Does short-term virologic failure translate to clinical events in antiretroviral-naïve patients initiating antiretroviral therapy in clinical practice?
The Antiretroviral Therapy Cohort Collaboration (ART-CC)
* A complete listing of the ART-CC steering committee, coordinating team, and contributing cohorts is given in Acknowledgement section.
Received 19 March, 2008
Revised 8 September, 2008
Accepted 11 September, 2008
Correspondence to Michael J. Mugavero, MD, MHSc, CCB 178 1530, 3rd Avenue S., Birmingham, AL 35294-2050, USA. E-mail: email@example.com
Objective: To determine whether differences in short-term virologic failure among commonly used antiretroviral therapy (ART) regimens translate to differences in clinical events in antiretroviral-naïve patients initiating ART.
Design: Observational cohort study of patients initiating ART between January 2000 and December 2005.
Setting: The Antiretroviral Therapy Cohort Collaboration (ART-CC) is a collaboration of 15 HIV cohort studies from Canada, Europe, and the United States.
Study participants: A total of 13 546 antiretroviral-naïve HIV-positive patients initiating ART with efavirenz, nevirapine, lopinavir/ritonavir, nelfinavir, or abacavir as third drugs in combination with a zidovudine and lamivudine nucleoside reverse transcriptase inhibitor backbone.
Main outcome measures: Short-term (24-week) virologic failure (>500 copies/ml) and clinical events within 2 years of ART initiation (incident AIDS-defining event, death, and a composite measure of these two outcomes).
Results: Compared with efavirenz as initial third drug, short-term virologic failure was more common with all other third drugs evaluated; nevirapine (adjusted odds ratio = 1.87, 95% confidence interval (CI) = 1.58–2.22), lopinavir/ritonavir (1.32, 95% CI = 1.12–1.57), nelfinavir (3.20, 95% CI = 2.74–3.74), and abacavir (2.13, 95% CI = 1.82–2.50). However, the rate of clinical events within 2 years of ART initiation appeared higher only with nevirapine (adjusted hazard ratio for composite outcome measure 1.27, 95% CI = 1.04–1.56) and abacavir (1.22, 95% CI = 1.00–1.48).
Conclusion: Among antiretroviral-naïve patients initiating therapy, between-ART regimen, differences in short-term virologic failure do not necessarily translate to differences in clinical outcomes. Our results should be interpreted with caution because of the possibility of residual confounding by indication.
Combination antiretroviral therapy (ART) has resulted in dramatic reductions in HIV-associated morbidity and mortality for persons with access to treatment. Preferred initial ART regimens have changed over time largely on the basis of the evidence from randomized controlled clinical trials (RCTs). However, clinical trials are usually powered to detect between-regimen differences in short-term suppression of plasma HIV RNA. Due to the rarity, in recent years, of clinical events such as incident AIDS-defining events and death [1–3], clinical trials are typically underpowered to detect differences in these clinical outcome measures.
Collaborations of observational cohort studies, a complementary study design to RCTs, may have the statistical power to evaluate between-regimen differences in clinical outcomes. However, results from such studies are likely to be affected by confounding because of the nonrandomized selection of initial ART regimens in clinical practice , often referred to as ‘confounding by indication’ . Statistical methods can adjust for measured imbalances between treatment groups, but unmeasured confounding can never be fully excluded . Recognizing these limitations, observational HIV cohort studies can play an important role in providing evidence that is not available from RCTs [7,8].
Previous observational studies have evaluated between-regimen differences in short-term virologic failure in treatment-naïve patients initiating ART in clinical practice settings, often yielding findings consistent with RCT results [9–21]. However, these studies have largely been underpowered to evaluate between-regimen differences in clinical outcomes. Previously, the ART Cohort Collaboration (ART-CC) evaluated between-regimen differences in virologic and clinical outcomes in patients initiating ART between 1996 and 2002 . However, several regimens evaluated in that study are no longer widely used in clinical practice. Furthermore, ritonavir-boosted (RTV) protease inhibitors (amprenavir, lopinavir, saquinavir, and indinavir) were evaluated together due to the low number of such regimens in the database at the time of the study. Heterogeneity of outcomes between boosted protease inhibitor regimens may have affected the overall findings for these regimens, which were found to be inferior for both virologic and clinical outcomes, relative to efavirenz (EFV). Here, we analyse the data from an updated ART-CC database to evaluate between-regimen differences in short-term virologic failure and rates of clinical events among treatment-naïve patients initiating ART between 2000 and 2005; all analyses were conducted at the level of the individual regimen. We hypothesized that between-ART regimen differences in short-term virologic failure would not fully predict the effects on clinical endpoints.
The Antiretroviral Therapy Cohort Collaboration (ART-CC) is a collaboration of 15 HIV cohort studies from Canada, Europe, and the United States that was established in 2001. The collaboration has been described in detail elsewhere [23–26]. Briefly, prospective cohort studies were eligible for participation if they had enrolled at least 100 HIV-1–infected patients aged 16 years or more who had not previously received antiretroviral treatment, started ART with a combination of at least three antiretroviral drugs after 1996, and been followed for a median duration of at least 1 year after ART initiation. The database was updated in 2007 to additionally include patients who had started ART up until 31 December 2005 with follow-up until 1 July 2006. All cohorts have been approved by their local ethics committees or institutional review boards, use standardized methods of data collection, and schedule follow-up visits at least once every 6 months.
The cohorts in the dataset for this analysis are French Hospital Database on HIV (FHDH) ANRS CO4  and the Aquitaine Cohort ANRS CO3 (France) , the AIDS Therapy Evaluation project Netherlands (ATHENA) , Italian Cohort of Antiretroviral-Naive Patients (ICONA) , Swiss HIV Cohort Study (SHCS) , Frankfurt HIV Cohort  and Köln/Bonn Cohort (Germany) , the EuroSIDA study (20 countries in Europe and Argentina) , the Collaborations in HIV Outcomes Research US (CHORUS) , the University of Alabama at Birmingham 1917 Clinic Cohort  and the Veterans Aging Cohort Study (VACS) (USA) , the Royal Free Hospital Cohort (United Kingdom) , the British Columbia Centre for Excellence in HIV/AIDS  and the South Alberta Clinic (Canada) , and PISCIS, Catalonia and Balearic Islands (Spain) .
Patient selection and data extraction were performed at the data centres of the participating cohorts. Anonymized data on a predefined set of demographic, laboratory, and clinical variables were pooled and analysed centrally. Cohort data managers from EuroSIDA were asked to provide a unique study identification for each record as EuroSIDA patients may also be members of other cohort studies.
Analyses were restricted to HIV-1-positive patients aged 16 years or older, who first started antiretroviral therapy in the period 1 January 2000 to 31 December 2005 and had at least 6 months of potential follow-up before the cohort-specific database close date. Because of the focus on more recent ART regimens, study inclusion criteria required initiation of efavirenz (EFV), nevirapine (NVP), lopinavir/ritonavir (LPV/r), nelfinavir (NFV), or abacavir (ABC) as ‘third drugs’. We evaluated short-term (24-week) virologic failure (HIV RNA >500 copies/ml) and longer-term clinical outcomes (incident AIDS-defining event, death from any cause, and a composite measure of these two outcomes) by third drug, in patients who were taking zidovudine and lamivudine (ZDV and 3TC) as the nucleoside reverse transcriptase inhibitor (NRTI) backbone. This approach was taken to focus on differences in virologic failure and clinical outcomes between third drugs given in combination with the same NRTI pair, such that potential differences in prescribing patterns for NRTI backbones across third drugs was not a factor. ZDV and 3TC were chosen as the NRTI backbone as this combination represented the most commonly prescribed NRTI pair (68% of regimens). All centres used the 1993 US Centers for Disease Control and Prevention criteria and guidelines for the definitive or presumptive diagnosis of AIDS-defining events . Only new AIDS diagnosis, defined as the first occurrence of each AIDS-defining condition was considered to be an incident event; recurrences of conditions were not considered. Change in regimen at 6 months after initiating ART was a secondary outcome.
To evaluate short-term virologic failure, logistic regression models were used to estimate crude and adjusted odds ratios (ORs) of detectable 24-week plasma HIV-1 RNA, that is more than 500 copies/ml, among patients with an available measurement at that time (±3-month window). For this analysis, patients who died prior to 24 weeks and those with missing 24-week plasma HIV-1 RNA values were excluded. Logistic regression models were also used to estimate the crude and adjusted OR of not being on the initial regimen at 24 weeks; 24-week regimen change was evaluated as a secondary outcome measure. Sensitivity analyses were conducted evaluating 24-week virologic failure and initial ART regimen change for all patients, including those with missing 24-week measurements. For these analyses, patients with missing 24-week plasma HIV RNA measures (±3 months), including those who died, were considered treatment failures (‘missing equals failure’).
To evaluate clinical outcomes, we measured time from the date of initiating ART to earlier of the date that clinical endpoints occurred and the date of censoring (end of follow-up). In patients free of events, follow-up was censored on the date of the most recent visit plus half the usual visit interval (usually 3 months) for AIDS and the combined endpoint (incident AIDS event or death from any cause). For mortality, the censoring date was extended to the date the patient was last known to be alive in cohorts that could assert complete vital registration; otherwise, as above. Because the proportion of patients remaining on their initial regimen decreases over time, effects of initial regimen become increasingly diluted by regimen changes with increasing time since initiation of ART. Follow-up was therefore censored at 2 years after starting ART or at the cohort-specific close of database date, if either of these occurred sooner. Additional analyses, removing the 2-year censoring, were conducted to evaluate longer-term differences in clinical events according to initial ART regimen.
Weibull proportional hazards regression models were used to model the association of initial treatment regimen and other prognostic factors with disease progression as measured by clinical outcome measures. We estimated crude and adjusted hazard ratios comparing other third drugs with EFV when taken in combination with ZDV and 3TC. Analyses followed an ‘intent to continue initial therapy’ principle, in that eligible participants were analysed according to initial regimen, regardless of whether they later discontinued or modified their therapeutic regimen.
All multivariable models were adjusted for age at initiation of therapy (16–29, 30–39, 40–49, and >50 years), sex, transmission risk group [injection drug user (IDU), non-IDU], clinical stage (A/B, C), baseline CD4 cell count (<25, 25–49, 50–99, 100–199, 200–349, and ≥350 cells/μl), baseline plasma HIV-1 RNA (<1000, 1000–9999 10 000–99 999, and ≥100 000 copies/ml), year of starting ART and cohort. Sensitivity analyses were restricted to patients who started ART with a CD4 cell count 200 cells/μl or less and to those whose reported transmission risk group was non-IDU.
AIDS-free survival up to 2 years after initiation of therapy by third drug was plotted using the estimated probability of a survival free of an incident AIDS-defining event or death from the adjusted Weibull model with covariates set at their average value across the population of patients and for the cohort with median survival.
Overall, 13 546 patients in the ART-CC initiated ART with the third drugs of interest (EFV, NVP, LPV/r, NFV, ABC) paired with ZDV and 3TC during the study period. Among study participants, 69% were men, 13% reported a history of IDU, and 20% had CDC clinical stage C disease (Table 1). Overall, the median age (interquartile range) was 38 years (31–45) and the median CD4 cell count and plasma log10 HIV RNA levels were 218 cells/μl (104–329) and 4.9 (4.4–5.3), respectively, at the time of ART initiation. During the study period, EFV was the most commonly prescribed third drug (28%), followed by LPV/r (21%), ABC (19%), NFV (16%), and NVP (16%). Temporal trends in prescribing patterns measured as the proportion of overall ART prescriptions in a given year represented by each antiretroviral drug indicated increased use of LPV/r and decreased use of all other third drugs over the course of the observation period (Fig. 1). Compared with other third drugs, LPV/r was more commonly prescribed to patients with lower CD4 cell counts (median 150 cells/μl) and higher plasma HIV RNA levels (5.1 log10 copies/ml), whereas the opposite was observed for ABC (median 251 cells/μl and 4.7 log10 copies/ml) and NVP (median 260 cells/μl and 4.7 log10 copies/ml) (Table 1).
In multivariable logistic regression analyses among patients who had 24-week plasma HIV RNA measures (n = 11 194, 83%), detectable 24-week plasma HIV RNA (>500 copies/ml) was more common with all other third drugs than with EFV (Table 2). Findings were most pronounced for NFV (adjusted OR = 3.20, 95% CI = 2.74–3.74), whereas patients treated with NVP (1.87, 95% CI = 1.58–2.22) and ABC (2.13, 95% CI = 1.82–2.50) had roughly twice the odds of short-term virologic failure. There was a modest increase in the odds of 24-week virologic failure for LPV/r (adjusted OR = 1.32, 95% CI = 1.12–1.57). Among those with available 24-week data (n = 11 338, 84% of cohort), patients receiving NVP (adjusted OR = 1.30, 95% CI = 1.13–1.51) and NFV (1.39, 95% CI = 1.20–1.60) were less likely to be treated with their initial regimen at 24 weeks than those receiving EFV (Table 2).
In general, sensitivity analyses including all patients (n = 13 546) and utilizing a ‘missing equals failure’ approach gave similar results to those observed in primary analyses, but with ORs that were attenuated towards one (Table 3). In these analyses, the odds of virologic failure were similar for LPV/r relative to EFV (adjusted OR = 1.03, 95% CI = 0.91–1.16). This is in contrast to the primary analyses in which the odds of 24-week virologic failure were higher with LPV/r compared with that in EFV. Sensitivity analyses of 24-week change of initial ART regimen yielded similar results to primary analyses, and parameter estimates were of comparable magnitude (Table 3).
In Weibull proportional hazards analysis of clinical outcomes, rates of incident AIDS events (adjusted hazard ratio = 1.28, 95% CI = 1.02–1.60), death (1.54, 95% CI = 1.09–2.19), and combined clinical outcome (1.27, 95% CI = 1.04–1.56) appeared higher for NVP than for EFV (Table 4). Because baseline CD4 cell counts tended to be higher for patients initiating NVP (median baseline CD4 cell count 260 cells/μl) than those starting EFV (median 207 cells/μl), adjusted hazard ratios for this comparison were markedly greater than crude hazard ratios. In contrast, for the comparison of LPV/r (median baseline CD4 cell count 150 cells/μl) with EFV adjusted hazards were attenuated towards one after controlling for patient characteristics at baseline. In adjusted analyses, there was little evidence that rates of clinical events in patients on LPV/r differed from those in patients receiving EFV (AIDS-event adjusted hazard ratio = 1.14, 95% CI = 0.93–1.39, death 1.12, 95% CI = 0.80–1.57, combined outcome measure 1.13, 95% CI = 0.94–1.36) (Table 4). Figure 2 shows that by 2 years after starting ART, there was an estimated difference of about 2% in the cumulative probability of AIDS-free survival, between patients initiating ART on NFV and those initiating NVP.
Relative to EFV, hazards of AIDS events (adjusted hazard ratio = 0.98, 95% CI = 0.79–1.21), death (0.89, 95% CI = 0.63–1.28), and the combined clinical endpoint (0.92, 95% CI = 0.76–1.11) were slightly lower for NFV (Table 4). In adjusted analyses, hazards of death (adjusted hazard ratio = 1.41, 95% CI = 1.01–1.99) and the combined clinical endpoint (1.22, 95% CI = 1.00–1.48) appeared higher for ABC than for EFV. Such differences were not apparent in unadjusted analyses, in part because the median baseline CD4 cell count was higher for patients on ABC (median 251 cells/μl) than for those on EFV (median 207 cells/μl).
In general, sensitivity analyses of the combined clinical outcome measure (incident AIDS event or death) restricted to patients with baseline CD4 cell counts 200 cells/μl or less when initiating ART yielded parameter estimates of similar magnitude for each third drug relative to the primary analyses, although CIs were wider (Table 5). However, larger shifts in hazards ratios relative to primary analyses were observed when AIDS events and death were modelled separately, relative to models of the composite clinical outcome measure. On the whole, sensitivity analyses of clinical outcomes restricted to non-IDU patients yielded similar findings to primary analyses (Table 6). Evaluation of longer-term clinical events by initial ART regimen removing 2-year censoring yielded similar results to primary analyses, although, as expected, hazard ratios were attenuated towards one (Table 7).
Among antiretroviral-naïve patients initiating ART in clinical practice settings, short-term (24-week) virologic failure was more common for all third drugs evaluated (NVP, LPV/r, NFV, and ABC) relative to EFV when given in combination with ZDV and 3TC. However, compared with EFV, estimated rates of AIDS and death appeared higher only with NVP and ABC. For LPV/r and NFV, we found little evidence that rates of AIDS and death differed from those on EFV. Taken together, these findings suggest that, between ART regimen, differences in short-term virologic failure do not necessarily translate to differences in clinical outcomes.
Although suppression of plasma HIV RNA is an important goal of treatment to avoid the emergence of viral resistance among other reasons, the ultimate aim of antiretroviral therapy is to prevent clinical progression and death. Preferred initial ART regimens change frequently, based on differential rates of virologic suppression observed in clinical trials. Our study suggests that such differences in virologic suppression between ART regimens may not translate to differences in clinical events among patients receiving treatment in a clinical practice setting. This observation may relate, in part, to the many available antiretroviral treatment options: patients failing treatment at 24-weeks may subsequently switch to other effective ART regimens. A recent study recognized the association of longitudinal CD4 cell count and plasma HIV RNA responses in contributing to long-term clinical outcomes in patients initiating modern ART, regardless of specific initial regimen .
Most previous observational studies (like RCTs) have lacked statistical power to analyse between-regimen differences in clinical events among patients initiating ART [9–20]. The ART-CC makes such comparisons possible through the collaborative efforts of multiple observational HIV cohort studies. The current study advances the findings of an earlier report from the ART-CC , by focusing on more recent ART regimens at the level of the third drug among patients receiving the same NRTI backbone (ZDV and 3TC). Importantly, the current study allowed for the evaluation of LPV/r individually, and not grouped with other RTV-boosted protease inhibitors (amprenavir, saquinavir, and indinavir) as done in the earlier analysis due to the relatively small frequency of LPV/r use during the earlier evaluation period (1996–2002).
In contrast with our earlier study, in which RTV-boosted protease inhibitors were associated with increased rates of both short-term virologic failure and clinical outcomes compared with EFV , LPV/r was associated only with 24-week virologic failure in the current study. The AIDS Clinical Trial Group (ACTG) 5142 study found a higher frequency of virologic failure among ARV-naïve patients treated with two NRTIs and LPV/r compared with those treated with two NRTIs and EFV . Although EFV outperformed LPV/r in achieving plasma HIV RNA levels of less than 50 copies/ml and showed a trend for superiority at less than 200 copies/ml, increases in CD4 cell counts were greater for patients receiving LPV/r than for those receiving EFV in that randomized clinical trial. In the current study, similar 24-week CD4 responses were observed for patients treated with LPV/r and EFV (median CD4 cell count increase 110 vs. 100 cells/μl, respectively). These similar CD4 responses among ART-CC patients treated with LPV/r and EFV may have contributed to comparable hazards of clinical outcomes, despite a higher frequency of 24-week virologic failure in patients treated with LPV/r.
Another possible explanation for the apparent lack of difference in clinical endpoints between EFV and LPV/r may relate to varying resistance patterns emerging upon treatment failure between different initial ART regimens. Recently, it was shown that patients failing a first-line nonnucleoside reverse transcriptase inhibitor (NNRTI) containing regimen harboured viruses with higher numbers of IAS-USA drug resistance mutations and resistance to more antiretroviral drug classes when compared with patients initiating therapy with ritonavir-boosted protease inhibitor containing regimens . Thus, EFV-based regimens, although more virologically effective as shown in this study, may result in more HIV resistance upon failure making it more difficult to generate potent successive ART regimens. In contrast, it might be easier to find effective salvage regimens for patients failing an initial boosted protease inhibitor regimen due to the lower number of drug resistance mutations observed. Furthermore, another study found the emergence of resistance to NNRTIs was associated with a greater risk of subsequent death than was the emergence of protease inhibitor resistance .
This updated analysis of the ART-CC found higher odds of 24-week virologic failure and hazards of clinical endpoints with NVP compared with EFV in analyses adjusted for covariates (Table 4). The findings regarding virologic failure are in contrast to the 2NN clinical trial , but consistent with other observational studies comparing these NNRTIs [18–20]. Although we are not able to determine the reasons for the observed inferior virologic and clinical outcomes associated with NVP use in the current study, it is possible that EFV outperformed NVP in a clinical practice setting. It is also possible that unmeasured confounders associated with NVP selection in clinical practice, confounding by indication, contributed to the inferior outcomes for NVP in the current study. Notably, shifts in parameter estimates for both NVP (increased) and LPV/r (decreased) for clinical outcome measures were observed between unadjusted and adjusted analyses attributable to differential patient profiles (e.g., baseline CD4 cell count and plasma HIV viral load) among patients stratified by third drug receipt (Table 1).
The impact of confounding by indication in the selection of third drugs was more apparent in the evaluation of clinical outcomes than observed in analyses of short-term virologic failure; more marked shifts in parameter estimates between crude and adjusted analyses were observed for the clinical outcomes models (Tables 2 and 4). Prior studies have shown the importance of baseline CD4 cell counts at the time of ART initiation on subsequent clinical events [24,48]. Taking into account the drastically different median CD4 cell counts among patients initiating ART observed in this study (e.g., LPV/r 150 cells/μl, NVP 260 cells/μl, and ABC 251 cells/μl), it would be expected that multivariable models controlling for these differences would lead to shifts in estimates observed for crude analyses, as was seen. Although the impact of confounding by indication is observed across analyses in this study, it is notable that sensitivity analyses of adjusted models largely yielded consistent findings to those observed in primary analyses.
The findings of our study must be interpreted with regard to the study limitations. The potential for confounding is inherent to all observational studies. The impact of confounding by indication is demonstrated and discussed in this study, but it is possible that other unmeasured confounders not included in adjusted statistical models may have contributed to observed study findings. As with prior studies of the ART-CC, we have adjusted for factors associated with clinical events (e.g., baseline CD4 cell count), but cannot rule out the possibility of unmeasured confounding. For example, it is possible that a provider's selection of initial ART regimen was influenced by their expectations of a patient's adherence to their antiretroviral medications. Such prescribing bias may represent unmeasured confounding that contributed to the between-regimen differences in outcomes observed in this study. Furthermore, between-provider differences (e.g., experience) may also have contributed to differential outcomes. Finally, although the ART-CC has broad geographic representation from Europe and North America, findings of this study may not apply to other geographic settings.
In summary, among patients initiating ART from 2000 to 2005 in clinical practice settings with a ZDV and 3TC backbone, those receiving third drugs other than EFV (NVP, LPV/r, NFV, and ABC) were more likely to experience short-term (24-week) virologic failure. However, such differences were not as prominent in the evaluation of clinical events, which were more common (relative to EFV) in patients receiving NVP and ABC as the third drug of their initial ART regimen, but with little evidence of such differences for those receiving NFV and LPV/r. This study clearly demonstrates the impact of confounding by indication: such confounding, as well as the potential for unmeasured confounding should be taken into account when conducting, evaluating, and reviewing studies utilizing this methodology [6,49]. Because of the limited available evidence from randomized trials on the impact of initial ART regimens on rates of clinical events, findings from well designed observational cohort studies may serve a complementary role to findings from clinical trials in informing clinical practice.
We are grateful to all patients, doctors, nurses, and other persons who were involved with the participating cohort studies. We would like to thank participating cohort members who provided thoughtful review and feedback on the content of this manuscript, particularly Colette Smith, Bruno Ledergerber, Peter Reiss, and Caroline Sabin.
The ART Cohort Collaboration is supported by the UK Medical Research Council grant RD1564. Sources of funding of individual cohorts include the Agence Nationale de Recherche contre le SIDA (ANRS), the Institut National de la Santé et de la Recherche Médicale (INSERM), the French, Italian, Spanish and Swiss Ministries of Health, The Swiss HIV Cohort Study, supported by the Swiss National Science Foundation (grant no. 33CSC0-108787), the Stichting HIV Monitoring, the European Commission, the British Columbia and Alberta Governments, the Michael Smith Foundation for Health Research, the Canadian Institutes of Health Research, the VHA Office of Research and Development and unrestricted grants from GlaxoSmithKline, Roche and Boehringer-Ingelheim. Supported in part by the Spanish Network for AIDS Research (RIS; ISCIII-RETIC RD06/006).
Author contributions: Study conception and design: Robert Hogg, Michael J. Mugavero, Margaret May, Michael S. Saag, Matthias Egger, Jonathan A.C. Sterne.
Data analysis: Margaret May, Ross Harris.
Acquisition of data and/or interpretation of data: Dominique Costagliola, Frank de Wolf, Amy Justice, Matthias Egger, Huldrych F. Günthard, Antonella D'Arminio Monforte, Jose M. Miró, Schlomo Staszewski, Andrew Phillips, Robert Hogg, Francois Dabis, Fiona Lampe, Gerd Fatkenheuer, M. John Gill, Michael J. Mugavero, Michael S. Saag, Margaret May, Ross Harris, Jonathan A.C. Sterne.
Drafting the manuscript: Michael J. Mugavero, Margaret May, Michael S. Saag, Jonathan A. C. Sterne.
Critical revision of the manuscript for important intellectual content: Ross Harris, Dominique Costagliola, Matthias Egger, Andrew Phillips, Huldrych F. Günthard, Francois Dabis, Robert Hogg, Frank de Wolf, Gerd Fatkenheuer, M. John Gill, Amy Justice, Antonella D'Arminio Monforte, Fiona Lampe, Jose M. Miró, Schlomo Staszewski.
Final manuscript approval: Michael J. Mugavero, Margaret May, Ross Harris, Michael S. Saag, Dominique Costagliola, Matthias Egger, Andrew Phillips, Huldrych F. Günthard, Francois Dabis, Robert Hogg, Frank de Wolf, Gerd Fatkenheuer, M. John Gill, Amy Justice, Antonella D'Arminio Monforte, Fiona Lampe, Jose M. Miró, Schlomo Staszewski, Jonathan A.C. Sterne.
The antiretroviral therapy cohort collaboration (ART-CC) study group.
Steering committee: Jordi Casabona (PISCIS), Geneviève Chêne (Aquitaine), Dominique Costagliola (FHDH), François Dabis (Aquitaine), Antonella D'Arminio Monforte (ICONA), Julia del Amo (CoRIS-MD), Frank de Wolf (ATHENA), Matthias Egger (SHCS), Gerd Fätkenheuer (Koln/Bonn), John Gill (South Alberta Clinic), Jodie Guest (HAVACS), Robert Hogg (BCCfE-HIV), Amy Justice (VACS), Mari Kitahata (Washington), Fiona Lampe (Royal Free), Bruno Ledergerber (SHCS), Amanda Mocroft (EuroSIDA), Peter Reiss (ATHENA), Michael Saag (Alabama), Schlomo Staszewski (Frankfurt).
Coordinating team: Matthias Egger, Margaret May, Ross Harris, Jonathan Sterne (Principal Investigator).
Writing committee: Michael J. Mugavero, Division of Infectious Disease, Department of Medicine, University of Alabama at Birmingham, Birmingham, USA; Margaret May, Department of Social Medicine, University of Bristol, Bristol, UK; Ross Harris, Department of Social Medicine, University of Bristol, Bristol, UK; Michael S. Saag, Division of Infectious Disease, Department of Medicine, University of Alabama at Birmingham, Birmingham, USA; Dominique Costagliola, INSERM U720, UPMC Paris 06, Paris, France; Matthias Egger, Department of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Andrew Phillips, Department of Primary Care and Population Sciences Royal Free and University College Medical School, London, UK; Huldrych F. Günthard, Divison of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland; Francois Dabis, INSERM U593, Université Victor Segalen Bordeaux, France; Robert Hogg, Division of Epidemiology and Population Health, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Frank de Wolf, Academisch Medisch Centrum bij de Universiteit van Amsterdam, Amsterdam. The Netherlands; Gerd Fatkenheuer, Department of Internal Medicine, University of Cologne, Germany; M. John Gill, Division of Infectious Diseases, University of Calgary, Calgary, Canada; Amy Justice, Yale University School of Medicine, New Haven, CT, USA and VA Connecticut Healthcare System, West Haven, CT, USA; Antonella D'Arminio Monforte, Clinic of Infectious Diseases & Tropical Medicine, ‘San Paolo’ Hospital, University of Milan, Italy; Fiona Lampe, Department of Primary Care and Population Sciences Royal Free and University College Medical School, London, UK; Jose M. Miró, Hospital Clinic – IDIBAPS. University of Barcelona, Barcelona, Spain; Schlomo Staszewski, Zentrum der Inneren Medizin, J.W. Goethe Universität, Frankfurt, Germany; Jonathan A.C. Sterne, Department of Social Medicine, University of Bristol, Bristol, UK.
Presented in part at the 14th Conference on Retroviruses and Opportunistic Infections, Los Angeles, CA; February 2007, abstract 527.
1. Palella FJ Jr, Baker RK, Moorman AC, Chmiel JS, Wood KC, Brooks JT, Holmberg SD. Mortality in the highly active antiretroviral therapy era: changing causes of death and disease in the HIV outpatient study. J Acquir Immune Defic Syndr 2006; 43:27–34.
2. Sabin CA, Smith CJ, Youle M, Lampe FC, Bell DR, Puradiredja D, et al
. Deaths in the era of HAART: contribution of late presentation, treatment exposure, resistance and abnormal laboratory markers. AIDS 2006; 20:67–71.
3. van Sighem AI, van de Wiel MA, Ghani AC, Jambroes M, Reiss P, Gyssens IC, et al
. Mortality and progression to AIDS after starting highly active antiretroviral therapy. AIDS 2003; 17:2227–2236.
4. Hughes MD. Initial treatment of HIV infection: randomized trials with clinical end points are still needed. J Infect Dis 2006; 194:542–544.
5. Walker AM. Confounding by indication. Epidemiology 1996; 7:335–336.
6. D'Agostino RB Jr, D'Agostino RB Sr. Estimating treatment effects using observational data. JAMA 2007; 297:314–316.
7. Hughes MD, Williams PL. Challenges in using observational studies to evaluate adverse effects of treatment. N Engl J Med 2007; 356:1705–1707.
8. Smeeth L, Douglas I, Hubbard R. Commentary: we still need observational studies of drugs – they just need to be better. Int J Epidemiol 2006; 35:1310–1311.
9. De Luca A, Cozzi-Lepri A, Antinori A, Zaccarelli M, Bongiovanni M, Di Giambenedetto S, et al
. Lopinavir/ritonavir or efavirenz plus two nucleoside analogues as first-line antiretroviral therapy: a nonrandomized comparison. Antivir Ther 2006; 11:609–618.
10. Easterbrook PJ, Newson R, Ives N, Pereira S, Moyle G, Gazzard BG. Comparison of virologic, immunologic, and clinical response to five different initial protease inhibitor-containing and nevirapine-containing regimens. J Acquir Immune Defic Syndr 2001; 27:350–364.
11. Friedl AC, Ledergerber B, Flepp M, Hirschel B, Telenti A, Furrer H, et al
. Response to first protease inhibitor- and efavirenz-containing antiretroviral combination therapy. The Swiss HIV Cohort Study. AIDS 2001; 15:1793–1800.
12. Lucas GM, Chaisson RE, Moore RD. Comparison of initial combination antiretroviral therapy with a single protease inhibitor, ritonavir and saquinavir, or efavirenz. AIDS 2001; 15:1679–1686.
13. Phillips AN, Grabar S, Tassie JM, Costagliola D, Lundgren JD, Egger M. Use of observational databases to evaluate the effectiveness of antiretroviral therapy for HIV infection: comparison of cohort studies with randomized trials. EuroSIDA, the French Hospital Database on HIV and the Swiss HIV Cohort Study Groups. AIDS 1999; 13:2075–2082.
14. Potard V, Rey D, Mokhtari S, Frixon-Marin V, Pradier C, Rozenbaum W, et al
. First-line highly active antiretroviral regimens in 2001–2002 in the French Hospital Database on HIV: combination prescribed and biological outcomes. Antivir Ther 2007; 12:317–324.
15. Pulido F, Arribas JR, Miro JM, Costa MA, Gonzalez J, Rubio R, et al
. Clinical, virologic, and immunologic response to efavirenz-or protease inhibitor-based highly active antiretroviral therapy in a cohort of antiretroviral-naive patients with advanced HIV infection (EfaVIP 2 study). J Acquir Immune Defic Syndr 2004; 35:343–350.
16. Weiser SD, Guzman D, Riley ED, Clark R, Bangsberg DR. Higher rates of viral suppression with nonnucleoside reverse transcriptase inhibitors compared to single protease inhibitors are not explained by better adherence. HIV Clin Trials 2004; 5:278–287.
17. Wood E, Hogg RS, Heath KV, de la Rosa R, Lee N, Yip B, et al
. Provider bias in the selection of nonnucleoside reverse transcriptase inhibitor and protease inhibitor-based highly active antiretroviral therapy and HIV treatment outcomes in observational studies. AIDS 2003; 17:2629–2634.
18. Braithwaite RS, Kozal MJ, Chang CC, Roberts MS, Fultz SL, Goetz MB, et al
. Adherence, virological and immunological outcomes for HIV-infected veterans starting combination antiretroviral therapies. AIDS 2007; 21:1579–1589.
19. Matthews GV, Sabin CA, Mandalia S, Lampe F, Phillips AN, Nelson MR, et al
. Virological suppression at 6 months is related to choice of initial regimen in antiretroviral-naive patients: a cohort study. AIDS 2002; 16:53–61.
20. Phillips AN, Pradier C, Lazzarin A, Clotet B, Goebel FD, Hermans P, et al
. Viral load outcome of nonnucleoside reverse transcriptase inhibitor regimens for 2203 mainly antiretroviral-experienced patients. AIDS 2001; 15:2385–2395.
21. Chou R, Fu R, Huffman LH, Korthuis PT. Initial highly-active antiretroviral therapy with a protease inhibitor versus a nonnucleoside reverse transcriptase inhibitor: discrepancies between direct and indirect meta-analyses. Lancet 2006; 368:1503–1515.
22. Rates of disease progression according to initial highly active antiretroviral therapy regimen: a collaborative analysis of 12 prospective cohort studies. J Infect Dis
23. Chene G, Sterne JA, May M, Costagliola D, Ledergerber B, Phillips AN, et al
. Prognostic importance of initial response in HIV-1 infected patients starting potent antiretroviral therapy: analysis of prospective studies. Lancet 2003; 362:679–686.
24. Egger M, May M, Chene G, Phillips AN, Ledergerber B, Dabis F, et al
. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet 2002; 360:119–129.
25. May M, Porter K, Sterne JA, Royston P, Egger M. Prognostic model for HIV-1 disease progression in patients starting antiretroviral therapy was validated using independent data. J Clin Epidemiol 2005; 58:1033–1041.
26. May M, Royston P, Egger M, Justice AC, Sterne JA. Development and validation of a prognostic model for survival time data: application to prognosis of HIV positive patients treated with antiretroviral therapy. Stat Med 2004; 23:2375–2398.
27. Grabar S, Le Moing V, Goujard C, Leport C, Kazatchkine MD, Costagliola D, Weiss L. Clinical outcome of patients with HIV-1 infection according to immunologic and virologic response after 6 months of highly active antiretroviral therapy. Ann Intern Med 2000; 133:401–410.
28. Binquet C, Chene G, Jacqmin-Gadda H, Journot V, Saves M, Lacoste D, Dabis F. Modeling changes in CD4-positive T-lymphocyte counts after the start of highly active antiretroviral therapy and the relation with risk of opportunistic infections: the Aquitaine Cohort, 1996–1997. Am J Epidemiol 2001; 153:386–393.
29. Wit FW, van Leeuwen R, Weverling GJ, Jurriaans S, Nauta K, Steingrover R, et al
. Outcome and predictors of failure of highly active antiretroviral therapy: one-year follow-up of a cohort of human immunodeficiency virus type 1-infected persons. J Infect Dis 1999; 179:790–798.
30. d'Arminio Monforte A, Lepri AC, Rezza G, Pezzotti P, Antinori A, Phillips AN, et al
. Insights into the reasons for discontinuation of the first highly active antiretroviral therapy (HAART) regimen in a cohort of antiretroviral naive patients. I. CO. N. A. Study Group. Italian Cohort of Antiretroviral-Naive Patients. AIDS 2000; 14:499–507.
31. 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.
32. Brodt HR, Kamps BS, Gute P, Knupp B, Staszewski S, Helm EB. Changing incidence of AIDS-defining illnesses in the era of antiretroviral combination therapy. AIDS 1997; 11:1731–1738.
33. Fatkenheuer G, Theisen A, Rockstroh J, Grabow T, Wicke C, Becker K, et al
. Virological treatment failure of protease inhibitor therapy in an unselected cohort of HIV-infected patients. AIDS 1997; 11:F113–F116.
34. Lundgren JD, Phillips AN, Vella S, Katlama C, Ledergerber B, Johnson AM, et al
. Regional differences in use of antiretroviral agents and primary prophylaxis in 3122 European HIV-infected patients. EuroSIDA Study Group. J Acquir Immune Defic Syndr Hum Retrovirol 1997; 16:153–160.
35. Becker SL, Raffanti SR, Hansen NI, Fusco JS, Fusco GP, Slatko GH, et al
. Zidovudine and stavudine sequencing in HIV treatment planning: findings from the CHORUS HIV cohort. J Acquir Immune Defic Syndr 2001; 26:72–81.
36. Chen RY, Accortt NA, Westfall AO, Mugavero MJ, Raper JL, Cloud GA, et al
. Distribution of healthcare expenditures for HIV-infected patients. Clin Infect Dis 2006; 42:1003–1010.
37. Justice AC, Dombrowski E, Conigliaro J, Fultz SL, Gibson D, Madenwald T, et al
. Veterans Aging Cohort Study (VACS): overview and description. Med Care 2006; 44:S13–S24.
38. Mocroft A, Barry S, Sabin CA, Lepri AC, Kinloch S, Drinkwater A, et al
. The changing pattern of admissions to a London hospital of patients with HIV: 1988–1997. Royal Free Centre for HIV Medicine. AIDS 1999; 13:1255–1261.
39. Rhone SA, Hogg RS, Yip B, Sherlock C, Conway B, Schechter MT, et al
. The antiviral effect of ritonavir and saquinavir in combination amongst HIV-infected adults: results from a community-based study. AIDS 1998; 12:619–624.
40. Mocroft A, Gill MJ, Davidson W, Phillips AN. Predictors of a viral response and subsequent virological treatment failure in patients with HIV starting a protease inhibitor. AIDS 1998; 12:2161–2167.
41. Jaen A, Casabona J, Esteve A, Miro JM, Tural C, Ferrer E, et al
. Clinical–epidemiological characteristics and antiretroviral treatment trends in a cohort of HIV infected patients. The PISCIS Project. Med Clin (Barc) 2005; 124:525–531.
42. Centers for Disease Control and Prevention. 1993 Revised classification system for HIV infection and expanded surveillance case definitions for AIDS among adolescents and adults
43. Olsen CH, Gatell J, Ledergerber B, Katlama C, Friis-Moller N, Weber J, et al
. Risk of AIDS and death at given HIV-RNA and CD4 cell count, in relation to specific antiretroviral drugs in the regimen. AIDS 2005; 19:319–330.
44. Riddler SA, Haubrich R, DiRienzo G, Peeples L, Powderly WG, Klingman KL, et al. A prospecitve randomized, phase III trial of NRTI-, PI-, and NNRTI-sparing regimens for initial treatment of HIV-infection - ACTG 5142.
In: Program and Abstracts of the XVI International AIDS Conference
; 13–18 August 2006; Toronto, Canada. Abstract THLB0204.
45. von Wyl V, Yerly S, Boni J, Burgisser P, Klimkait T, Battegay M, et al
. Emergence of HIV-1 drug resistance in previously untreated patients initiating combination antiretroviral treatment: a comparison of different regimen types. Arch Intern Med 2007; 167:1782–1790.
46. Hogg RS, Bangsberg DR, Lima VD, Alexander C, Bonner S, Yip B, et al
. Emergence of drug resistance is associated with an increased risk of death among patients first starting HAART. PLoS Med 2006; 3:e356.
47. van Leth F, Phanuphak P, Ruxrungtham K, Baraldi E, Miller S, Gazzard B, 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.
48. Hogg RS, Yip B, Chan KJ, Wood E, Craib KJ, O'Shaughnessy MV, Montaner JS. Rates of disease progression by baseline CD4 cell count and viral load after initiating triple-drug therapy. JAMA 2001; 286:2568–2577.
49. Pocock SJ, Elbourne DR. Randomized trials or observational tribulations? N Engl J Med 2000; 342:1907–1909.
This article has been cited 4 time(s).
Hiv MedicineNevirapine/zidovudine/lamivudine has superior immunological and virological responses not reflected in clinical outcomes in a 48-week randomized comparison with abacavir/zidovudine/lamivudine in HIV-infected Ugandan adults with low CD4 cell countsHiv Medicine
Journal of Antimicrobial ChemotherapyEfavirenz: a decade of clinical experience in the treatment of HIVJournal of Antimicrobial Chemotherapy
Current Opinion in Infectious DiseasesCohort studies: to what extent can they inform treatment guidelines?Current Opinion in Infectious Diseases
JAIDS Journal of Acquired Immune Deficiency SyndromesEarly Clinical and Programmatic Outcomes with Tenofovir-Based Antiretroviral Therapy in ZambiaJAIDS Journal of Acquired Immune Deficiency Syndromes
AIDS; AIDS-related opportunistic infections; antiretroviral therapy; cohort analysis; highly active; HIV; mortality; viral load
© 2008 Lippincott Williams & Wilkins, Inc.
Highlight selected keywords in the article text.