Initiating patients on antiretroviral therapy at CD4 cell counts above 200 cells/μl is associated with improved treatment outcomes in South Africa
Fox, Matthew Pa,b,c,d; Sanne, Ian Mc; Conradie, Francescac; Zeinecker, Jennifere; Orrell, Catherinee; Ive, Prudencec; Rassool, Mohammedc; Dehlinger, Marjorief; van der Horst, Charlesg; McIntyre, Jamesh; Wood, Robine
aCenter for Global Health and Development, Boston University, Boston, Massachusetts, USA
bHealth Economics and Epidemiology Research Office, Johannesburg, South Africa
cFaculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
dDepartment of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA
eUniversity of Cape Town, Cape Town, South Africa
fNational Institute of Allergy and Infectious Diseases, NIH, Bethesda, Maryland
gUniversity of North Carolina, Chapel Hill, North Carolina, USA
hANOVA Health Institute, Johannesburg, South Africa.
Received 18 March, 2010
Revised 12 May, 2010
Accepted 25 May, 2010
Correspondence to Matthew P. Fox, Center for Global Health and Development, Boston University, Crosstown Center, 3rd Floor, 801 Massachusetts Avenue, Boston, MA 02118, USA. Tel: +1 617 414 1260; fax: +1 617 414 1261; e-mail: firstname.lastname@example.org
Objectives: To compare treatment outcomes by starting CD4 cell counts using data from the Comprehensive International Program of Research on AIDS-South Africa trial.
Design: An observational cohort study.
Methods: Patients presenting to primary care clinics with CD4 cell counts below 350 cells/μl were randomized to either doctor or nurse-managed HIV care and followed for at least 2 years after antiretroviral therapy (ART) initiation. Clinical and laboratory outcomes were compared by baseline CD4 cell counts.
Results: Eight hundred and twelve patients were followed for a median of 27.5 months and 36% initiated ART with a CD4 cell count above 200 cells/μl. Although 10% of patients failed virologically, the risk was nearly double among those with a CD4 cell count of 200 cells/μl or less vs. above 200 cells/μl (12.2 vs. 6.8%). Twenty-one deaths occurred, with a five-fold increased risk for the low CD4 cell count group (3.7 vs. 0.7%). After adjustment, those with a CD4 cell count of 200 cells/μl had twice the risk of death/virologic failure [hazard ratio 1.9; 95% confidence interval (CI), 1.1–3.3] and twice the risk of incident tuberculosis (hazard ratio 1.90; 95% CI, 0.89–4.04) as those above 200 cells/μl. Those with either a CD4 cell count of 200 cells/μl or less (hazard ratio 2.1; 95% CI, 1.2–3.8) or a WHO IV condition (hazard ratio 2.9; 95% CI, 0.93–8.8) alone had a two-to-three-fold increased risk of death/virologic failure vs. those with neither, but those with both conditions had a four-fold increased risk (hazard ratio 3.9; 95% CI, 1.9–8.1). We observed some decreased loss to follow-up among those initiating ART at less than 200 cells/μl (hazard ratio 0.79; 95% CI, 0.50–1.25).
Conclusion: Patients initiating ART with higher CD4 cell counts had reduced mortality, tuberculosis and less virologic failure than those initiated at lower CD4 cell counts. Our data support increasing CD4 cell count eligibility criteria for ART initiation.
With the increase in global funding for HIV/AIDS, the developing world has seen unprecedented access to lifesaving antiretroviral therapy (ART) over the past 5 years. Funds mandated toward rapidly scaling up access to ART have been successfully targeted and nearly four million people are now on ART . When large-scale treatment programs began, in most cases, treatment was limited to patients with advanced disease. The ideal time to initiate ART is currently unknown . Although guidelines for resource-rich environments currently recommend ART initiation at CD4 cell counts below 350 cells/μl [3,4], developing country guidelines recommended initiating ART at CD4 cell counts of 200 cells/μl or less in the absence of clinical disease until November 2009 when the WHO recommended initiating treatment at CD4 cell counts below 350 cells/μl [5,6]. As new evidence from resource-rich environments has accumulated, showing that starting ART at higher CD4 cell counts is associated with better treatment outcomes [7–9], programs in resource-limited settings, given limited resources, must make difficult choices about whether or not to raise initiating CD4 cell count thresholds to higher levels.
The debate about when to initiate treatment is difficult as ART is a lifelong treatment that has significant cost and can have significant side effects. On an individual level, decisions about when to initiate therapy must balance the potential medical benefits of initiating at higher CD4 cell counts  and reductions in HIV transmission  with the risk of toxicity and the costs associated with longer time on treatment. On a public health level, a decision about when to initiate ART must balance not only any expected population-level benefits of initiating treatment at higher CD4 cell counts with the cost implications of potentially increased demand for treatment if treatment thresholds are raised but also any possible cost savings associated with earlier treatment, including reduced hospitalization and treatment of opportunistic infections . The first step toward rationalizing decisions on when to initiate ART is to assess, using data from resource-limited settings, the likely treatment benefits that can be expected.
Recent evidence from the developed world suggests that starting ART at CD4 cell counts below 350 cells/μl improves treatment outcomes and decreases mortality compared with waiting until the CD4 cell count drops below 200 cells/μl [13–17], and the benefits may even begin when initiating at CD4 cell counts above 350 cells/μl , yet limited evidence from the developing world exists to inform policy . To date, only one study from a developing country has attempted to randomize patients to initiate ART at CD4 cell counts below 350 cells/μl compared with waiting until the CD4 cell count drops below 200 cells/μl. An interim analysis of the Comprehensive International Program of Research on AIDS (CIPRA)-Haiti trial [19,20] found that initiating ART at CD4 cell counts below 200 cells/μl was associated with a four-fold increased risk of mortality and a two-fold increased risk of incident tuberculosis (TB) compared with starting at a CD4 cell count between 200 and 350 cells/μl.
The recent changes in WHO guidelines have yet to be adopted globally . In order to support decision-making around when to initiate ART, we assessed the association between treatment outcomes and starting ART at higher CD4 cell counts using data collected as part of the Comprehensive International Program of Research on AIDS-South Africa (CIPRA-SA) randomized trial comparing nurse-monitored antiretroviral treatment with doctor-monitored treatment in South Africa .
The data for this study were collected as part of the CIPRA-SA trial, an unblinded, prospective, randomized controlled trial comparing nurse vs. doctor-monitored HIV care and demonstrated equivalence of the two monitoring strategies for treatment failure over 2 years [hazard ratio 1.09; 95% confidence interval (CI), 0.89–1.33] . The study enrolled 812 HIV-positive ART-naive patients of at least 16 years of age with a CD4 cell count of 350 cells/μl or less or prior AIDS-defining illness [Centers for Disease Control and Prevention (CDC) category B/C] at one of two sites in South Africa (Soweto, Johannesburg and Masiphumelele, Cape Town). All patients were managed under South African National Guidelines for HIV treatment and were given standard ART regimens consisting of lamivudine given with either zidovudine or stavudine and either efavirenz or nevirapine . A protease inhibitor-based regimen was used in a limited number of cases (N = 62) for women of childbearing potential with a CD4 cell count above 350 cells/μl. Patients were randomized 1: 1 to have their HIV care monitored by either a nurse or a clinical officer and were followed for a minimum of 96 weeks. Details of the CIPRA-SA trial can be found elsewhere .
Patient follow-up and data collection
Patients were seen at baseline and then returned for follow-up visits at weeks 0, 2, 4, 9, 12 and then every 12 weeks. At each visit, patients had a clinical examination, symptom screening for TB and a blood draw for laboratory testing, including CD4 cell count, viral load, hematology and biochemistry.
Although current guidelines in South Africa allow for initiation of ART for patients with CD4 cell counts of 200 cells/μl or less or WHO Stage IV condition , and because the CIPRA-SA study enrolled patients with a CD4 cell count of 350 cells/μl or less, we conducted a prospective cohort study assessing differences in treatment failure among those initiating ART at a CD4 cell count above 200 cells/μl and those initiating at 200 cells/μl or less.
Definition of study variables
The primary exposure was CD4 cell count above 200 vs. 200 cells/μl or less at ART initiation. CD4 cell count was measured at randomization in the main CIPRA-SA study and was assessed using CD4+ flow cytometry (FlowCount Fluorospheres; Beckman Coulter-Immunotech, Marseille, France).
We assessed the relation between starting CD4 cell count and three indicators of program failure: treatment failure (an indicator of death or failure to achieve or maintain viral suppression), incident TB and program failures (indicated by patients who leave care). Virologic failure was defined as either failure to reach a 1.5 log10 drop in viral load by 12 weeks on treatment or two consecutive viral loads of more than 1000 copies/ml within 1 month of each other after 24 weeks on treatment. We defined loss to follow-up (LTFU) as missing three or more consecutive study visits (in the main study shown as LTFU and defaulting clinic schedule); we did not include patients who voluntarily withdrew from the study, as these patients could remain in care just not on the study protocol.
To determine whether there were any association between toxicity-related outcomes and initiating treatment at higher CD4 cell counts, we examined the relation between initiating CD4 cell count and treatment-related toxicities. Details of the toxicities that occurred are given elsewhere  but included any toxicity which required discontinuation of the study regimen, with a resulting treatment interruption of more than 6 weeks.
For all analyses, person-time accrued from initiation of treatment to the date of the earliest of experiencing a treatment outcome (defined above), completion of 48 months of treatment, becoming LTFU (except in analyses in which LTFU was the outcome) or date of closing the dataset (20 January 2009).
All patients in the CIPRA-SA trial signed informed consent forms. The CIPRA-SA trial was approved by the Institutional Review Boards (IRB) of the University of the Witwatersrand and the University of Cape Town. The Boston University IRB gave approval for analysis of the data in a de-identified manner.
We compared differences between study groups by stratifying our data by baseline CD4 cell count group. We looked for crude associations between baseline predictors and treatment outcomes and compared groups using relative risks (RRs) and 95% CIs. We explored the relation between initiating CD4 cell count and treatment failure by describing the rate of treatment failure using crude Kaplan–Meier curves. We used Cox proportional hazards regression to model the relation between CD4 cell count at ART initiation and treatment failure. All models were adjusted for age, sex (stratified at baseline into men, pregnant women and nonpregnant women), study site and randomization group. We did not include postbaseline measures, as these may be influenced by baseline CD4 cell count. We looked for a dose response between higher CD4 cell count and treatment outcomes by fitting a model with finer categorizations of baseline CD4 cell count. Finally, we looked for interactions between CD4 cell count and other markers of immunosuppression at baseline (e.g. viral load, WHO stage and BMI).
Baseline characteristics of the 812 patients enrolled in the CIPRA-SA cohort stratified by baseline CD4 cell counts group are shown in Table 1. Patients were followed for a median of 27.5 months (interquartile range 13.8–33.1), with no differences by study group. As expected based on randomization, roughly half of those in each CD4 cell count group had nurse-monitored and half had doctor-monitored ART care. Median age was 32 years and more than two of three were women with no differences by CD4 cell count group. Prior ART use (typically for prevention of mother-to-child transmission) was balanced between CD4 cell count groups. Those in the low CD4 cell counts group were more likely to have nevirapine in their baseline regimen than efavirenz, whereas those in the higher CD4 cell counts group were more likely to have lopinavir–ritonavir.
Five hundred eighteen patients (64%) fell into the low CD4 cell counts group (≤200 cells/μl), whereas the remaining 294 patients (36%) were in the high CD4 cell count group (>200 cells/μl). Those in the low CD4 cell count group were more immunosuppressed at baseline as indicated by viral loads of at least 100 000 copies/ml (RR, 1.67; 95%CI, 1.43–1.95), WHO stage IV (RR, 2.32; 95% CI, 1.62–3.33) or CDC C (RR, 1.42; 95% CI, 1.16–1.73). Few patients had extremely low or high CD4 cell count; only 16% (85/518) of those in the low CD4 cell count group had a CD4 cell count below 50 cells/μl and only 16% (46/294) of those in the high CD4 cell counts group had a CD4 cell counts above 350 cells/μl.
Death and virologic failure
Treatment outcomes by CD4 cell count group are shown in Table 2. There were 21 deaths in the study (2.6%); however, in crude analyses, those with a baseline CD4 cell count of 200 cells/μl or less had a five-fold increased risk vs. those above 200 cells/μl (RR, 5.4; 95% CI, 1.3–23.0). Virologic failure occurred in 10% of the cohort, with the majority (84%) of these virologic failures based on two consecutive viral loads of above 1000 copies/ml and not based on failure to achieve a 1.5 log10 drop in viral load from baseline by 12 weeks (16%, 13/83). Those with a CD4 cell count of 200 cells/μl or less at baseline had nearly twice the crude risk of virologic failure as those above 200 cells/μl (RR, 1.79; 95% CI 1.10–2.90). The Kaplan–Meier curve of death or virologic failure presented in Fig. 1(a) shows that the difference between the two groups in death and virologic failure emerges mainly between 6 and 24 months on treatment.
Table 3 shows three different crude and adjusted models of the relation between baseline CD4 cell counts and virologic failure or death. We present three separate models that are identical except that they use different categorizations of CD4 cell count (models 1 and 2) or include an interaction between baseline WHO stage and CD4 cell count (model 3). Model 1, which uses the CD4 categories used previously (≤200 vs. >200 cells/μl), shows that after adjusting for age, sex and pregnancy, site, treatment arm and other indicators of immunosuppression, those with a baseline CD4 cell count of 200 cells/μl or less had twice the risk of virologic failure or death (hazard ratio, 1.94; 95% CI, 1.14–3.30). Having a baseline WHO stage IV (hazard ratio, 1.98; 95% CI, 1.18–3.33), a viral load above 100 000 vs. below 10 000 copies/ml (hazard ratio, 2.05; 95% CI, 0.71–5.89) and having a nelfinavir-based regimen (hazard ratio, 4.27; 95% CI, 1.17–15.6) were also predictive of virologic failure or death independent of CD4 cell counts.
In Model 2, we looked for a CD4 cell count dose response between decreasing baseline CD4 cell count and risk of death or virologic failure by stratifying baseline CD4 cell count into finer categories (0–99, 100–199, 200–299, and ≥300 cells/μl). After adjustment, we found those with a CD4 cell count between 100 and 199 cells/μl and those with a CD4 cell count below 100 cells/μl had a roughly three-fold increased risk of death or virologic failure as those with at least 300 cells/μl (CD4 cell count <100 vs. >300 cells/μl; hazard ratio, 3.08; 95% CI, 0.92–10.4 and CD4 cell count 100–199 vs. >300 cells/μl, hazard ratio, 3.23; 95% CI, 0.99–10.6 cells/μl), whereas those with a CD4 cell count of 200–299 cells/μl had twice the risk (hazard ratio, 2.00; 95% CI, 1.19–3.37). Thus, higher baseline CD4 cell count does appear to be associated with lower risk of virologic failure and death.
We also looked for interactions between the baseline CD4 cell count group and other markers of immunosuppression. Model 3 shows the results of a regression model that includes the only significant interaction we identified, that between baseline CD4 cell count (≤200 vs. >200 cells/μl) and baseline WHO Stage IV. Compared with the reference group of those with a baseline CD4 cell count above 200 cells/μl and no WHO Stage IV condition, those with either a WHO Stage IV condition alone or a CD4 cell count of 200 cells/μl or less alone had a two-to-three-fold increased risk of death or virologic failure (hazard ratio, 2.87; 95% CI, 0.93–8.83 and hazard ratio, 2.14; 95% CI, 1.20–3.81, respectively). However, those with both a WHO Stage IV condition and a CD4 cell count of 200 cells/μl or less at baseline had a four-fold increased risk of death or virologic failure vs. those with neither condition (hazard ratio, 3.91; 95% CI, 1.88–8.14).
Overall about 6% of all patients in the study developed incident TB over the course of follow-up with substantially more of it occurring among those initiated on ART at CD4 cell counts of 200 cells/μl or less than among those initiated above 200 cells/μl (8.0 vs. 3.1%; RR, 2.6; 95% CI, 1.3–5.2) (Table 2). In a Kaplan–Meier analysis (Fig. 1c), we note that the majority of the difference between the two groups emerged within the first 24 months on treatment. In Table 4, we present two separate models of incident TB that are identical except that they use different categorizations of CD4 cell count (Models 1 uses ≤200 vs. >200 cells/μl, whereas Model 2 uses <50, 50–199 and ≥200 cells/μl). After adjusting for site, treatment group, age, sex, use of a protease inhibitor-based regimen, baseline viral load, WHO stage and BMI, using proportional hazards regression, we found that those initiated on ART at CD4 cell counts of 200 cells/μl were twice as likely to develop TB compared with those initiated above 200 cells/μl (hazard ratio, 1.9; 95% CI, 0.89–4.0) (Table 4, Model 1). When we further stratified the lowest CD4 cell counts group into those above and below 50 cells/μl (Model 2), we found that those with a CD4 cell count below 50 vs. above 200 cells/μl were at strongly increased risk of incident TB (hazard ratio, 3.4; 95% CI, 1.4–8.5), whereas those with 50–200 vs. above 200 cells/μl were at lower increased risk (hazard ratio, 1.60; 95% CI, 0.73–3.5) (Table 4).
Loss to follow-up
Nearly 12% of the cohort were LTFU and LTFU was more common among those with a baseline CD4 cell count above 200 than 200 cells/μl or less (14.3 vs. 10.2%)(Table 2). After adjusting for age, sex, baseline WHO stage, viral load, use of a protease inhibitor, treatment arm and site (data not shown), we found a small decreased risk of being LTFU among those initiated on ART with lower CD4 cell counts (≤200 cells/μl) vs. those initiated at higher CD4 cell counts (>200 cells/μl) (hazard ratio, 0.79; 95% CI, 0.50–1.25). Figure 1(b) shows that the difference between the groups emerges only after 24 months, the minimum potential follow-up time for the cohort. Those with a baseline WHO stage IV condition also had an increased risk of LTFU (hazard ratio, 1.61; 95% CI 0.93–2.79) (data not shown).
Toxicity endpoints were experienced by about 17% of the entire cohort (Table 2). We observed small differences in rates of toxicities between CD4 count groups slightly favoring those with baseline CD4 cell counts of 200 cells/μl or less vs. above 200 cells/μl (15.6 vs. 18.0%) (Fig. 1d). After adjusting for age, sex, baseline WHO stage, viral load, treatment regimen, treatment arm and site, women (hazard ratio, 1.95; 95% CI, 1.17–3.24), those who with a BMI above 30 vs. 18.5–30 kg/m2 (hazard ratio, 2.17; 95% CI, 1.41–3.34) or a baseline WHO stage IV condition (hazard ratio, 1.91; 95% CI, 1.15–3.18) were at increased risk of toxicity failure, but we found little difference between CD4 cell count groups (hazard ratio, 0.78; 95% CI, 0.53–1.16) (data not shown). Use of lopinavir–ritonavir vs. efavirenz-based regimens decreased the risk of toxicity (hazard ratio, 0.40; 95% CI, 0.16–1.02). Nevirapine use was associated with increased risk of toxicity vs. efavirenz-based regimens in unadjusted analyses (hazard ratio, 1.46; 95% CI, 0.99–2.16), but the association disappeared after adjustment (hazard ratio, 1.01; 95% CI, 0.63–1.61).
The results of analyses of the CIPRA-SA trial data show a clearly increased risk of death or virologic failure associated with initiating ART at lower CD4 cell counts. We found that those who started ART at CD4 cell counts of 200 cells/μl or less had roughly twice the risk of death or virologic failure as those initiated at CD4 cell counts above 200 cells/μl (hazard ratio, 1.94; 95% CI, 1.14–3.30) and twice the risk of developing incident TB (hazard ratio, 1.90; 95% CI, 0.89–4.04). These findings are in line with numerous observational studies [23–27] from resource-limited settings showing low baseline CD4 cell count is a major predictor of death and LTFU. Recently, an interim analysis of the CIPRA-HT001 trial in Haiti showed a nearly four-fold increased risk of death among those starting ART with a CD4 cell count of 200 vs. 200–350 cells/μl , very similar to our five-fold increased risk (RR, 5.4; 95% CI, 1.3–23.0) . Thus, a body of evidence is beginning to emerge, showing the benefits of earlier treatment initiation in resource-limited settings. This, along with a recent analysis by Lawn et al.  showing that the longer a patient maintains a CD4 cell count of below 100 cells/μl, the higher the risk of death suggests that starting patients at higher CD4 cell counts may allow them to maintain their CD4 cell counts above the point at which they are at increased risk of death.
Our findings are also consistent with data from resource-rich environments. Observational data have shown that higher CD4 cell counts are associated with lower risk of death [7,9]. More recently, Kitahata et al.  have shown that patients initiating ART at CD4 cell counts above 500 cells/μl had substantially reduced risk of mortality vs. those below 500 cells/μl. Although our data cannot be used to comment on CD4 cell counts above 350 cells/μl, our finding of decreased mortality and virologic failure risk associated with having a starting CD4 cell count above 300 cells/μl is suggestive of a dose response with increasing baseline CD4 cell count associated with better outcomes.
Although we found a substantial association between earlier ART initiation and better treatment outcomes we also found a slightly increased risk of being LTFU among those with higher baseline CD4 cell counts, which could potentially offset some of the benefits of initiating treatment earlier. However, we urge caution in interpreting these results. Under ideal conditions, assessing the effectiveness of initiating ART at higher CD4 cell counts would come from randomizing patients to either immediate initiation of ART when the CD4 cell count falls below 350 cells/μl or follow patients and delay ART until the CD4 cell count falls below 200 cells/μl [14,29]. In both arms, patients would be followed from the time of their first CD4 cell count below 350 cells/μl. In our study, patients were initiated onto ART at enrollment as long as their CD4 cell count was below 350 cells/μl, so we do not have any follow-up time to approximate what happens to patients in the time their CD4 cell count is between 200 and 350 cells/μl; however, we anticipate some deaths and LTFU occur in this time. Although methods exist to adjust for this lead-time bias , they require pre-ART data, which we did not have.
The current analysis has several strengths. The data were from a large prospective randomized trial with excellent follow-up data at standardized intervals, which allowed the assessment of the impact of starting treatment at higher CD4 cell counts. Although the data were from a randomized trial of another intervention, because the trial showed no differences between randomization groups (i.e. nurse vs. doctor-monitored care) and because adjustment for randomization group had no impact on our current results, there is little evidence that the primary intervention had any impact on our findings.
Still, the current analysis should be considered in light of several limitations. First, as noted above, we did not have the ideal comparison group to assess death and virologic failure (i.e. a group followed from a CD4 cell count of 350 cells/μl until 200 cells/μl and then initiated on ART). Thus, any deaths occurring between 350 and 200 cells/μl would not be included in our analysis. As we are missing deaths in the high CD4 cell count group, this analysis may underestimate the treatment benefits of starting at higher CD4 cell counts. Thus, our estimates cannot be considered the true causal effect of starting treatment at higher CD4 cell counts. Second, as the data came from a randomized trial with conservative definitions of toxicity, many patients who were treatment failures for toxicity might have otherwise continued on treatment under usual practice conditions. This could have biased our toxicity results toward the null and prevented us from observing a true difference between the groups if one existed. Third, in our analysis of LTFU, we were not able to determine the final outcomes of patients lost and, therefore, we cannot say whether patients left care because they were feeling well nor could we determine how many of them have since died. Finally, as the data were from a trial, the study population may have been healthier than the general clinic population.
We found that patients initiated on standard first-line South African ART regimens were at increased risk of death and virologic failure if initiated at CD4 cell counts below 200 cells/μl compared with those initiated above 200 cells/μl. This is consistent with findings from developed areas that have shown that the benefits of starting at earlier CD4 cell counts outweigh the risks of toxicity and long-term adherence. Although the cost implications are unknown, national and international guidelines on the topic of when to initiate ART should consider our findings when deciding on whether to increase initiating CD4 cell count thresholds. If thresholds are increased, then substantial efforts will need to be made to move patients into care earlier in their disease progression in order to obtain the maximum benefit from ART.
Support for this study was provided by the US National Institute of Allergy and Infectious Diseases (NIAID) through the CIPRA network, grant #U19 AI53217. The project described was also supported by K01AI083097 and P30-AI50410 from the NIAID and 5U2RTW007373-03 from the Fogarty International Center and was also provided by the United States Agency for International Development (USAID) under the terms of agreement 674-A-00-08-00007-00 with Right to Care (RTC). The content of this publication does not necessarily reflect the views or policies of NIAID, the Fogarty Center, USAID or RTC nor does mention of trade names, commercial projects or organizations imply endorsement by the US Government. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIAID, the Fogarty Center, the National Institutes of Health, USAID or other parties.
M.F. performed the primary statistical analyses and drafted the manuscript. I.S., F.C. J.Z., C.O. R.I. M.R. M.D. C.v.d.H. J.M. and R.W. contributed to the design of the study and data interpretation and revising the article. All authors approved the final manuscript.
1. Souteyrand Y, Akwara P, Warner Smith M, Beusenberg M, Jashi M, Hayashi C, et al
. Scaling up access to antiretroviral therapy (ART) in low- and middle-income countries: global and regional progress in 2008
. International AIDS Society Conference WELBD105
2. Hughes MD, Ribaudo HR. The search for data on when to start treatment for HIV infection. J Infect Dis 2008; 197:1084–1086.
3. Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents;
2008. [Accessed 12 January 2009].
4. Hammer SM, Eron JJ Jr, Reiss P, Schooley RT, Thompson MA, Walmsley S, et al
. Antiretroviral treatment of adult HIV infection: 2008 recommendations of the International AIDS Society-USA panel. JAMA 2008; 300:555–570.
5. National Department of Health, South Africa. National antiretroviral treatment guidelines,
first ed. Jacana; 2004.
6. World Health Organization. Antiretroviral therapy for HIV infection in adults and adolescents: recommendations for a public health approach (2006 revision).
World Health Organization; 2006.
7. Egger M, Hirschel B, Francioli P, Sudre P, Wirz M, Flepp M, et al
. Impact of new antiretroviral combination therapies in HIV infected patients in Switzerland: prospective multicentre study. Swiss HIV Cohort Study. BMJ 1997; 315:1194–1199.
8. Emery S, Neuhaus JA, Phillips AN, Babiker A, Cohen CJ, Gatell JM, et al
. Major clinical outcomes in antiretroviral therapy (ART)-naive participants and in those not receiving ART at baseline in the SMART study. J Infect Dis 2008; 197:1133–1144.
9. May M, Sterne JA, Sabin C, Costagliola D, Justice AC, Thiebaut R, et al
. Prognosis of HIV-1-infected patients up to 5 years after initiation of HAART: collaborative analysis of prospective studies. AIDS 2007; 21:1185–1197.
10. Sabin CA, Phillips AN. Should HIV therapy be started at a CD4 cell count above 350 cells/microl in asymptomatic HIV-1-infected patients? Curr Opin Infect Dis 2009; 22:191–197.
11. Royce RA, Sena A, Cates W Jr, Cohen MS. Sexual transmission of HIV. N Engl J Med 1997; 336:1072–1078.
12. Walensky RP, Wolf LL, Wood R, Fofana MO, Freedberg KA, Martinson NA, et al
. When to start antiretroviral therapy in resource-limited settings. Ann Intern Med 2009; 151:157–166.
13. Kitahata MM, Gange SJ, Abraham AG, Merriman B, Saag MS, Justice AC, et al
. Effect of early versus deferred antiretroviral therapy for HIV on survival. N Engl J Med 2009; 360:1815–1826.
14. Phillips AN, Gazzard BG, Clumeck N, Losso MH, Lundgren JD. When should antiretroviral therapy for HIV be started? BMJ 2007; 334:76–78.
15. Hernan MA, Cole SR, Philippakis A, Robins JM. Methods for estimating the optimal time of HAART initiation
[abstract no. TuPeC4844]. International Conference on AIDS
16. Hogg RS, Yip B, Chan KJ, Wood E, Craib KJ, O'Shaughnessy MV, et al
. Rates of disease progression by baseline CD4 cell count and viral load after initiating triple-drug therapy. JAMA 2001; 286:2568–2577.
17. Kaplan JE, Hanson DL, Cohn DL, Karon J, Buskin S, Thompson M, et al
. When to begin highly active antiretroviral therapy? Evidence supporting initiation of therapy at CD4+
lymphocyte counts <350 cells/microl. Clin Infect Dis 2003; 37:951–958.
18. Moh R, Danel C, Messou E, Ouassa T, Gabillard D, Anzian A, et al
. Incidence and determinants of mortality and morbidity following early antiretroviral therapy initiation in HIV-infected adults in West Africa. AIDS 2007; 21:2483–2491.
19. Severe P, Fitzgerald DW, and The Haiti CIPRA Team. A randomized clinical trial of early versus standard antiretroviral therapy for HIV-infected patients with a CD4 T Cell Count of 200–350 cells/ml (CIPRAHT001)
[abstract #H-1230c]. 49th Interscience Conference on Antimicrobial Agents and Chemotherapy
; 14 September 2009; San Francisco, California, USA; 2009.
20. Questions and answers: the CIPRA HT 001 Clinical Trial. National Institute of Allergy and Infectious Diseases, National Institutes of Health
; 6 August 2009.
21. World Health Organization. Rapid advice: antiretroviral therapy for HIV infection in adults and adolescents
. Switzerland: WHO; 2009.
22. Sanne I, Orrell C, Fox MP, Conradie F, Ive P, Zeinecker J, et al.
, for the CIPRA-SA Study Team. Nurse versus doctor management of HIV-infected patients receiving antiretroviral therapy (CIPRA-SA): a randomised non-inferiority trial
. Lancet published online June 16, 2010 DOI:10.1016/S0140-6736(10)60894-X
23. Toure S, Kouadio B, Seyler C, Traore M, Dakoury-Dogbo N, Duvignac J, et al
. Rapid scaling-up of antiretroviral therapy in 10000 adults in Cote d'Ivoire: 2-year outcomes and determinants. AIDS 2008; 22:873–882.
24. Brinkhof MW, Dabis F, Myer L, Bangsberg DR, Boulle A, Nash D, et al
. Early loss of HIV-infected patients on potent antiretroviral therapy programmes in lower-income countries. Bull World Health Organ 2008; 86:559–567.
25. Coetzee D, Hildebrand K, Boulle A, Maartens G, Louis F, Labatala V, et al
. Outcomes after two years of providing antiretroviral treatment in Khayelitsha, South Africa. AIDS 2004; 18:887–895.
26. Calmy A, Pinoges L, Szumilin E, Zachariah R, Ford N, Ferradini L. Generic fixed-dose combination antiretroviral treatment in resource-poor settings: multicentric observational cohort. AIDS 2006; 20:1163–1169.
27. Lawn SD, Harries AD, Anglaret X, Myer L, Wood R. Early mortality among adults accessing antiretroviral treatment programmes in sub-Saharan Africa. AIDS 2008; 22:1897–1908.
28. Lawn SD, Little F, Bekker LG, Kaplan R, Campbel E, Orrell C, et al
. Changing mortality risk associated with CD4 cell response to antiretroviral therapy in South Africa. AIDS 2009; 23:335–342.
29. Lane HC, Neaton JD. When to start therapy for HIV infection: a swinging pendulum in search of data. Ann Intern Med 2003; 138:680–681.
30. Cole SR, Li R, Anastos K, Detels R, Young M, Chmiel JS, et al
. Accounting for leadtime in cohort studies: evaluating when to initiate HIV therapies. Stat Med 2004; 23:3351–3363.
This article has been cited 3 time(s).
International Journal of EpidemiologyCohort Profile: The Themba Lethu Clinical Cohort, Johannesburg, South AfricaInternational Journal of Epidemiology
Plos OneA Novel Approach to Accounting for Loss to Follow-Up when Estimating the Relationship between CD4 Count at ART Initiation and MortalityPlos One
CD4 cell count; highly active antiretroviral therapy; HIV; mortality; Sub-Saharan Africa; tuberculosis; virologic failure
© 2010 Lippincott Williams & Wilkins, Inc.
Highlight selected keywords in the article text.