 (83)17 (17)1 
 Intermediate2622 (85)4 (15)1.14 (0.35–3.73) 
 Poor138 (62)5 (38)0.33 (0.10–1.14) 
CD4 count (cells/μL)§
 Median (range)185 (4–1123)205 (4–1123)118 (15–670)1.33 (1.01–1.80) 
 Viral load (log10 copies/mL)
 Median (range)4.5 (1.7–5.0)1.7 (1.7–5.0)4.5 (1.7–5.0)2.01 (1.40–2.92) 

The patients were recruited using three different criteria for treatment failure (virological, immunological and clinical) because access to plasma HIV-1 RNA and CD4 quantification was irregular during the study period. Table 2 shows that 51% of the treatment failures were identified virologically, 21% immunologically and 28% clinically.

At the time of sampling for resistance testing, 50% of the patients were receiving two NRTIs+one NNRTI, 47% were receiving two NRTIs+one PI, and 3% were receiving triple-class therapy (one NRTI+one NNRTI+one PI). The most common drug combinations were: zidovudine+lamivudine+efavirenz (40 patients), stavudine+lamivudine+nelfinavir (13 patients), stavudine+lamivudine+nevirapine (12 patients), and zidovudine+lamivudine+indinavir (nine patients).

Genotyping of HIV resistance was performed in all 138 study subjects using an in-house resistance assay. As described in the Materials and Methods and for logistical reasons (i.e. safe transport of high-quality samples to Sweden), the majority of the sequences were obtained from PBMCs, whereas 42 resistance tests were performed using both PBMC DNA and plasma RNA. We compared the mutational resistance patterns in plasma and PBMCs for these 42 patients and observed a high concordance (data not shown). Thus, 97% of the observed resistance mutations were concordantly detected in plasma and PBMCs. All pol sequences were of HIV-1 genetic subtype B. We did not find any unexpected close clustering or identical sequences, which indicates that we did not experience problems with PCR contamination.

At least one major drug resistance mutation was documented in 112 of the 138 patients (81%; 95% CI 79–91%) (Table 2). Resistance was more common in the samples from children (98%; 95% CI 87–99) than in those from adults (74%; 95% CI 64–82) (P=0.011). Resistance was also strongly related to route of transmission (P=0.010), which was not unexpected given the significant difference between adults and children. Resistance was significantly more prevalent in patients in whom treatment failure had been identified virologically as compared with immunologically (P<0.001) or clinically (P=0.019).

Of the study subjects, 80 patients (58%) had started treatment after 2002 within the frame of the National HIV/AIDS cART Program and thus should have received triple combination therapy in a systematic way. Sixty of these patients (75%) displayed drug resistance mutations after a median time on cART of 2.6 years. There were 58 study subjects (42%) who had begun therapy before 2002 (before the start of the National HIV/AIDS Program); they had a median time on ART of 6 years, and 52 of them (90%) showed drug resistance mutations. Of these patients, 52% had started with mono or dual therapy, whereas 48% had been started on a triple combination, but as described below almost all had had discontinuous ART and many treatment changes. Start of therapy before or within the national treatment programme was significantly associated with the prevalence of resistance (P=0.035). Resistance was also strongly correlated to years on therapy (P=0.001).

The patients had received a median of two (range one to six) different ART regimens (Table 2). Resistance was positively correlated with the number of treatment changes (P=0.005). Thus, resistance was documented in 20 of 30 patients (67%) who were on their first regimen vs. 15 of 15 patients (100%) who had undergone at least five treatment changes. Only 22% of the patients remained on first-line therapy. The remaining patients had undergone one or several treatment changes. The majority of these treatment changes (49%) were made rationally (e.g. because of suspected treatment failure or drug toxicity), in 12% of the cases the treatment changes were irrational (e.g. because of cost or interrupted drug supplies) and 17% of the changes involved treatment interruption (often because of cost or interrupted drug supplies) (Table 2). CDC stage and self-reported adherence levels were not significantly correlated to resistance, whereas CD4 cell counts and plasma HIV RNA levels were significantly correlated to resistance. However, it should be pointed out that these CD4 and HIV RNA levels frequently were not obtained concomitantly with the resistance test and often not even while the patient was on the same therapy as when the resistance test was carried out.

Multiple logistic regression was used to identify variables that were independently associated with the presence of genotypic resistance. The final model includes as categorical variables: route of infection, start of therapy within the national treatment programme (yes/no) and type of virological failure (virological, immunological or clinical). Number of treatment changes and years on therapy were included as continuous variables. Age (adult vs. child) was not included as a variable because it largely overlapped with route of infection. CD4 cell counts and HIV RNA were not included because results were not available for all patients and often were obtained long before the sample used for resistance testing. The multivariable analysis identified the following variables as independently associated with resistance: type of treatment failure [virological failure (OR=1) vs. immunological failure (OR=0.11; 95% CI 0.030–0.43) vs. clinical failure (OR=0.037; 95% CI 0.0063–0.22)]; route of transmission (OR=42.8; 95% CI 3.73–491); and years on therapy (OR=1.81; 95% CI 1.11–2.93). This indicates that VL testing was needed to correctly identify patients with treatment failure attributable to resistance.

As shown in Table 3, genotypes predicted to have reduced susceptibility to at least one NRTI were observed in 98 of 138 patients (71%; 95% CI 63–78%); to at least one NNRTI in 96 patients (70%; 95% CI 61–77%); and to at least one PI in 51 patients (37%; 95% CI 29–45%). Dual and triple class resistance was very common. Thus, triple-class drug resistance was documented in 37 of the 138 study subjects (27%; 95% CI 20–35%) and dual-class drug resistance was detected in 59 patients (43%; 95% CI 34–51%), whereas only 16 (12%; 95% CI 7–18) of the patients showed single-class resistance.

Table 3.   Frequency of HIV drug resistance mutations according to drug class family
 Patients with drug resistance
Before national programmeWithin national programmeTotal
  1. Data are n (%).

  2. NRTI, nucleoside reverse transcriptase inhibitor; NNRTI, nonnucleoside reverse transcriptase inhibitor; PI, protease inhibitor.

All5880138
 No resistance6 (10.3%)20 (25.0%)26 (18.8%)
 Any resistance52 (89.7%)60 (75.0%)112 (81.2%)
 Any NRTI48 (82.7%)50 (62.5%)98 (71.0%)
 Any NNRTI42 (72.4%)54 (67.5%)96 (69.5%)
 Any PI32 (55.1%)19 (23.7%)51 (36.9%)
Single
 NRTI1 (1.7%)2 (2.5%)3 (2.1%)
 NNRTI2 (3.4%)9 (11.2%)11 (7.9%)
 PI2 (3.4%)2 (1.4%)
Dual
 NRTI+NNRTI17 (29.3%)30 (37.5%)47 (34.0%)
 NRTI+PI7 (12.0%)4 (5.0%)11 (7.9%)
 NNRTI+PI1 (1.2%)1 (0.7%)
Triple
 NRTI+NNRTI+PI23 (39.6%)14 (17.5%)37 (26.8)

During their treatment history, 45 patients had received treatment with two classes of drug (NRTIs+NNRTIs); 15 of these patients did not display resistance, four had resistance to one class of drug (three to NNRTIs and one to NRTIs), 25 had two-class resistance (24 to NRTIs+NNRTIs and one to NRTIs+PIs), and one patient had three-class resistance (NRTIs+NNRTIs+PIs). Ninety-three patients had taken at least one PI in their treatments: 11 of them showed no resistance; 12 displayed resistance to one class of drug (eight to NNRTIs, two to NRTIs and two to PIs); 34 patients showed resistance to two classes of drug (23 to NRTIs+NNRTIs, 10 to NRTIs+PIs and one to NNRTIs+PIs), and 37 showed resistance to three classes of drug.

Figure 1 shows the resistance mutations that were observed in the study population. At least one thymidine-associated mutation (TAM), that is a mutation at position 41, 67, 210, 215 or 219 in RT, was seen in 60% of patients, and the lamivudine/emtricitabine resistance mutation M184I/V was observed in 62% of the patients. Multi-nucleoside resistance mutations, such as Q151M, were rare and such a mutation was only observed in one patient. The K103N mutation was the most frequently observed (30%) of the NNRTI resistance mutations. A smaller proportion of the study subjects (32%) had at least one major PI resistance mutation; for example, a mutation at position 30, 46, 82, 84, 88 or 90 of PR.

image

Figure 1.  Prevalence of antiretroviral resistance mutations at selected codons associated with decreased susceptibility. NRTI, nucleoside reverse transcriptase inhibitors; NNRTI, nonnucleoside reverse transcriptase inhibitors; PI, protease inhibitors.

Download figure to PowerPoint

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

The present study describes the prevalence of genotypic resistance to antiretroviral drugs in clinical samples from 138 Honduran patients who were failing ART. It was found that the prevalence of resistance was high (81%) in our study population. Thus, resistance to at least one drug class was found in 11% of the patients, dual class resistance was found in 43% of the patients and triple class resistance was found in 27% of the patients. The proportion of individuals with resistance was higher among children (98%) than among adults (74%). The type of treatment failure (virological, immunological or clinical) was the strongest predictor of resistance, but route of transmission and years on therapy were also independently associated with the presence of genotypic resistance.

Our study revealed that there are considerable problems with resistance to antiretroviral drugs in Honduras. However, it is important to stress that our results do not reflect the prevalence of resistance among all HIV-infected patients in Honduras, because the study subjects were selected on the basis of treatment failure. Nevertheless, it is worrying that dual- and triple-class resistance was very common. Furthermore, we observed that treatment changes were common and associated with a higher prevalence of resistance, as was years on therapy.

Our review of the patient records revealed that many of the treatment changes were not driven by laboratory results indicating treatment failure, primarily because access to plasma HIV-1 RNA and CD4 quantification was irregular during the study period. Instead, treatment changes had often been initiated as a consequence of clinical progression or interrupted access to specific antiretroviral drugs. Thus, the resistance problems in our study population appear in part to be attributable to limited and interrupted access to treatment, but also involve problems with adherence and the prior use of mono and dual therapy. Importantly, the definition of treatment failure (virological, immunological or clinical) was the strongest predictor of resistance. Immunological and clinical treatment failure were categorised as inclusion criteria because access to plasma HIV-1 RNA and CD4 quantification was irregular during the study period. The finding that immunological and clinical criteria were poor predictors of treatment failure attributable to resistance is important and has relevance for other resource-poor settings where access to VL testing may be limited. Our results are in agreement with recent data which also show that CD4 cell counts and clinical criteria do not accurately identify patients with virological treatment failure [17–19].

In this study, we estimated that the overall prevalence of resistance-associated mutations was 81% among the investigated Honduran patients, who were selected on the basis of signs and symptoms of treatment failure. This finding agrees well with results from the United Kingdom (80% resistance) [10], United States (76% resistance) [11], and France (88% resistance) [12], in spite of the fact that the cART conditions in these countries are very different from those in Honduras. It is somewhat surprising that 19% of the 138 studied patients did not appear to harbour a resistant virus even though they had been selected as experiencing treatment failure. The absence of resistance in 19% of the patients indicates that adherence in these patients may have been too low to drive the development of resistance. However, and as discussed above, the significant association of resistance with type of failure (virological, immunological or clinical) also demonstrates that it is difficult to monitor HIV therapy without regular access to plasma HIV-1 quantification. Thus, patients with adequate adherence and low plasma HIV RNA levels may incorrectly have been perceived to have immunological or clinical treatment failure.

We observed that the presence of genotypic resistance was positively correlated with years on therapy and the number of ART regimens used. When this study was carried out, access in Honduras to boosted PIs was very limited. The broad resistance to NRTIs, NNRTIs and unboosted PIs indicates that many of our study subjects were in need of salvage therapy with boosted PIs as well as entry and integrase inhibitors [3]. Improved access to these drugs is urgently needed for these and other heavily treatment-experienced Honduran patients. M184V and K103N were the most prevalent NRTI and NNRTI mutations in our study, at 62% and 30%, respectively. M184V causes high-level (>100-fold) resistance to lamivudine/emtricitabine and emerges rapidly in patients who receive lamivudine monotherapy [20]. It is also the first mutation to develop in patients receiving partially suppressive triple combination therapy including lamivudine [21–23]. K103N is the most clinically important NNRTI resistance mutation. It causes 20- to 50-fold resistance to the most available NNRTIs, which is sufficient to cause virological failure [24,25]. It was not surprising to find a high frequency of the K103N mutation because of the common use of NNRTIs in Honduras and the ability of the virus to develop NNRTI resistance mutations during monotherapy and during incomplete viral suppression [25].

Some limitations of our analysis should be mentioned. The patients were classified as failing their current cART based on virological, immunological, and/or clinical data; but some patients may incorrectly have been classified as failing their current regimen because access to laboratory monitoring is limited in Honduras. Furthermore, for logistical reasons (i.e. safe transport of high-quality samples to Sweden), only 42 resistance tests were performed using plasma samples and the remaining sequences were obtained from PBMCs. We compared the mutational resistance patterns in plasma and PBMCs for these 42 patients and observed a high concordance. Similar results have been shown in other studies [26–28]. Thus, we feel that it is unlikely that our findings have been significantly affected by the fact that most resistance tests were carried out on PBMC DNA. Another potential limitation of our study is that it is difficult to precisely estimate the representativeness of our study population with regard to all patients failing ART in Honduras because there is no reliable information about how many patients have successful vs. failing first- or second-line therapy.

In conclusion, we have documented a high prevalence of resistance to antiretroviral drugs in this sample of antiretroviral-treated adult and paediatric HIV-infected patients in Honduras. Most of the treatment failures observed in these patients can be attributed to the previous use of mono and dual therapy and to limited and interrupted access to antiretroviral drugs in this country. Irregular access to CD4 and VL testing is an additional problem. Similarly, there is a need to establish access to routine resistance testing in Honduras, and this is one of the overall aims of the bilateral collaboration between Honduras and Sweden. In our study, virological failure was the strongest predictor of resistance. This suggests that plasma HIV RNA quantification may be clinically beneficial and cost effective through preventing unnecessary treatment changes. Thus, the management of these heavily treatment-experienced HIV-infected patients represents a considerable challenge for HIV clinicians in Honduras. There is an urgent need for improved and sustainable access to antiretroviral drugs, including boosted PIs, newly introduced NNRTIs, and entry and integrase inhibitors, as well as VL, CD4 and resistance testing.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

We thank all collaborators in this study. In particular, we thank Elizabeth Dacarett, Renato Cruz, Varinia Izaguirre, Emil Padgett, Norma Solorzano, Luisamaria Pineda, César Caballero, Gabriela Cano, Marco Tulio Luque, Ondina Linares, Charles Parchment, Dennis Padgett and Maribel Rivera enrolled patients; in Sweden, Kajsa Aperia, Afsaneh Heidarian and Maj Westman; in Honduras, Karla Mejía, Gloria Salinas and Olga Chirinos for assistance and practical help. We especially thank Katarina Gyllensten and Lars Navér for expert advice on possible treatment modifications following resistance results, and particularly all study participants.

This study was supported by Sida/SAREC in a bilateral collaboration with the National Autonomous University of Honduras.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
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