Background: Although tenofovir (TDF) is a common component of antiretroviral therapy (ART), recent evidence suggests inferior outcomes when it is combined with nevirapine (NVP).
Methods: We compared outcomes among patients initiating TDF + emtricitabine or lamivudine (XTC) + NVP, TDF + XTC + efavirenz (EFV), zidovudine (ZDV) + lamuvidine (3TC) + NVP, and ZDV + 3TC + EFV. We categorized drug exposure by initial ART dispensation by a time-varying analysis that accounted for drug substitutions and by predominant exposure (>75% of drug dispensations) during an initial window period. Risks for death and program failure were estimated using Cox proportional hazard models. All regimens were compared with ZDV + 3TC + NVP.
Results: Between July 2007 and November 2010, 18,866 treatment-naive adults initiated ART: 18.2% on ZDV + 3TC + NVP, 1.8% on ZDV + 3TC + EFV, 36.2% on TDF + XTC + NVP, and 43.8% on TDF + XTC + EFV. When exposure was categorized by initial prescription, patients on TDF + XTC + NVP [adjusted hazard ratio (AHR): 1.45; 95% confidence interval (CI): 1.03 to 2.06] had a higher post–90-day mortality. TDF + XTC + NVP was also associated with an elevated risk for mortality when exposure was categorized as time-varying (AHR: 1.51; 95% CI: 1.18 to 1.95) or by predominant exposure over the first 90 days (AHR: 1.91, 95% CI: 1.09 to 3.34). However, these findings were not consistently observed across sensitivity analyses or when program failure was used as a secondary outcome.
Conclusion: TDF + XTC + NVP was associated with higher mortality when compared with ZDV + 3TC + NVP but not consistently across sensitivity analyses. These findings may be explained in part by inherent limitations to our retrospective approach, including residual confounding. Further research is urgently needed to compare the effectiveness of ART regimens in use in resource-constrained settings.
*Centre for Infectious Disease Research in Zambia, Lusaka, Zambia
†Department of Obstetrics and Gynecology, University of Alabama at Birmingham School of Medicine, Birmingham, AL
‡Zambian Ministry of Health, Lusaka, Zambia
§Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD
The work reported herein was supported in part by the President's Emergency Plan for AIDS Relief through a multicountry grant to the Elizabeth Glaser Pediatric AIDS Foundation from the US Department of Health and Human Services and Centers for Disease Control and Prevention's Global AIDS Program (cooperative agreement U62/CCU12354). Additional investigator salary or trainee support was provided by the National Institutes of Health (D43-TW001035, P30-AI027767, R24-TW007988) and a Clinical Scientist Development Award from the Doris Duke Charitable Foundation (2007061).
The funding agencies played no role in study design, data collection, data analysis, or article writing.
The findings and conclusions included herein are solely the responsibility of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention.
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 HTML and PDF versions this article on the journal's Web site (www.jaids.com).
Correspondence to: Dr Benjamin H. Chi, MD, MSc, Plot 1275 Lubutu Road, PO Box 34681, Lusaka, Zambia (e-mail: firstname.lastname@example.org).
Received April 9, 2011
Accepted July 19, 2011
Tenofovir disoproxil fumarate (TDF) is an important component of antiretroviral therapy (ART) worldwide. Numerous studies have demonstrated its efficacy, durability, favorable safety profile, and high genetic barrier for antiretroviral drug resistance.1–4 Over the past decade, its use has increased significantly in North America and Europe,5,6 where it is commonly recommended as part of first-line therapy.7,8
The original clinical trials of TDF demonstrated efficacy when used with efavirenz (EFV), a nonnucleoside reverse transcriptase inhibitor with once-daily dosing.1,2 However, EFV is expensive, and this may present economic challenges in areas with severe resource constraint.9,10 In these settings, it is more likely that TDF would be paired with nevirapine (NVP) when possible, a cheaper nonnucleoside reverse transcriptase inhibitor with efficacy similar to EFV as part of combination regimens.11
To date, ART regimens incorporating both TDF and NVP have only been evaluated in small clinical trials, but there is some suggestion that this combination may be associated with inferior virologic outcomes. Early interim analyses of 2 randomized studies—with 71 and 14 patients, respectively—found that patients on TDF-containing and NVP-containing ART had higher rates of treatment failure.12,13 Work by Scarsi et al14 demonstrated an increased risk for virologic failure [adjusted odds ratio (OR): 1.7; 95% confidence interval (CI): 1.3 to 2.3] when NVP-based regimens containing TDF were compared with analogous combinations with zidovudine (ZDV). Each of these studies had limitations (eg, small sample size, missing data), but the potential interaction between TDF and NVP is nevertheless cause for concern, especially in resource-constrained settings. In this report, we compared outcomes of treatment-naive adults initiating 1 of 4 different ART regimens, including combinations with TDF and NVP, in a setting with predominant subtype C HIV infection.
The ART program in Lusaka, Zambia, has been described in detail previously.15–20 Briefly, patients with known HIV infection are referred by health providers to 1 of 18 government facilities for long-term HIV care and treatment. They are screened for ART eligibility using CD4+ cell count and clinical disease staging. Over the analysis period, adults were deemed eligible and initiated treatment if they met the following criteria: CD4+ cell count of less than 200 cells per microliter, World Health Organization (WHO) stage 4 disease, or CD4+ cell count of less than 350 cells per microliter with WHO stage 3 disease.21 Patients on ART undergo an intensive visit schedule over their first 3 months to monitor adherence behaviors and early drug toxicities. Clinical visits are then spaced out to every 3–6 months. Those who miss scheduled appointments are identified and contacted through a follow-up home-visit program.22 Deaths among ART patients are reported to the clinic by family members or by local community health workers.
Preferred first-line ART regimens have evolved over time. When the Lusaka program was first implemented in 2004, the primary combinations were ZDV or stavudine (d4T) combined with lamivudine (3TC) and either NVP or EFV.15 In July 2007, the Ministry of Health introduced TDF—in combination with either 3TC or emtricitabine (FTC)—as a preferred nucleoside reverse transcriptase inhibitor backbone for first-line therapy.23 NVP is prescribed at 200 mg once daily for the first 2 weeks before escalation to twice-daily dosing. 3TC is generally prescribed as a twice-daily dose (150 mg), except when dispensed in coformulations with TDF in a once-a-day pill (300 mg), available starting in October 2009. Dosing schedules for ZDV (300 mg twice daily), d4T (30 mg twice daily), TDF (300 mg once daily), and EFV (600 mg once daily) were standardized across all regimen combinations.
At time of ART initiation, a patient's prescription is based on drug availability at the facility and any identified medical contraindications. For example, patients with anemia are not prescribed ZDV-containing regimens, and those with severe renal insufficiency (ie, creatinine clearance < 50 mL/min) do not start TDF-containing ART. Patients on tuberculosis cotreatment start regimens with EFV rather than NVP. The ART regimen prescribed at initiation is continued at subsequent visits unless there are signs of toxicity or evidence of treatment failure. Antiretroviral drugs are provided free-of-charge in the government program and dispensed at pharmacy visits every 1–3 months.
For the present analysis, we included treatment-naive adults (>16 years) initiating 1 of 4 ART regimens as follows: (1) ZDV + 3TC + NVP; (2) ZDV + 3TC + EFV; (3) TDF + XTC + NVP; and (4) TDF + XTC + EFV. (We considered 3TC and FTC to be equivalent and interchangeable, abbreviating them as “XTC” according to conventions set forth by the WHO.24) To minimize “confounding by indication,”25 we excluded patients who at baseline had a hemoglobin of less than 10 g/dL or a creatinine clearance of less than 50 mL/min. Individuals with known tuberculosis at time of ART initiation were also excluded.
We considered 2 outcomes: mortality and “program failure.” Consistent with our previous work,23 we further categorized mortality as overall death (ie, through entire follow-up period), death within the first 90 days, and death at or after 90 days. Using the same time conventions, we created a composite program failure outcome that comprises mortality, program withdrawal (eg, transfer outside of Lusaka, treatment cessation), and follow-up loss (ie, patients who are more than 60 days late for their most recent clinical or pharmacy visit26). Similar to previous studies,23,27 our primary analytical approach categorized patients according to their initial drug dispensation. We fit Kaplan–Meier curves to determine the time to event in unadjusted analyses; we then performed multivariable Cox proportional hazards regression to account for the contribution of potential confounders. Across all analyses, ZDV + 3TC + NVP was used as the reference group.
In secondary analyses, we utilized other approaches for categorizing drug exposure. First, we considered regimen allocation as a “time-varying” covariate, thus attributing an event to the ART combination the patient was taking at the time of death or program failure. Such an approach may be necessary to identify culprit exposures among patients who undergo single-drug substitutions of their regimens.23 We recognize, however, that such an approach risks misclassification in situations where death results from complications of a recently replaced drug (eg, toxicity, clinical progression of disease). We therefore performed 2 sensitivity analyses using “lag times” of 7 days and 30 days; in these, mortality is attributed to the drug exposure active before an event. Patients whose prescription was changed to a regimen other than the 4 studied in this analysis were censored at time of switch. Second, we performed a “predominant exposure” analysis, where we considered only patients who had been on a single regimen for at least 75% of the time over the first 90 days. Those who did not meet this criterion were excluded. We then examined subsequent mortality and program failure in the 180 days after the initial exposure window based on these allocations. Analogous analyses were performed examining predominant exposure over the first 180 days and the first 365 days, with mortality and program failure measured in the 180 days after these initial window periods.
All analyses were adjusted for age, sex, CD4+ cell count, clinical disease stage, body mass index, hemoglobin, and serum creatinine at time of treatment initiation. To estimate adherence, we measured the medication possession ratio (MPR). MPR is calculated using pharmacy refill data and measures the proportion of days since ART initiation that a patient has had drugs on hand and available for ingestion.17,28 In our initial dispensation analysis, adherence (over the first 90 days) was only included in our ≥90 day analysis; we did not include adherence <90 day analysis because of its short duration of measurement and its limited impact on outcomes. None of the time-varying analyses included adherence because of the variable time windows by which it would be measured. In the predominant exposure analysis, we calculated MPRs over the initial window period (ie, 90 days, 180 days, 365 days) and included them in the corresponding postwindow analyses. All analyses were performed using SAS version 9.13 (SAS Institute, Cary, NC). Use of these routinely collected data was approved by the ethical review committees at the University of Zambia (Lusaka, Zambia) and University of Alabama at Birmingham (Birmingham, AL).
Between July 1, 2007, and November 1, 2010, a total of 38,506 treatment-naive adults started 1 of the 4 ART regimens. Of these, 19,640 (51%) were excluded because of anemia, renal insufficiency, missing baseline examinations, and/or known tuberculosis coinfection. Of the remaining 18,866 included in the analysis, 3431 (18.2%) started ZDV + 3TC + NVP; 335 (1.8%) started ZDV + 3TC + EFV; 6825 (36.2%) started TDF + XTC + NVP; and 8275 (43.8%) started TDF + XTC + EFV (Fig. 1). Among the 15,100 who started a TDF-based regimen, 12,934 (85.7%) were concomitantly prescribed FTC and, 2166 (14.3%) were prescribed 3TC. For the overall cohort, median follow-up time was 403 days (interquartile range: 166–731). As of November 1, 2010, 13,095 (69.4%) remained alive and active in care, whereas 910 (4.8%) had died, 1090 (5.8%) had formally withdrawn from the program, and 3771 (20.0%) were more than 60 days late for their last scheduled visit.
We compared basic demographic and medical characteristics according to initial ART regimen, the details of which are shown in Table 1. Patients on the TDF-based regimens had lower median CD4+ cell count (157 vs. 186 cells/uL; P < 0.01), lower median body mass index (20.2 vs. 21.7; P < 0.01), and higher proportion with clinical stage 3 and 4 disease (52.6% vs. 35.4%; P < 0.01) at time of ART initiation when compared with those on ZDV-based regimens. A higher proportion of men started a TDF-based regimen when compared with ZDV-based regimens (46.4% vs. 21.7%; P < 0.01).
Initial Dispensation Analysis
In our primary analysis, patients' drug exposure was categorized according to their initial drug dispensation. Lower mortality was observed among those in the ZDV + 3TC + NVP group when compared with the other 3 ART regimens (see Supplemental Digital Content 1, http://links.lww.com/QAI/A222, showing Kaplan–Meier analysis). When compared with the ZDV + 3TC + NVP in multivariable analysis, TDF + XTC + NVP [adjusted hazard ratio (AHR): 1.45; 95% CI: 1.03 to 2.06] was associated with higher mortality at or after 90 days. This finding, however, was no longer statistically significant in analysis of overall mortality or in analyses of program failure (Table 2).
We considered ART regimen as a time-varying covariate in secondary analysis. When we examined our mortality outcome with no lag (ie, outcome was attributed to the regimen taken at time of event), exposure to TDF + XTC + NVP (AHR: 1.51; 95% CI: 1.18 to 1.95), TDF + XTC + EFV (AHR: 2.10; 95% CI: 1.25 to 3.53), and ZDV + 3TC + EFV (AHR: 1.88; 95% CI: 1.18 to 3.01) conferred a higher hazard of death compared with ZDV + 3TC + NVP. These trends remained consistent when 7-day and 30-day lag periods were incorporated (Table 3). When we performed similar analyses using our program failure outcome, no differences were noted between regimens when no lag or 7-day lag periods were utilized. When a 30-day lag period was used, the hazards for ZDV + 3TC + EFV and TDF + XTC + EFV were significantly elevated compared with ZDV + 3TC + NVP. No significant differences were observed between TDF + XTC + NVP and ZDV + 3TC + NVP (Table 3).
Predominant Exposure Analysis
We performed analyses that included only patients who had been on a single regimen for at least 75% of the time over the first 90 days (n = 12,951 overall), 180 days (n = 11,295 overall), and 365 days (n = 8306 overall). When compared with ZDV + 3TC + NVP, mortality seemed higher with each of the 3 regimens in our post–90-day analyses, although it failed to reach statistical significance with ZDV + 3TC + EFV. When we performed similar analyses using the outcome of program failure, there seemed to be a trend toward increased hazard for ZDV + 3TC + EFV in the post–90-day and post–365-day analyses (Table 4).
We analyzed data from a large African cohort to determine whether TDF + XTC + NVP was associated with compromised treatment responses among adults on ART. Because of the methodological challenges inherent to such an analysis—in particular, proper regimen assignment in the face of drug substitutions—we undertook 3 statistical approaches. When we categorized patients by drug exposure at time of death (ie, time-varying analysis), TDF + XTC + NVP was associated with higher mortality over ZDV + 3TC + NVP. However, such findings were inconsistent across other analytical approaches. When we categorized patients according to their initial drug dispensation, the increased risk for mortality associated with TDF + XTC + NVP was only evident after 90 days of follow-up. When we categorized patients by predominant regimen exposure over an initial window period—and then studied subsequent patient outcomes—an elevated hazard for death was only observed in the post-90 day analysis; no differences were noted in post–180-day or post–365-day analyses.
Thus far, the data linking TDF + XTC + NVP to poor patient outcomes have come mostly from small clinical trials. Rey et al12 first described this phenomenon after an interim analysis of the DAUFIN study revealed higher rates of 12-week virologic failure among patients on TDF + 3TC + NVP (8 of 36) compared with ZDV + 3TC + NVP (0 of 35). In another interim analysis, Lapadula et al13 found that, in combination with TDF and FTC, NVP was associated with higher virologic failure (3 of 7) compared with atazanavir/ritonavir (0 of 7). These clinical trials results are supported by observational data from Nigeria (n = 2987), where a nearly 2-fold increase in virologic failure was demonstrated when TDF + 3TC + NVP was compared with ZDV + 3TC + NVP (16.1% vs. 9.5%; P < 0.001).14 However, not all studies agree. Trial 2 of the OCTANE study (n = 500), for example, found no differences in virologic failure when women were randomized to receive either NVP or lopinavir/ritonavir in combination with TDF and FTC (14% vs. 14%; HR: 0.97; 95% CI: 0.6 to 1.6).29 In a retrospective analysis of 178 patients initiating TDF + FTC + NVP, Labarga et al30 found that only 5 (2.8%) met criteria for virologic failure over a median follow-up of 16 months.
Certain aspects of our analysis seem to support the superiority of ZDV + 3TC + NVP over TDF + XTC + NVP. However, we urge caution in this interpretation. Like the Nigeria analysis—which excluded nearly two-thirds of patients because of missing data, follow-up losses, and death14—we observed significant attrition over the course of follow-up. When these were incorporated in our outcome as part of program failure, differences in patient outcomes were attenuated or altogether absent. We attempted to minimize “confounding by indication” through careful cohort selection, but patients on TDF-based ART were still more likely to have markers of advanced HIV disease (eg, higher clinical staging, lower CD4+ cell counts, lower body mass index) than those on ZDV-based regimens. Although these factors were included in our multivariable models, data describing other important confounders, such as baseline viral load,12,13 were unavailable in our setting. It is also possible that the observed differences in treatment outcomes were related to combinations with the “third” ART component: FTC or 3TC. Although considered equivalent by WHO,24 studies by Svicher et al31 and Maserati et al32 suggest that development of antiretroviral drug resistance may be more commonly observed in patients on ART regimens incorporating TDF + 3TC when compared with those with TDF + FTC.
ZDV + 3TC + NVP was associated with better outcomes when compared with the 2 EFV-based regimens (ZDV + 3TC + EFV, TDF + XTC + EFV), an unexpected result given the demonstrated equivalence of EFV and NVP in clinical studies.11 This finding may be explained by selection biases inherent to these observational data. A significantly larger proportion of men started EFV-based ART and, in some studies, male gender has been associated with poor adherence and poor treatment outcomes.33–35 The increased mortality observed in our time-varying analyses may also be related to clinical indications for the EFV switch. For example, although patients with tuberculosis at enrollment were excluded from our present analysis, those who began without tuberculosis—but later contracted the disease—were not. These individuals, now at substantially increased risk for mortality, were switched from a NVP-based regimen to an EFV-based one. In the time-varying analysis, any subsequent deaths would be ascribed to the more recent ART combination. Reasons for drug substitutions (including drug toxicities and incident opportunistic infections) were not reliably collected in our observational database, and thus could not be considered.
Like many settings in sub-Saharan Africa, ascertainment of deaths in our cohort has been shown to be incomplete.22 A proportion of patients lost to follow-up may represent unrecognized deaths, especially in the early course of ART.36 Because of the observed imbalances in baseline medical characteristics among our comparison groups, the proportion of undocumented patient deaths likely varies. For this reason, we included program failure—a composite outcome that considers follow-up losses—in our secondary analyses. The impact of drug regimen on program failure seemed attenuated when compared with the mortality outcome; in only a few cases were the associations statistically significant. Although program failure has its own limitations as an outcome, these findings provide reassurance about the continued use of the different first-line ART regimens in Zambia.
In summary, data from this large observational cohort suggests that ZDV + 3TC + NVP may be associated with improved patient outcomes when compared with other ART regimens, including TDF + XTC + NVP. However, this finding was inconsistent across analytical approaches and may be the result of residual confounding. Further studies, including head-to-head clinical trials, are urgently needed to determine the comparative effectiveness of ART regimens currently used in resource-constrained settings. As HIV treatment programs in Africa move toward use of TDF as a first-line agent, a better understanding of regimen effectiveness—particularly in the context of other antiretroviral drugs—is paramount.
The authors acknowledge the Zambian Ministry of Health for consistent and high-level support of operations research in the context of HIV program expansion. We thank Andrew Westfall for his review of our study design and analysis plan.
1. Gallant JE, DeJesus E, Arribas JR, et al. Tenofovir DF, emtricitabine, and efavirenz vs. zidovudine, lamivudine, and efavirenz for HIV. N Engl J Med. 2006;354:251–260
2. Gallant JE, Staszewski S, Pozniak AL, et al. Efficacy and safety of tenofovir DF vs stavudine in combination therapy in antiretroviral-naive patients: a 3-year randomized trial. JAMA. 2004;292:191–201
3. Margot NA, Isaacson E, McGowan I, et al. Extended treatment with tenofovir disoproxil fumarate in treatment-experienced HIV-1-infected patients: genotypic, phenotypic, and rebound analyses. J Acquir Immune Defic Syndr. 2003;33:15–21
4. Nelson MR, Katlama C, Montaner JS, et al. The safety of tenofovir disoproxil fumarate for the treatment of HIV infection in adults: the first 4 years. AIDS. 2007;21:1273–1281
5. McKinnell JA, Willig JH, Westfall AO, et al. Antiretroviral prescribing patterns in treatment-naive patients in the United States. AIDS Patient Care STDS. 2010;24:79–85
6. Easterbrook PJ, Phillips AN, Hill T, et al. Patterns and predictors of the use of different antiretroviral drug regimens at treatment initiation in the UK. HIV Med. 2008;9:47–56
7. Clumeck N, Pozniak A, Raffi F. European AIDS Clinical Society (EACS) guidelines for the clinical management and treatment of HIV-infected adults. HIV Med. 2008;9:65–71
8. Thompson MA, Aberg JA, Cahn P, et al. Antiretroviral treatment of adult HIV infection: 2010 recommendations of the International AIDS Society-USA panel. JAMA. 2010;304:321–333
9. Hill A, Wood E. Balancing effectiveness and access to HIV treatment in the developing world. AIDS. 2007;21:361–363
10. Medecins Sans Frontieres. . Untangling the Web of Antiretroviral Price Reductions Available at: http://utw.msfaccess.org
. Accessed February 11, 2011
11. van Leth F, Phanuphak P, Ruxrungtham K, et al. Comparison of first-line antiretroviral therapy with regimens including nevirapine, efavirenz, or both drugs, plus stavudine and lamivudine: a randomised open-label trial, the 2NN Study. Lancet. 2004;363:1253–1263
12. Rey D, Hoen B, Chavanet P, et al. High rate of early virological failure with the once-daily tenofovir/lamivudine/nevirapine combination in naive HIV-1-infected patients. J Antimicrob Chemother. 2009;63:380–388
13. Lapadula G, Costarelli S, Quiros-Roldan E, et al. Risk of early virological failure of once-daily tenofovir-emtricitabine plus twice-daily nevirapine in antiretroviral therapy-naive HIV-infected patients. Clin Infect Dis. 2008;46:1127–1129
14. Scarsi K, Darin K, Rawizza H, et al.TDF-3TC-NVP is inferior to AZT-3TC-NVP in a large ART program in Nigeria [Abstract THPE0115]. 2010 Austria Vienna Presented at: 18th International AIDS Conference 2010
15. Stringer JS, Zulu I, Levy J, et al. Rapid scale-up of antiretroviral therapy at primary care sites in Zambia: feasibility and early outcomes. JAMA. 2006;296:782–793
16. Bolton-Moore C, Mubiana-Mbewe M, Cantrell RA, et al. Clinical outcomes and CD4 cell response in children receiving antiretroviral therapy at primary health care facilities in Zambia. JAMA. 2007;298:1888–1899
17. Chi BH, Cantrell RA, Zulu I, et al. Adherence to first-line antiretroviral therapy affects non-virologic outcomes among patients on treatment for more than 12 months in Lusaka, Zambia. Int J Epidemiol. 2009;38:746–756
18. Chi BH, Giganti M, Mulenga PL, et al. CD4+ response and subsequent risk of death among patients on antiretroviral therapy in Lusaka, Zambia. J Acquir Immune Defic Syndr. 2009;52:125–131
19. Mulenga LB, Kruse G, Lakhi S, et al. Baseline renal insufficiency and risk of death among HIV-infected adults on antiretroviral therapy in Lusaka, Zambia. AIDS. 2008;22:1821–1827
20. Cantrell RA, Sinkala M, Megazinni K, et al. A pilot study of food supplementation to improve adherence to antiretroviral therapy among food-insecure adults in Lusaka, Zambia. J Acquir Immune Defic Syndr. 2008;49:190–195
21. Zambian Ministry of Health. Antiretroviral Therapy for Chronic HIV Infection in Adults and Adolescents: New ART Protocols, May 2007. 2007 Lusaka, Zambia Printech Press
22. Krebs DW, Chi BH, Mulenga Y, et al. Community-based follow-up for late patients enrolled in a district-wide programme for antiretroviral therapy in Lusaka, Zambia. AIDS Care. 2008;20:311–317
23. Chi BH, Mwango A, Giganti M, et al. Early clinical and programmatic outcomes with tenofovir-based antiretroviral therapy in Zambia. J Acquir Immune Defic Syndr. 2010;54:63–70
24. World Health Organization. Antiretroviral Therapy for HIV Infection in Adults and Adolescents; Recommendations for a Public Health Approach—2010 Revision. 2010 Geneva, Switzerland WHO Press
25. Walker AM. Confounding by indication. Epidemiology. 1996;7:335–336
26. Chi BH, Cantrell RA, Mwango A, et al. An empirical approach to defining loss to follow-up among patients enrolled in antiretroviral treatment programs. Am J Epidemiol. 2010;171:924–931
27. Stringer J, Mulenga L, Giganti M, et al. Effectiveness of generic vs. proprietary first-line ARV regimens in a primary health care setting: Lusaka, Zambia [Abstract 611] 2009 Canada Montreal Paper presented at: 16th Conference on Retroviruses and Opportunistic Infections
28. Goldman JD, Cantrell RA, Mulenga LB, et al. Simple adherence assessments to predict virologic failure among HIV-infected adults with discordant immunologic and clinical responses to antiretroviral therapy. AIDS Res Hum Retroviruses. 2008;24:1031–1035
29. Lockman S, Hughes MD, McIntyre J, et al. Antiretroviral therapies in women after single-dose nevirapine exposure. N Engl J Med. 2010;363:1499–1509
30. Labarga P, Medrano J, Seclen E, et al. Safety and efficacy of tenofovir/emtricitabine plus nevirapine in HIV-infected patients. AIDS. 2010;24:777–779
31. Svicher V, Alteri C, Artese A, et al. Different evolution of genotypic resistance profiles to emtricitabine versus lamivudine in tenofovir-containing regimens. J Acquir Immune Defic Syndr. 2010;55:336–344
32. Maserati R, De Silvestri A, Uglietti A, et al. Emerging mutations at virological failure of HAART combinations containing tenofovir and lamivudine or emtricitabine. AIDS. 2010;24:1013–1018
33. Calmy A, Pinoges L, Szumilin E, et al. Generic fixed-dose combination antiretroviral treatment in resource-poor settings: multicentric observational cohort. AIDS. 2006;20:1163–1169
34. Chen SC, Yu JK, Harries AD, et al. Increased mortality of male adults with AIDS related to poor compliance to antiretroviral therapy in Malawi. Trop Med Int Health. 2008;13:513–519
35. 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
36. Brinkhof MW, Pujades-Rodriguez M, Egger M. Mortality of patients lost to follow-up in antiretroviral treatment programmes in resource-limited settings: systematic review and meta-analysis. PLoS One. 2009;4:e5790