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Impact of genotypic drug resistance mutations on clinical and immunological outcomes in HIV-infected adults on HAART in West Africa

Seyler, Catherinea,c; Adjé-Touré, Christianeb; Messou, Eugènea,d; Dakoury-Dogbo, Nicolec,d; Rouet, Françoise; Gabillard, Delphinea; Nolan, Monicab; Toure, Siakaa,d; Anglaret, Xaviera,c

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doi: 10.1097/QAD.0b013e3281c615da
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At the end of 2005, the number of adults receiving antiretroviral therapy in sub-Saharan Africa was estimated at 810 000 [1]. This number is expected to increase rapidly within the next few years. In this context, the emergence of resistance to antiretroviral drugs should be watched closely [2].

So far, the rate of primary resistance to antiretroviral drugs has been found to be low in sub-Saharan Africa [3–5]. A few studies have suggested a rapid selection of drug resistance mutations after antiretroviral therapy initiation [6–8]. These investigations have, however, been conducted in small number of settings only or have concerned a limited number of patients over a short period on HAART. In most sub-Saharan African settings where access to HAART has been rapidly scaled-up over the past few years, little is known about the pattern of primary and secondary drug resistance

Data on antiretroviral drug resistance are needed to help experts identify the most appropriate first and second-line regimens of HAART to be recommended in national and international guidelines. These guidelines will, however, have to take into account not only the prevalence of primary and secondary resistance mutations in the population, but also the clinical and immunological consequences for patients of harbouring resistant virus while being on a given HAART regimen. To our knowledge, these consequences have not been clearly described in the sub-Saharan African context.

In 2004, we performed viral load measurements and genotype resistance tests in adults who were receiving HAART in Abidjan, Côte d’Ivoire. After virological assessments, we followed these patients under cohort conditions for 20 months. We describe here their clinical and immunological evolution over 20 months, according to the presence or absence of mutations at the time of inclusion in the study.


Setting and patients

From 1996 to 2003, 723 HIV-infected adults have been followed in the ANRS 1203 cohort study in Abidjan, Côte d’Ivoire [9,10]. At the end of this study, health professionals managing this cohort created a non-governmental association, ACONDA. In 2004, ACONDA launched a 5-year programme of access to HIV care and treatment in partnership with the Institute of Public Health, Epidemiology and Development (ISPED, Bordeaux, France). This programme was funded by the United States President's Emergency Plan for AIDS Relief (PEPFAR), through the Elizabeth Glaser Pediatric AIDS Foundation (EGPAF, Washington, DC, USA). The follow-up procedures and the computerized data management system of the ACONDA/ISPED programme have been inspired from those of the ANRS 1203 cohort study [9,10].

In July 2004, when the ACONDA/ISPED programme started, all adults who previously received HAART while being followed in the ANRS 1203 cohort study were offered a virological status assessment, including plasma viral load measurements and genotypic drug resistance testing. Patients included in the present study were all HIV-1-infected adults who started HAART in the ANRS 1203 cohort study and who continued to be followed in the ACONDA/ISPED programme when the ANRS 1203 study stopped. Baseline was the date of the blood sample collection for virological tests. The end of study date was 31 March 2006.

The ANRS 1203 cohort study and the ACONDA/ISPED programme database were approved by the National Ethics Committee of Côte d’Ivoire.


In the ACONDA/ISPED programme, patients on HAART have scheduled monthly clinical visits and bi-annual CD4 cell count measurements. In the interval between two visits, they have open access to their health centre. In accordance with the guidelines of the Côte d’Ivoire Ministry of Health, medical scheduled and unscheduled consultations, antiretroviral drugs, and bi-annual CD4 cell counts are provided under a monthly package price of US$2. For all non-antiretroviral drugs, patients are required to pay an additional package price of US$1 per drug prescription, irrespective of the number and type of drugs prescribed. Symptomatic patients are managed according to predefined standardized algorithms, including laboratory X-ray investigations and standardized first-line treatment regimens for most frequent syndromes [11]. For patients who do not keep scheduled appointments, telephone calls or home visits are made by a community-based team, including experienced social workers and members of associations of people living with HIV [12]. For the present study, we used standardized forms to record baseline and follow-up sociodemographic and clinical data. All clinical events were reviewed by an event documentation committee. The diagnostic criteria were the same as those used in the ANRS 1203 cohort study [9–11].

Laboratory testing

CD4 cell count was measured by flow cytometry (True Count technique on FACScan; Becton Dickinson, Aalst-Erembodegem, Belgium) at the CeDReS laboratory, Treichville Hospital, Abidjan, Côte d’Ivoire. Plasma HIV-1-RNA viral load was quantified using real-time polymerase chain reaction (PCR) at the CeDReS laboratory (Taq Man technology Abi Prism 7000; Applied Biosystems, Rotkreuz, Switzerland, limit of detection 300 copies/ml) [13]. For all patients with a detectable viral load, genotypic resistance testing was performed at the Projet RETRO-CI laboratory, Abidjan, Côte d’Ivoire. For sequencing of the pol gene, HIV-1 RNA was extracted from plasma using the Quiagen method (Quiamp Viral RNA Mini Kit; Quiagen, Valencia, California, USA). The RNA was then used in a two-step reverse transcriptase PCR reaction. The resulting PCR product was 1800 base pairs in length. After purification with Microcon 100 columns (Millipore, Billerica, USA), the PCR products were sequenced using six to seven primers and the Big Dye Terminator v1.1 chemistry. Excess dye terminators were removed using ethanol/sodium precipitation. The sequencing reactions were run on the ABI 3100 genetic analyser. Protease and reverse transcriptase sequences obtained were analysed for the presence of drug resistance mutations using the Viroseq Genotyping System Software v.2.5 (Applied Biosystems, Foster City, California, USA) and were manually edited. Amino acid sequences were pairwise aligned to an HIV-1 HXB-2 K03455 reference sequence. Genotypic mixtures were reported as mutant when non-wild-type nucleotide peaks were at least 20% of the total peak at a base [14].

In this study, any mutations that are listed in the October/November 2006 consensus from the International AIDS Society were considered [15]. Mutations were classified as either major or minor. A strain was considered resistant in the presence of major drug resistance mutations. Major genotypic drug resistance mutations were the following: for nucleoside reverse transcriptase inhibitors: T215Y/F, K70R, M184V, D67N, M41L, L210W, K219E/Q or T69D; for non-nucleoside reverse transcriptase inhibitors: K103N, P225H or L100I; and for protease inhibitors: L90M or I84V.

Statistical analysis

Outcomes were death from any cause, the occurrence of any new serious morbidity event, and immunological failure. Serious morbidity events were all World Health Organization stage 3 or 4 classifying events, and all events leading to hospitalization or death. Immunological failure was defined as a CD4 cell count below 200 cells/μl at study termination. Patients were considered as ‘lost to follow-up’ if their last contact with the study team was before 31 March 2006, and no further information on vital status could be recorded from 31 March 2006 to 31 September 2006. The probability of survival and of remaining free of serious morbidity was estimated using the Kaplan–Meier method. Univariate and multivariate Cox's proportional hazard regression models for first events were used to study the association between outcomes and baseline and follow-up characteristics.


Patient characteristics

Of the 723 patients who participated in the ANRS 1203 cohort, 195 started HAART before July 2004, including 54 who started HAART within the framework of a trial of structured treatment interruption of HAART (Trivacan trial) and 141 who started HAART within the framework of the Cotrame cohort. Among the latter, three were HIV-2 infected, 20 died, eight were lost-to-follow-up and four were transferred out before July 2004. The remaining 106 patients were alive and followed up in the ACONDA/ISPED programme in July 2004, and could be included in the present study. Their characteristics are shown in Table 1. Their median nadir of CD4 cell count was 122 cells/μl [interquartile range (IQR) 28–266]. At study entry, their median previous time on HAART was 37.4 months (IQR 27.2–48.3). During the period on HAART preceding inclusion, 66 patients had 135 modifications in their HAART regimen, including 27 patients with only one modification, 18 with two modifications, and 21 with more than two modifications.

Table 1
Table 1:
Characteristics of the 106 patients included in the study.

Viral load and resistance tests at study entry

At inclusion, 62 patients (58%) had undetectable viral loads (< 300 copies/ml) and 44 (42%) had detectable viral loads. There was no significant difference in viral load distribution between patients with major genotypic drug resistance mutations and patients with no major mutations (median viral load 3.7 log10 copies/ml, IQR 3.2–4.6, versus median viral load 3.6 log10 copies/ml, IQR 3.1–4.4; P = 0.52).

All patients’ strains with detectable viral loads could be amplified for HIV genotyping. Of the 44 patients with detectable viral loads, 21 had no major resistance mutations and 23 had one or more major resistance mutations. In all patients with detectable viral loads with no major resistance mutations, at least one minor mutation was detected. Table 2 details the patterns of minor mutations and major resistance mutations that were detected in the 44 patients with detectable viral loads. The most frequent major mutations were M184V (n = 15), D67N (n = 6), M41L (n = 6), K103N (n = 10) and L90M (n = 3). The most frequent minor mutations were M36I (n = 43), L10I/V/F (n = 19), L63P (n = 6), and A71V (n = 5). Table 3 details, for each of the 23 patients with at least one major mutation, the mutations detected, the type of drugs and the number of drug classes affected. Of the 23 patients with major mutations, 16 presented major mutations for one class and seven for two classes. No patient had major mutations affecting the three classes of drug. The only baseline factor found to be associated with the presence of at least one major mutation was a low CD4 cell count [odds ratio of major mutation in patients with less than 200 CD4 cells/μl compared with other patients: 3.49; 95% confidence interval (CI) 1.32–9.21; P = 0.01].

Table 2
Table 2:
Pattern of mutations in the 44 patients with detectable viral load at inclusion in the study.
Table 3
Table 3:
Distribution of mutations in the 23 patients with major mutations at inclusion in the study.


After virological assessment, patients were followed for a median of 20.5 months. During follow-up, only 10 of the 23 patients with major resistance mutations experienced a change in their HAART regimen and received a new regimen containing only drugs for which no resistance was found in the genotype tests. Of the remaining 13 patients, three were still receiving their first-line regimen, and 10 were already receiving a second-line regimen at the time of inclusion.

During follow-up after virological assessment, one patient was lost to follow-up and one patient died. These two patients harboured major resistance mutations. Twenty-nine patients (including nine patients with major resistance mutations) experienced 43 new episodes of serious morbidity, including 11 patients with 17 oral candidiasis, six patients with eight severe bacterial events (pneumonia, three; enteritis, two; invasive urogenital infections, two; sinusitis, one), one patient with tuberculosis and 12 patients with 17 episodes of unexplained fever or unexplained enteritis leading to at least one day at hospital. As shown in Fig. 1, the 18-month probability of remaining alive and free of severe morbidity was 79% in patients with undetectable viral loads, compared with 86% in patients with detectable viral loads without major resistance mutations (P = 0.91), and 69% in patients with detectable viral loads with major resistance mutations at study entry (P = 0.19), respectively. In the multivariate analysis, the presence of mutations at study entry was not significantly associated with the risk of serious morbidity during follow-up (adjusted hazard ratio 1.73, 95% CI 0.73–4.12; P = 0.21)

Fig. 1
Fig. 1:
Probability of remaining alive and free of serious morbidity within time, according to virological status at inclusion. Log rank: P = 0.19 for undetectable viral load versus detectable viral load with major resistance; P = 0.91 for undetectable viral load versus detectable viral load without major resistance. 0 is the date of inclusion in the study. Serious morbidity was defined as any World Health Organization stage 3 or 4-classifying event and any event leading to hospitalization or death. ——— Detectable viral load with major resistance mutations; – – – – – detectable viral load without major resistance mutations; - - - - - undetectable viral load.

The median time between the end of the study and the date of the last available CD4 cell count was 2.6 months (IQR 0.8–3.7). The median gain in CD4 cell count between study entry and the date of this last available CD4 cell count was +75 cells/μl overall, and +129 cells/μl, +51 cells/μl and +3 cells/μl in patients with undetectable viral loads, detectable viral loads without resistance mutations, and detectable viral loads with resistance mutations at study entry, respectively (Fig. 2). In the multivariate analysis, the two variables significantly associated with immunological failure at the end of the study were a baseline CD4 cell count of less than 200 cells/μl and the presence of major resistance mutations at study entry (Table 4).

Fig. 2
Fig. 2:
Change in CD4 cell count between inclusion and study termination, according to virological status at inclusion. VL, Viral load (plasma HIV-1 RNA level).
Table 4
Table 4:
Factors associated with immunological failure at study termination.


Data on the clinical consequences for patients of harbouring resistant virus while being on HAART have never been reported in Africa.

Among our patients on HAART for a median of 3 years in Abidjan, Côte d’Ivoire, 58% had undetectable viral loads, 20% had detectable viral loads with no major resistance mutations and 22% had major drug resistance mutations. In the following 20 months, patients with major mutations had higher rates of immunological failure and tended to have higher rates of serious morbidity, but their CD4 cell counts remained stable and only one of them died.

These findings deserve the following comments.

In our population, one out of five patients harboured major resistance mutations after a median time on HAART of 3 years. This rate is in the lower bracket of those previously reported from other sub-Saharan African settings, in patients with similar or shorter times on HAART [4,6–8,16–18]. Differences between African settings in terms of the rate of patients with resistance mutations may depend on various determinants. Our study did not aim at identifying these determinants, which still remain to be carefully studied.

The main objective of our study was to analyse the association between the presence of resistance mutations and treatment outcomes. To our knowledge, this has never been done in sub-Saharan Africa so far. Studies of outcomes in patients with resistance mutations are likely to reach different conclusions depending on the type and number of drugs affected and on the range of drugs available in a given setting. In industrialized countries, some studies found an association between drug resistance mutations and an increased risk of death or new AIDS-defining event/death [19,20], whereas others did not find any association between drug resistance mutations and clinical outcomes [21,22]. In Abidjan, Côte d’Ivoire, during the study period, the number of available antiretroviral drugs was limited. Several large programmes of access to HAART were being launched, but the country was experiencing a severe political crisis. In this context, only 43% of patients with major resistance mutations at baseline experienced a change in their HAART regimen, and had a chance that a consecutive reduction in viral load could lead to better immunological and clinical outcomes. The remaining 57% of patients with major resistance could not have their drug regimen appropriately adapted to the genotypic tests results during the study period. The consequences were as follows. On one hand, the 20-month clinical and immunological outcomes of patients with resistance at baseline were clearly compromised compared with patients with no resistance. On the other hand, these patients with resistance mutations had reasonable viral load values at baseline (median 3.7 log10 copies/ml). During the 20-month follow-up, their CD4 cell counts remained stable and close to 200 cells/μl. Although they tended to have higher morbidity rates, most were curable diseases, and only one patient died. In other words, their medium-term outcomes were impaired compared with patients without resistance mutations, but their antiretroviral treatment still protected them from immunological breakdown. The main reason for this is probably that they continued to receive at least one or two antiretroviral drugs against which their viruses had no resistance. Other reasons could be the poorer capacity of the replication of resistant virus compared with wild-type viruses [23,24], and the preservation of some in-vivo effects of some drugs on viruses showing in-vitro resistance [25,26]. In patients with virological failure, even a limited reduction in viral load has been shown to be of importance [27].

Our study has the following limitations. First, patients who participated in the study were part of a group of patients who started HAART while they were followed in a cohort study between 1998 and 2003. Patients from this cohort who died or who were lost to follow-up before July 2004 could not be included in the present study. Among these patients, the rate of resistance mutations was unknown. Therefore, our conclusion that there is immunological stability among the patients with resistance mutations cannot apply to all patients who started HAART, but only to patients who survived and remained in care during a median of 37 months after HAART initiation. Second, our study included patients receiving different regimens of HAART and with different histories of regimen modification since HAART initiation. Our sample size was too limited to adjust the analysis of the association between resistance and outcomes on these variables. Further studies comparing outcomes in patients with and without resistance mutations should include a sufficient number of patients to allow adjustment on antiretroviral drugs received by the patients. Third, in our study, viral load was only measured at baseline, and adherence to HAART was not measured. In further studies, viral load and adherence evolution should be carefully recorded. In patients with detectable viral loads but no major resistance mutation and in those with major resistance who experience a change in their HAART regimen, the rate of virological success would be likely to be associated with improved adherence.

Our findings have the following consequences on ‘when to change a failing regimen’ in sub-Saharan Africa.

In settings in which resistance tests are routinely available, drugs can be spared by an early selective substitution of the drugs against which the virus strains have been shown to be resistant through genotypic tests. In sub-Saharan Africa, although CD4 cell measurement is becoming increasingly available, viral load measurement is still rarely available, and genotypic resistance tests are almost never available. Within the following years, millions of sub-Saharan African adults will receive HAART. In these patients, changing regimens for treatment failure will have to be based on clinical outcomes, with the help of CD4 cell counts in most settings and of viral load measurements in some settings. In these patients, the timing of the acquisition of resistance mutations and the number of mutations will be impossible to determine. Failing therapeutic regimens will be maintained during incompressible periods of time, thus increasing drug resistances [28,29]. In this context, the decision of when to change a failing regimen should not be based on the possibility of sparing some drugs of the failing regimen, but should only focus on the risk for a patient to continue a given failing regimen until an entirely new regimen can be proposed to him or her. Our data suggest that most patients with major drug resistance mutations might maintain stable CD4 cell counts and stay alive for more than one year. In low resource settings with restricted access to second-line antiretrorival regimens, the decision to change a failing regimen could be taken within months. This should be taken into account in further cost-effectiveness analyses of HAART in sub-Saharan Africa [30].

Sponsorship: This study was funded by the United States President's Emergency Plan for AIDS Relief (PEPFAR) via the Elizabeth Glaser Pediatrics AIDS Foundation (EGPAF), and by the Agence Nationale de Recherches sur le SIDA et les Hépatites Virales, Paris, France (ANRS 1203).


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adults; antiretroviral therapy; HIV; morbidity; resistance; sub-Saharan Africa

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