Skip Navigation LinksHome > April 1, 2013 - Volume 62 - Issue 4 > Risk of Virological Failure and Drug Resistance During First...
JAIDS Journal of Acquired Immune Deficiency Syndromes:
doi: 10.1097/QAI.0b013e31827a2a7a
Clinical Science

Risk of Virological Failure and Drug Resistance During First and Second-Line Antiretroviral Therapy in a 10-Year Cohort in Senegal: Results From the ANRS 1215 Cohort

De Beaudrap, Pierre MD, PhD*; Thiam, Moussa PhD; Diouf, Assane MD, MPH; Toure-Kane, Coumba PhD; Ngom-Guèye, Ndèye F. MD§,‖; Vidal, Nicole PhD*; Mboup, Souleymane PhD; Ndoye, Ibrahim MD; Sow, Papa S. MD; Delaporte, Eric MD, PhD*; for the ANRS 1215 Study Group

Free Access
Supplemental Author Material
Article Outline
Collapse Box

Author Information

*UMI 233, Institut de Recherche pour le Développement (IRD), Université de Montpellier 1, Montpellier, France

Laboratoire de Bactériologie-Virologie, Hôpital Le Dantec, Dakar, Sénégal

Multisectorial AIDS Program, Dakar, Senegal

§Centre Régional de Recherche et Formation sur le VIH/SIDA, Université Cheikh Anta Diop (UCAD), UMI 233, Dakar, Sénégal

Centre de traitement ambulatoire, CHU de Fann, Dakar, Sénégal.

Correspondence to: Pierre De Beaudrap, UMI 233 “TransVIHMI,” Institut de Recherche pour le Développement (IRD), 911 Avenue Agropolis, BP 64501, 34394 Montpellier cedex 05, France (e-mail: pierre.debeaudrap@ird.fr).

Supported by the French National Agency for Research on AIDS and Viral Hepatitis (ANRS) (Projects 1215 and 1290), the European Union (Project B7-6211/99/005), the Institut de Recherche pour le Développement (IRD).

The authors have no conflicts of interest to disclose.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the full text and PDF versions of this article on the journal's Web site (www.jaids.com).

Received July 05, 2012

Accepted October 19, 2012

Collapse Box

Abstract

Background: In 1998, Senegal launched one of Africa's first antiretroviral therapy (ART) programs. Since then, the number of treated patients in Africa has substantially increased thanks to simplification in treatment management. Although good outcomes over the first years of ART have been observed in sub-Saharan Africa, little is known about the long-term (>5 years) risks of virological failure and drug resistance and about second-line treatment response.

Methods: Patients from the ANRS-1215 cohort in Senegal, started with either one nonnucleoside reverse transcriptase inhibitor or indinavir, a first-generation nonboosted protease inhibitor, followed for >6 months and having >1 viral load (VL) measurement were included. Virological failure was defined as 2 consecutive VL measurements >1000 copies/mL.

Results: Of the 366 patients included, 89% achieved a VL <500 copies/mL. The risk of virological failure at 12, 24, and 60 months was 5%, 16%, and 25%, being higher in younger patients (P = 0.05), those receiving a protease inhibitor–containing regimen (P = 0.05), and those with lower adherence (P = 0.03). The risk of resistance to any drug at 12, 24, and 60 months was 3%, 11%, and 18%. After virological failure, 60% of the patients were switched to second-line treatments. Although 81% of the patients achieved virological success, the risk of virological failure was 27% at 24 months, mostly in patients with multiple resistances.

Conclusions: In this cohort, virological outcomes for first-line treatments were good compared with those from high-resource settings. However, the rate of virological failure for second-line treatment was high, probably because of accumulation of resistances.

Back to Top | Article Outline

INTRODUCTION

In 1998, Senegal was one of the first African countries to launch a national antiretroviral treatment program, the Senegalese Initiative for Antiretroviral Access (ISAARV).1 Since then, highly active antiretroviral therapy (HAART) has been rolled out all over African countries,2–4 and a substantial increase in the number of HIV-infected patients treated has been observed.5 Although good outcomes over the first years of HAART have been reported in low-resource settings,3,6,7 limited access to laboratory monitoring, the use of poorly tolerated antiretroviral combinations, and the numerous logistical challenges to treatment delivery may compromise long-term outcomes.8–10 Further evidence to justify this concern is therefore of utmost importance. However, data on the long-term virological outcomes and on the response to second-line HAART in resource-limited settings are scarce.

An observational research cohort (ANRS 1215) was started in Senegal with the first patients included in the ISAARV to assess the feasibility, acceptability, and effectiveness of starting an ART.2 In this study, we aimed to analyze long-term virological outcomes and responses to second-line HAART treatment.

Back to Top | Article Outline

METHODS

Study Population

The source population consisted of 444 HIV-1 infected adults enrolled between August 1998 and December 2004 and followed up until June 2010. Study design and inclusion criteria have been previously reported in detail.2,6,11–13 Patients were included in this analysis if (1) they had been started with an ART regimen containing 2 nucleoside reverse transcriptase inhibitors (NRTIs) and either one first-generation nonboosted protease inhibitor (PI) or one nonnucleoside reverse transcriptase inhibitor (NNRTI), (2) they had been followed up for at least 6 months and had had at least one viral load (VL) measurement after their baseline measurement at cohort inclusion. All patients had a comprehensive clinical and biological evaluation at inclusion. Follow-up with a clinical examination occurred every 2 months and biological evaluations—including CD4-cell count and VL measurements—were performed every 6 months. Other monitoring details have been previously published.2,6 The study was approved by the Senegalese National Committee for Health Research.

Back to Top | Article Outline
Definitions

Virological success and failure were defined, respectively, as a patient achieving a VL <500 copies/mL and 2 consecutive VLs ≥1000 copies/mL after achieving initial virological success.14 When the second VL measurement was unavailable, the following criteria were used to define virological failure: one VL measurement ≥1000 copies/mL along with documented immunologic failure (fall in CD4-cell count below pre-ART level or ≥50% decrease) or one VL measurement ≥5000 copies/mL. An alternative definition of virological failure as any VL ≥1000 copies/mL was also considered in this analysis to assess the sensitivity of the results to the criteria used. Finally, a major treatment switch was defined as initiating a new HAART regimen containing either a new drug class or at least 2 drugs not used in the failed regimen.

Back to Top | Article Outline
Adherence

Pill counts of untaken ARVs returned by patients were performed at each pharmacy visit. Adherence was therefore computed for each different ARV as the ratio of pills actually consumed to the number that had been prescribed between 2 consecutive pharmacy visits. The average adherence level was calculated as the mean adherence for all ARV until virological failure, treatment switch, censoring, or death, whichever came first.

Back to Top | Article Outline
Laboratory Procedures

VL was measured using the Amplicor HIV-1 1.5 or 2.0 assay (Roche Molecular Systems, Meylan, France) or the Bayer bDNA HIV-1 Quantiplex 2.0 or 3.0 assay (Bayer Diagnostics, Tarrytown, NY). CD4-cell counts were measured with the FACSCount technique (Becton Dickinson, San Jose, CA). Genotypic drug resistance testing was performed on samples with VL ≥1000 copies/mL, using a previously described in-house assay.15 Briefly, a pol gene fragment spanning the protease and two-thirds of the reverse transcriptase regions was generated by nested polymerase chain reaction and then directly sequenced. HIV-1 subtypes/CRFs were determined by phylogenetic tree and recombination analysis. Amino acid sequences were used to identify minor and major resistance mutations in protease and reverse transcriptase genes, based on the latest updated online Stanford Resistance Database HIValg program (http://sierra2.stanford.edu/sierra/servlet/JSierra?action=algSequenceInput). Mutations were interpreted using the ANRS algorithm version V2011.05, HIVDB algorithm version 6.1.1, and the REGA algorithm version V8.0.2.

Back to Top | Article Outline
Statistical Analysis

The following end points were considered in this analysis: (1) the probability of virological success, (2) the probability of virological failure, (3) the immunologic response in relation to the virological response, (4) the proportion of drug resistance and the resistance pattern among patients with virological failure, (5) the probability of switching to second-line HAART, and (6) virological response after switching to second-line HAART.

For patients who experienced virological failure, results of genotypic drug resistance tests were considered in the analysis if the tests were performed in a window of 6 months before and 12 months after virological failure. It was assumed that patients with virological suppression did not have drug resistance. As results of the resistance tests were available for only two-thirds of the patients with virological failure, a multiple-imputation method was used to estimate the probability of resistance from the full data set.16,17 VL and resistance tests were performed intermittently resulting in interval-censored data that were analyzed using the interval censoring framework.18 The cumulative probabilities of virological success, virological failure, and resistance over time were computed with a nonparametric estimator derived from Turnbull algorithm.19 A bootstrap resampling procedure was used to compute robust confidence intervals.20 Variables assessed as potential risk factors of virological failure or resistance included those measured at baseline (age, sex, CDC stage, CD4-cell count, and pre-HAART VL), the type of HAART regimen received (PI- or NNRTI-based) and the average adherence level. The relationship between covariates, the occurrence of virological failure and drug resistance, was assessed using generalized linear models.21 Nonlinear relationships were modeled using splines with generalized additive model models.22 Immunologic response before and after virological failure was assessed by comparing the CD4-cell count just before and then 6 months after virological failure between patients who experienced virological failure, and control patients matched for follow-up duration, sex, age, baseline clinical stage, and baseline CD4-cell count. All statistical analyses were performed with the open source software R.23

Back to Top | Article Outline

RESULTS

Study Population

A total of 366 patients were included in the study after excluding the following: 18 patients who were receiving a dual-therapy regimen, 48 patients who had been followed up for <6 months, and 12 patients who had no VL results after baseline. The mortality rate in these excluded patients was high (60%). The median follow-up duration on first-line HAART was 69 months [inter quartile range (IQR) = 42–99]. NNRTI-based regimens were more common than PI-based ones [228 (62%) patients receiving an NNRTI vs. 138 (38%) patients receiving a PI]. Compared with patients started with an NNRTI, those receiving a PI had been enrolled earlier in the cohort (88% of them had been enrolled before 2001 vs. 64% of those receiving an NNRTI, P < 0.001) and had lower CD4-cell count (P < 0.001). The other characteristics of the study population and the other drugs received are provided in Table 1.

Table 1
Table 1
Image Tools
Back to Top | Article Outline
Virological Response
Initial Virological Response

A total of 324 (89%) patients achieved virological success. The probability of virological success at 6, 12, and 24 months was 78% (95% CI: 74 to 82), 86% (95% CI: 83 to 89), and 89% (95% CI: 86 to 92), respectively (Fig. 1A). In adjusted analysis, the probability of virological success was lower in patients receiving a PI-based regimen [relative risk (RR) = 0.57, 95% CI: 0.44 to 0.74] and was higher in older patients (RR = 1.19, 95% CI: 1.11 to 1.27). Of the 42 (11%) patients who did not achieve initial virological success, 23 (55%) died. The most common cause of death was tuberculosis (6 patients). Baseline resistance tests were available for 16 (38%) of these 42 patients, and no primary drug resistance mutation was found. Receiving a PI-based regimen and being younger were the 2 independent risk factors for not achieving virological success (odds ratio = 2.23, 95% CI: 1.10 to 4.59 for PI compared with NNRTI and 0.65, 95% CI: 0.44 to 0.98 per 10-year increase). Patients who did not achieve virological success had significantly lower adherence than those who did (P = 0.005).

Figure 1
Figure 1
Image Tools
Back to Top | Article Outline
Virological Failure After Initial Virological Success

The 324 patients who achieved initial virological success were followed up for a total of 1530 person-years until censoring or first virological failure. Of these, 79 (24%) experienced virological failure, and 127 (39%) patients a single increase of their VL ≥1000 copies/mL not confirmed by a consecutive test. The overall cumulative risk of virological failure was 5% (95% CI: 3 to 7) at 12 months, 16% (95% CI: 13 to 20) at 24 months, and 25% (95% CI: 21 to 30) at 60 months (Fig. 1B). Restricting the subset to patients who received an NNRTI-based regimen, this risk was 3% (95% CI: 1 to 5) at 12 months, 12% (95% CI: 9 to 17) at 24 months, 16% (95% CI: 12 to 21) at 48 months, and 18% (95% CI: 13 to 23) at 60 months. If the definition of virological failure was changed to any VL ≥1000 copies/mL, the estimated risk increased to 7% at 12 months, 22% at 24 months, and 39% at 60 months. In adjusted analysis, the risk of virological failure was higher in patients who were receiving a PI-based regimen, were younger, and had a mean adherence <80% (Table 2). When adherence was considered as a continuous variable, a nonlinear relationship with the risk of virological failure was found (Fig. 2, P = 0.05).

Table 2
Table 2
Image Tools
Figure 2
Figure 2
Image Tools

The mean CD4-cell count at virological failure was 340 cells/mm3 (IQR = 178–481) versus 410 cells/mm3 (IQR = 257–525) in patients with no virological failure and matched for follow-up duration, age, sex, baseline CD4, and clinical stage (P < 0.001). The mean change in CD4-cell count over the first 6 months after virological failure was also poorer compared with matched control patients (+4 cells/mm3 versus +30 cells/mm3 in controls, P = 0.04). Interestingly, only 28 patients (35%) met the WHO criteria for immunologic failure at the time of virological failure.

Back to Top | Article Outline
Drug Resistances

The results of a genotypic resistance test performed before HAART initiation were available for 48 (60%) of those who experienced virological failure. Only one drug resistance mutation was detected (resistance to lamivudine). Conclusive genotypic resistance tests were available for 53 (67%) patients (31 patients receiving a PI-based regimen and 22 an NNRTI). Among these 53 individuals, 32 (60%) were at least resistant to one drug (77% and 48% of those receiving an NNRTI and a PI-based regimen, respectively). Seventeen (77%) NNRTI mutations and 7 (23%) PI mutations were found in patients receiving these drugs. Twenty-one patients (40%) had dual-class resistances. The most common resistance to NRTIs was the mutation M184V to lamivudine (n = 24, 45%). A summary of the different resistances detected is given in Figure 3 and Figure S1 (see Supplemental Digital Content, http://links.lww.com/QAI/A365). It should be noted that no resistance mutation was found in patients with a single VL ≥1000 copies/mL.

Figure 3
Figure 3
Image Tools

At the population level, the estimated cumulative risk of resistance to any drug was 3% (95% CI: 1 to 5) at 12 months, 11% (95% CI: 8 to 15) at 24 months, 16% (95% CI: 13 to 21) at 48 months, and 18% (95% CI: 13 to 21) at 60 months (Fig. 1C). The risk of resistance to any drug was positively associated with AIDS history at baseline and negatively associated with age, baseline CD4-cell count, and adherence (Table 2). As displayed in Figure 2, the relationship between the risk of resistance and adherence level was nonlinear (P = 0.05).

Back to Top | Article Outline
Outcomes After Switching to Second-Line HAART

Forty-eight (60%) patients with virological failure and 17 (40%) with no virological suppression were switched to second-line HAART. In the former, the median time between the first VL ≥1000 copies/mL and the treatment switch was 36 months (IQR = 18–54). This delay was larger for the first patients enrolled in the cohort (median delay was 33 months for those enrolled before 2001 versus 18 months for those enrolled after 2001, P < 0.01).

After excluding 7 patients who had been followed up for <6 months and/or had no VL measurement after switching to a second-line regimen and 5 others who achieved an undetectable VL before switching, 53 patients were eventually included in the subanalysis of virological response to second-line HAART. Their regimens included an NNRTI in 30 (57%) patients or a PI otherwise. Among the latter, lopinavir boosted with ritonavir, indinavir, and nelfinavir were used by 39%, 48%, and 13%, respectively. The median follow-up duration for these 53 patients was 45 months, and the median time on first-line HAART was 56 months (IQR = 44–70). Their median CD4-cell count and log10 VL just before or at treatment switch were 239 cells/mm3 (IQR = 103–332) and 4.47 log10 copies/mL (IQR = 4.04–5.00), respectively. Of these 53 patients, 43 (81%) achieved viral suppression <500 copies/mL within a median time of 6 months. All those who did not achieve virological suppression were receiving an NNRTI-based second-line regimen and 9 (90%) were documented as being resistant to at least one drug in their regimen before switching. After achieving virological suppression, 12 patients experienced a second episode of virological failure, which resulted in a cumulative risk of virological failure of 18% (95% CI: 8 to 28) at 6 months, 20% (95%CI: 10 to 30) at 12 months, and 27% (95% CI: 15 to 41) at 24 months (Fig. 1D). All of these patients (except one with no resistance data available) had dual-class resistances before or at the time of virological failure, and 8 (67%) of them were resistant to at least one of their second-line regimen drugs at virological failure. By contrast, their average adherence level was similar to that of patients who did not experience a second episode of virological failure (95% vs. 94.5%, P = 0.6).

Back to Top | Article Outline

DISCUSSION

In this study, using data from one of the first African cohorts of HIV-1–infected adults started on HAART, we were able to analyze together the virological outcomes for patients who were on first-line HAART for over >5 years and the virological response to second-line HAART. As the rollout of HAART in resource-limited countries continues, such results are important to inform calculations on the expected rate of virological failure and the effectiveness of second-line regimens.

We found that the overall virological response for patients on first-line HAART was good, with >80% of patients achieving virological success. This result is similar to those observed in other African and non-African settings.24–30 The risk of virological failure rose sharply during the first 24 months of HAART then leveled off. This result confirms the importance of monitoring the initial response to treatment more closely. Although the proportion of patients with virological failure estimated was dependent of the definition adopted, drug resistances were observed only when a VL ≥1000 copies/mL was found in 2 consecutives tests, which suggests that this definition might have more clinical significance. Restricted to the first 2 years of follow-up, the estimated proportion of people with resistance to at least one drug in this cohort was similar to those from studies with intensive monitoring (more frequently than every 2 weeks) reported by Gupta et al.31 Over a longer follow-up time (up to 5 years), we found that the cumulative risk of virological failure and resistance was lower than or similar to those reported in high-resource countries.14,29,32–35 However, because of the delay between virological failure and treatment switching, it is likely that resistances' mutations were actually more frequent when the patients were started on second-line HAART. This delay may be attributable to several factors. First of all, the patients included in this cohort were among the first patients started on HAART in Senegal, and the number of drugs available at the beginning of cohort was very limited. Second, although VL and CD4-cell count were used for the monitoring, they were measured only twice a year. This resulted in a delay before a confirmatory VL was obtained, and a decision of switch to a second-line regimen made.

In 1998, indinavir was the only PI-based regimen available. Because it was poorly tolerated and several pills had to be taken daily, impaired adherence and consequently, early virological failure or switches were commonly observed in patients receiving this regimen. Moreover, stavudine that was used in most regimen of this cohort resulted also in frequent adverse events.36 Although our results should be cautiously interpreted, as patients who receive were more likely to be sicker compared with those who receive an NNRTI, they are in line with the results from the PEARLS (ACTG A5175) trial.37 However, it should be noted that despite the higher rate of virological failures, proportionally less resistance mutations were detected in patients receiving a PI-based regimen. The nonlinear relationship between adherence to PI-based regimens and the risk of virological failure or drug resistance found in this study—which is similar to results from other studies34,38—suggests a greater robustness of PI-based regimens to drug resistance at low to moderate levels of adherence, although it is important to note that pills count is a very imperfect proxy for adherence.39 Therefore, antiretroviral regimens based on boosted PI regimens which are more efficient and better tolerated compared with their nonboosted PI counterparts, might be a better alternative to NNRTI-based regimens when adherence is imperfect and when VL monitoring is infrequent, as is the case in many HIV programs in resource-limited settings.40

Outcomes for second-line HAART were not as good as those observed for first-line HAART. Although the proportion of virological success in the former was only slightly lower than that in the latter, the probability of failure while receiving the former was more than twice as high. These results from a cohort of patients from West Africa fall within the range of those reported in a recent meta-analysis by Ajose et al.41 Likewise, we found that virological failure while receiving second-line regimens occurred early on after switching. An important concern is that virological failure occurred in a context of multiple resistances, which underscores the necessity of improving access to third-line regimens in resource-limited settings.

To our knowledge, this is the first study in a resource-limited setting to provide estimates of the risk of virological failure and drug resistance over such a long period. Moreover, because the data were prospectively collected, our estimates are less prone to bias compared with those from cross-sectional studies.33,42 However, several study limitations should be noted when interpreting our results. First, this study had a small population size limiting the precision of our estimates especially over the long term. A relatively large amount of data was missing, including genotypic tests for one-third of those who experienced virological failure. Such a situation is not uncommon,14,17,33 and we used a multiple-imputation approach to account for the missing data.17 Nevertheless, it is important to keep in mind the assumptions made with such a statistical approach: first, it was assumed that all patients with VL <1000 copies/mL had no resistance mutation. Second, multiple imputation only works under the assumption that data were missing at random, conditionally on the observed variables.16 Although it cannot actually be checked, this assumption seems reasonable as most of the tests were missing because of logistic problems.

In conclusion, this study shows good virological outcomes for patients on first-line HAART for over >5 years. However, outcomes for second-line HAART were not as good and most of the virological failure observed with second-line regimens occurred in the context of multiple resistances, emphasizing the importance of intensive monitoring and early adherence support, and the need to improve access to and availability of third-line regimens.

Back to Top | Article Outline
ACKNOWLEDGMENT

The authors are grateful to Jude Sweeney for his assistance in editing this manuscript.

The ANRS 1215 study group: I. Ndoye (Multisectorial AIDS Program, Dakar, Senegal), Alice Desclaux, E. Delaporte, J. F. Etard, C. Laurent, B. Taverne, M. Peteers, P. De Beaudrap (UMI 233, Research Institute for Development (IRD)/University of Montpellier, Dakar, Senegal and Montpellier, France), M. Basty Fall, A. B. Dieng, A. Diouf, C. Massidi, A. Sarr, L. Zié (Regional Research and Training Center for HIV/AIDS, Fann University Teaching Hospital, Dakar, Senegal), I. Lanièce, M. Meynard (French Ministry of Foreign Affairs, Dakar, Senegal), I. Ndiaye, A. Ndir, C. T. Ndour, C. S. Senghor, P. S. Sow, (Department of Infectious Diseases, Fann University Teaching Hospital, Dakar, Senegal), N. F. Ngom Guèye, (Ambulatory Care Unit-Red-Cross, Fann University Teaching Hospital, Dakar, Senegal), K. Ba Fall, P. M. Guèye, (Military Hospital of Dakar, Senegal), S. Mboup, N. C. Touré Kane (Le Dantec University Teaching Hospital, Virology and Bacteriology Laboratory, Dakar, Senegal), K. Diop, B. Ndiaye (Central Pharmacy, Fann University Teaching Hospital, Dakar, Senegal).

Back to Top | Article Outline

REFERENCES

1. Desclaux A, Lanièce I, Ndoye I, et al., eds. The Senegalese Antiretroviral Drug Access Initiative. An Economic, Social, Behavioural and Biomedical Analysis. Paris: France: ANRS, UNAIDS, WHO; 2002.

2. Laurent C, Diakhate N, Gueye NF, et al.. The Senegalese government's highly active antiretroviral therapy initiative: an 18-month follow-up study. AIDS. 2002;16:1363–1370.

3. Weidle PJ, Malamba S, Mwebaze R, et al.. Assessment of a pilot antiretroviral drug therapy programme in Uganda: patients' response, survival, and drug resistance. Lancet. 2002;360:34–40.

4. Seyler C, Anglaret X, Dakoury-Dogbo N, et al.. Medium-term survival, morbidity and immunovirological evolution in HIV-infected adults receiving antiretroviral therapy, Abidjan, Cote d'Ivoire. Antivir Ther. 2003;8:385–393.

5. UNAIDS. Global report: UNAIDS report on the global AIDS epidemic 2010. Available at: http://www.unaids.org/globalreport/Global_report.htm. Accessed December 2011.

6. Etard JF, Ndiaye I, Thierry-Mieg M, et al.. Mortality and causes of death in adults receiving highly active antiretroviral therapy in Senegal: a 7-year cohort study. AIDS. 2006;20:1181–1189.

7. Braitstein P, Brinkhof MW, Dabis F, et al.. Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet. 2006;367:817–824.

8. Keiser O, Chi BH, Gsponer T, et al.. Outcomes of antiretroviral treatment in programmes with and without routine viral load monitoring in Southern Africa. AIDS. 2011;25:1761–1769.

9. Keiser O, Tweya H, Boulle A, et al.. Switching to second-line antiretroviral therapy in resource-limited settings: comparison of programmes with and without viral load monitoring. AIDS. 2009;23:1867–1874.

10. Hosseinipour MC, van Oosterhout JJ, Weigel R, et al.. The public health approach to identify antiretroviral therapy failure: high-level nucleoside reverse transcriptase inhibitor resistance among Malawians failing first-line antiretroviral therapy. AIDS. 2009;23:1127–1134.

11. Landman R, Canestri A, Thiam S. First evaluation of d4T, ddI and EFZ in antiretroviral naive patients in Senegal: ANRS 1206/IMEA 012 study. Paper presented at: XIIth International Conference on AIDS and STDs in Africa; December 9-13, 2001; Ouagadougou, Africa.

12. Landman R, Schiemann R, Thiam S, et al.. Once-a-day highly active antiretroviral therapy in treatment-naive HIV-1-infected adults in Senegal. AIDS. 2003;17:1017–1022.

13. Landman R, Poupard M, Diallo M, et al.. Tenofovir-emtricitabine-efavirenz in HIV-I-infected adults in Senegal: a 96-week pilot trial in treatment-naive patients. J Int Assoc Physicians AIDS Care (Chic). 2009;8:379–384.

14. Phillips AN, Dunn D, Sabin C, et al.. Long term probability of detection of HIV-1 drug resistance after starting antiretroviral therapy in routine clinical practice. AIDS. 2005;19:487–494.

15. Djoko CF, Rimoin AW, Vidal N, et al.. High HIV type 1 group M pol diversity and low rate of antiretroviral resistance mutations among the uniformed services in Kinshasa, Democratic Republic of the Congo. AIDS Res Hum Retroviruses. 2011;27:323–329.

16. Little RJA, Rubin DB. Statistical Analysis With Missing Data. Hoboken, NJ: Wiley; 2002.

17. Abraham AG, Lau B, Deeks S, et al.. Missing data on the estimation of the prevalence of accumulated human immunodeficiency virus drug resistance in patients treated with antiretroviral drugs in North America. Am J Epidemiol. 2011;174:727–735.

18. Klein J, Moeschberger M. Survival Analysis. Techniques for Censored and Truncated Data. 2nd ed. New York, NY: Springer; 2003.

19. Turnbull B. The empirical distribution function with arbitrarily grouped, censored and truncated data. J R Stat Soc. 1976;38:290–295.

20. Efron B, Tibshirani R. An Introduction to the Bootstrap. New York, NY: Chapman & Hall; 1993.

21. Carstensen B. Regression models for interval censored survival data: application to HIV infection in Danish homosexual men. Stat Med. 1996;15:2177–2189.

22. Wood SN. Generalized Additive Models: An Introduction With R. New York, NY: Chapman & Hall/CRC; 2006.

23. R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2009.

24. Ferradini L, Jeannin A, Pinoges L, et al.. Scaling up of highly active antiretroviral therapy in a rural district of Malawi: an effectiveness assessment. Lancet. 2006;367:1335–1342.

25. Laurent C, Kouanfack C, Koulla-Shiro S, et al.. Long-term safety, effectiveness and quality of a generic fixed-dose combination of nevirapine, stavudine and lamivudine. AIDS. 2007;21:768–771.

26. Laurent C, Kouanfack C, Laborde-Balen G, et al.. Monitoring of HIV viral loads, CD4 cell counts, and clinical assessments versus clinical monitoring alone for antiretroviral therapy in rural district hospitals in Cameroon (Stratall ANRS 12110/ESTHER): a randomised non-inferiority trial. Lancet Infect Dis. 2011;11825–833.

27. Braitstein P, Brinkhof MW, Dabis F, et al.. Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet. 2006;367:817–824.

28. Barth RE, van der Loeff MF, Schuurman R, et al.. Virological follow-up of adult patients in antiretroviral treatment programmes in sub-Saharan Africa: a systematic review. Lancet Infect Dis. 2010;10:155–166.

29. Ledergerber B, Egger M, Opravil M, et al.. Clinical progression and virological failure on highly active antiretroviral therapy in HIV-1 patients: a prospective cohort study. Swiss HIV Cohort Study. Lancet. 1999;353:863–868.

30. Paredes R, Mocroft A, Kirk O, et al.. Predictors of virological success and ensuing failure in HIV-positive patients starting highly active antiretroviral therapy in Europe: results from the EuroSIDA study. Arch Intern Med. 2000;160:1123–1132.

31. Gupta RK, Hill A, Sawyer AW, et al.. Virological monitoring and resistance to first-line highly active antiretroviral therapy in adults infected with HIV-1 treated under WHO guidelines: a systematic review and meta-analysis. Lancet Infect Dis. 2009;9:409–417.

32. Mocroft A, Ruiz L, Reiss P, et al.. Virological rebound after suppression on highly active antiretroviral therapy. AIDS. 2003;17:1741–1751.

33. Pillay D, Green H, Matthias R, et al.. Estimating HIV-1 drug resistance in antiretroviral-treated individuals in the United Kingdom. J Infect Dis. 2005;192:967–973.

34. Harrigan PR, Hogg RS, Dong WW, et al.. Predictors of HIV drug-resistance mutations in a large antiretroviral-naive cohort initiating triple antiretroviral therapy. J Infect Dis. 2005;191:339–347.

35. Richman DD, Morton SC, Wrin T, et al.. The prevalence of antiretroviral drug resistance in the United States. AIDS. 2004;18:1393–1401.

36. Mercier S, Gueye NF, Cournil A, et al.. Lipodystrophy and metabolic disorders in HIV-1-infected adults on 4- to 9-year antiretroviral therapy in Senegal: a case-control study. J Acquir Immune Defic Syndr. 2009;51:224–230.

37. Campbell T, Smeaton L, De Grutolla V. PEARLS (ACTG A5175): a multinational study of didanosine-EC, emtricitabine and atazanavir vs. co-formulated zidovudine/lamivudine and efavirenz for initial treatment of HIV-1 infection. Paper presented at: XVII International AIDS Conference 2008; August 3-8, 2008; Mexico City, Mexico.

38. King MS, Brun SC, Kempf DJ. Relationship between adherence and the development of resistance in antiretroviral-naive, HIV-1-infected patients receiving lopinavir/ritonavir or nelfinavir. J Infect Dis. 2005;191:2046–2052.

39. Gardner EM, Burman WJ, Steiner JF, et al.. Antiretroviral medication adherence and the development of class-specific antiretroviral resistance. AIDS. 2009;23:1035–1046.

40. Adlington R, Richens J, Shahmanesh M. First-line antiretroviral therapy in resource-limited settings: time to reconsider? J Infect Dis. 2009;199:1407; Author reply–8.

41. Ajose O, Mookerjee S, Mills EJ, et al.. Treatment outcomes of patients on second-line antiretroviral therapy in resource-limited settings: a systematic review and meta-analysis. AIDS. 2012;26:929–938.

42. Harrigan PR, Wynhoven B, Brumme ZL, et al.. HIV-1 drug resistance: degree of underestimation by a cross-sectional versus a longitudinal testing approach. J Infect Dis. 2005;191:1325–1330.

Keywords:

HIV; antiretroviral therapy; virological response; drug resistance; sub-Saharan Africa

Supplemental Digital Content

Back to Top | Article Outline

© 2013 Lippincott Williams & Wilkins, Inc.

Login

Search for Similar Articles
You may search for similar articles that contain these same keywords or you may modify the keyword list to augment your search.