Factors associated with remaining on initial randomized efavirenz-containing regimens
Smurzynski, Marlenea; Wu, Kunlinga; Schouten, Jeffrey T.b,c; Lok, Judith J.a; Bosch, Ronald J.a; Taiwo, Babafemid; Johnson, Victoria Annee; Collier, Ann C.c
aCenter for Biostatistics in AIDS Research, Harvard School of Public Health, Boston, Massachusetts
bFred Hutchinson Cancer Research Center, Seattle, Washington
cUniversity of Washington, Seattle, Washington
dNorthwestern University Feinberg School of Medicine, Division of Infectious Diseases, Chicago, Illinois
eBirmingham Veterans Affairs Medical Center and University of Alabama at Birmingham School of Medicine, Birmingham, Alabama, USA.
Correspondence to Marlene Smurzynski, PhD, Department of Epidemiology and Biostatistics, School of Public Health and Health Services, George Washington University, 2100-W Pennsylvania Avenue NW, 8th floor Washington, DC 20037, USA. Tel: +1 202 578 6862; e-mail: email@example.com
Received 6 November, 2012
Revised 15 March, 2013
Accepted 18 March, 2013
Objective: Efavirenz (EFV) along with two nucleoside reverse transcriptase inhibitors (NRTIs) is a recommended initial antiretroviral regimen. Understanding characteristics related to EFV success is clinically useful.
Design: Data from 2220 antiretroviral-naive participants randomized to EFV and two to three NRTIs in four ACTG trials as well as a long-term cohort were analysed.
Methods: Logistic regression, using inverse probability of censoring weighting to address selective-follow-up bias, was used to identify factors associated with EFV success (no treatment interruptions of >30 days, HIV RNA < 200 copies/ml) 1 year post initiation and at years 2–5 if successful at year 1.
Results: Pretreatment characteristics were median age 38 years, 82% male, 40% white, 10% history of IDU (HxIDU), median CD4+ T-lymphocyte 227 cells/μl and 33% HIV RNA more than 100 000 copies/ml. In a multivariable model, factors associated with year 1 EFV success were race [white odds ratio (OR) 1.5; P < 0.001; Hispanic OR 1.5; P = 0.003 vs. black], no pretreatment sign/symptom grade 3 or higher (OR 1.7; P = 0.008) and no HxIDU (OR 1.7; P = 0.001). Predictors of EFV success at years 2–5 were no HxIDU (years 2–5; ORs 1.9–2.2); self-reported complete (4 days prior to study visit) adherence during year 1 (years 2–4; ORs 1.6–1.9); fewer missed visits during year 1 (years 2, 4, 5; ORs 0.92–0.98/1% increase); HIV RNA less than 50 copies/ml at year 1 (years 2, 3; ORs 1.9–2.2); and older age (>50 vs. ≤30 years) (years 2–4: ORs 2.3–3.7).
Conclusion: Characteristics predictive of EFV success in the short-term and longer term differed except for HxIDU. Behaviours occurring during year 1 were associated with EFV success over 5 years.
A combination antiretroviral regimen consisting of a nonnucleoside reverse transcriptase inhibitor (NNRTI) as well as two nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) can provide durable viral suppression and immunologic enhancement for HIV-positive individuals. Efavirenz (EFV) is the preferred initial NNRTI in the United States [1,2]. Individuals taking EFV-containing regimens can have a more favourable virologic response than those taking protease inhibitor based or triple-NRTI regimens [3–6]. EFV-containing regimens are associated with lower mortality and incidence of AIDS-defining events (ADEs), and better immunologic and virologic outcomes than those containing nevirapine . Central nervous system (CNS) side effects are common with EFV-containing regimens but are usually mild, resolve within several weeks and are rarely treatment-limiting [8,9].
With tolerable, effective initial regimens, persons can achieve long-term HIV viral suppression; however, durability is affected by a variety of factors. Chances of success are greatest with initial as opposed to subsequent regimens . With newer agents, less frequent dosing and simplified combination drugs, duration of use of initial antiretroviral regimens has increased [11,12]. Shorter initial antiretroviral regimen durations have been associated with higher baseline HIV RNA level, IDU, prior ADEs, calendar year of antiretroviral initiation, regimen type and non-Hispanic black race/ethnicity [10–13]. Blacks were more likely than other races to have virologic failure and regimen discontinuation when randomized to an initial EFV-containing regimen [14,15]; pharmacogenomic differences in drug-metabolizing enzymes might partially explain these differences .
To evaluate whether EFV-based regimens are optimal initial regimens , it is useful to understand factors related to longer term success. Randomized ACTG studies of initial HAART along with a long-term observational study [ACTG Longitudinal Linked Randomized Trials (ALLRT)] provide an opportunity to identify characteristics related to successfully remaining on initial EFV-containing regimens a year after initiating antiretroviral drugs, and in addition, for those still on an EFV-containing regimen at year 1, it is possible to examine whether baseline or factors collected during the first year on EFV are related to remaining on an EFV-containing regimen while virally suppressed 2–5 years after randomization.
Materials and methods
ART-naive patients with confirmed HIV infection in four randomized ACTG clinical trials (ACTG 384 , A5095 , A5142  and A5202 ) were included in this analysis (N = 2220). Individuals were randomized to EFV-containing treatment arms with at least two NRTIs [excluding arms with didanosine(ddI)/stavudine(d4T) because of the increased toxicity of this combination and individuals from non-United States-based sites who were not eligible to enrol in ALLRT]. ACTG 384 was a blinded study, whereas A5142 and A5202 were open-label studies; A5095 was initially blinded but became open-label in February 2003, following a data safety monitoring board (DSMB) review. Clinical trial participants were eligible to enrol into the ACTG long-term observational ALLRT study ; 67% of these 2220 clinical trial participants opted to coenrol in ALLRT. Data from the clinical trials and ALLRT were used for these analyses.
Frequency of visits and date of clinical trial final visit were determined by the clinical trial protocols; for individuals who coenrolled in ALLRT, study visits were every 16 weeks after the clinical trial ended. Data were analysed beginning at clinical trial entry (October 1998–December 2007) with follow-up continuing through the first of June 2010 (data sets frozen), last known study visit or death. Institutional Review Boards at participating sites approved the protocols; individuals provided written informed consent.
Data were collected from participants at the ACTG sites and reported on standardized case report forms; laboratory work was processed as outlined in standardized operating ACTG laboratory procedure manuals. Information on antiretroviral use was reviewed and updated at each study visit and assessed through year 10. Baseline demographics collected from the participants included age, sex, self-reported race/ethnicity and history of IDU (HxIDU). CD4+ T-lymphocyte count, HIV RNA (copies/ml, HIV RNA), signs/symptoms (peripheral neuropathy grade ≥2, others ≥grade 3) [22,23] and ADEs  were assessed at baseline and during the first year, whereas factors assessed only during the first year included evidence of a short treatment interruption (<30 days off EFV), laboratory toxicities (≥grade 3), self-reported adherence to medications (number of missed doses in the past 4 days)  and percentage of missed clinic visits.
The main outcome of interest was ‘EFV success’ defined as remaining on an EFV-containing regimen regardless of a switch in background NRTIs or treatment interruptions of less than 30 days and the most recent HIV RNA viral load of less than 200 copies/ml on/before the evaluable year.
A subset of individuals had information available on the CYP2B6 metabolizer genotype, a composite of 516G→T and 983T→C genotypes. Individuals were either intensive metabolizers (zero polymorphisms in the composite genotype), intermediate (one polymorphism) or slow (at least two polymorphisms) metabolizers; slow and intermediate metabolizers generally have higher plasma concentrations of EFV than intensive metabolizers [7,26].
The primary objective of this analysis was to identify factors associated with EFV success. There were two foci of the primary objective. A first aim was to examine baseline and pretreatment factors related to ‘EFV success’ at year 1. As a second aim, individuals who had initial EFV success at year 1 were analysed to examine baseline and year 1 characteristics related to ‘EFV success’ at years 2–5.
Participants who went off EFV for more than 30 days regardless of HIV RNA level, or who died, were considered off EFV on the last reported date of EFV use. If an individual was reportedly taking EFV when she/he went off study or as of June 2010, the censor date was off-study date or June 2010, respectively.
Inverse probability of censoring weighting (IPCW) techniques, redistributing weights of individuals without a known outcome to individuals with an observed outcome and with similar characteristics and history, were used to reduce informative censoring bias due to selective follow-up. IPCW attempts to estimate the probability of EFV success in the whole cohort, not just in those who were not censored before the time point of interest. When a patient on EFV is lost to follow-up, his or her weight gets transferred to ‘similar’ patients still in follow-up. If there are factors associated both with being lost to follow-up and EFV success, then simply excluding individuals due to an unknown outcome will lead to biased results; IPCW techniques can help reduce this drop-out bias [27–29]. Pooled logistic regression was used to estimate the IPCW.
Different approaches were used to estimate probabilities in the year 1 model and models for years 2–5. In year 1, only 2% of individuals had an unknown outcome; factors related to censoring due to drop-out included IDU and HIV RNA level; inverse probability weights for year 1 were constructed using the proportion of observed individuals in these groups, estimating the probability of remaining in follow-up among each group.
For years 2–5, unstabilized inverse probability weights were calculated from pooled logistic regression models using predicted probabilities of not remaining in follow-up, given past observed patient characteristics. Predetermined baseline covariates included age, sex, race, HxIDU, site location; time-varying covariates included 16-week CD4+ T-lymphocyte count and HIV RNA level . Separate models were built for individuals while on parent study and during ALLRT only. Similar pooled logistic regression models were fit for administrative censoring (i.e. individuals on study, receiving EFV as of June 2010 but without an outcome for a certain year).
Probability of successfully remaining on EFV at years 1–10 was estimated using IPCW weights. Kaplan–Meier estimates, which provide a nonparametric estimate in the absence of informative censoring, were calculated for comparison.
An IPCW multivariable logistic regression model was fit to examine predictors of ‘EFV success’ at year 1. Predetermined baseline covariates included sex, race/ethnicity, age, HxIDU, CD4+ T-lymphocyte count, HIV RNA, signs/symptoms and ADEs. Among participants who had ‘EFV success’ at year 1, an IPCW multivariable logistic regression was fit to predict ‘EFV success’ at years 2–5. Models included baseline characteristics from the year 1 model, as well as additional predetermined variables collected at year 1 (CD4+ T-lymphocyte count, HIV RNA) and events occurring during the first year on study (signs/symptoms, toxicities, ADEs, adherence, missed clinic visits).
Due to variation in estimated IPCW weights not accounted for in logistic regression models, standard errors and confidence intervals derived directly from the model are biased; therefore, 95% confidence intervals and P values were calculated using a bootstrap method (5000 replicates).
A sensitivity analysis was performed to examine the role of the CYP2B6 metabolizer genotype in remaining on an EFV-based regimen among 70% of individuals with genotype information (N = 1553). In yearly models, using the same variables noted above, CYP2B6 metabolizer genotype (slow and intermediate metabolizers compared with intensive metabolizers) was added; this analysis was done separately by race/ethnicity.
Of the 2220 individuals in the analysis, 727 individuals enrolled only in a clinical trial and 1493 individuals were also followed in ALLRT. Participants were predominantly male (Table 1); 40% were white with a median age of 38 years. Twenty percent had CD4+ T-lymphocyte count of 50 cells/μl or less (median 227 cells/μl) and 33% had HIV RNA more than 100 000 copies/ml at baseline (Table 1). There was no evidence that individuals who enrolled in ALLRT differed from those who did not by baseline factors or demographic status (P > 0.05) with the exception of race (whites more likely to enrol than blacks; P = <0.001).
Between baseline and year 1, 526 of the 2220 persons in the analysis were observed to have discontinued EFV. An additional 48 individuals went off study while still on EFV (52% not able to get to clinic, 15% withdrew consent, 10% not willing to adhere, 10% lost to follow-up, 8% severely debilitated, 4% at sites that closed), leaving a total of 1646 individuals eligible for further analysis. Of these 1646 participants, 46 had an HIV RNA viral load of more than 200 copies/ml, and subsequently were not considered successful under the definition of EFV success. Thus, 1600 individuals were included in further analyses of those who had initial EFV success at year 1.
Among 1600 individuals successfully remaining on EFV at year 1 (Table 1), median CD4+ T-lymphocyte count was 405 cells/μl, with a median increase of 180 cells/μl from baseline. Almost all (94%) individuals had HIV RNA viral load less than 50 copies/ml. Fifteen percent of individuals had a grade 3/4 sign/symptom (excluding CNS) and 17% had an ADE prior to the end of year 1. The majority of individuals never missed a clinic visit.
EFV-containing regimens included at least two NRTIs; NRTIs varied by parent study [14,17–19]. The estimated percentage of individuals successfully remaining on a randomized EFV-based regimen at year 1 was 74%; given a participant had EFV success at year 1, the percentages of subsequent EFV success were year 2: 88%, year 3: 78%, year 4: 61% and year 5: 50% (Table 2). The probability of remaining on an EFV-containing regimen 10 years after initiation was 21%, although only a small number of individuals reached this milestone (Table 2).
In the first year, 526 participants reported EFV discontinuation for at least 30 days (Fig. 1). Most participants switched to another antiretroviral regimen (n = 335; 64%). Among this group, the majority (n = 284) switched within 60 days of discontinuing EFV. A smaller number returned to an EFV-containing regimen with at least two NRTIs before the end of year 1 (n = 66); 25 of these participants had HIV RNA less than 200 copies/ml at year one. Among the remaining 191 individuals who did not switch antiretroviral regimens, 71 went off study, nine died and 111 individuals remained in follow-up (Fig. 1). A total of 345 individuals had short-term treatment interruptions of 30 days or less; reasons for interruptions included drug hypersensitivity, rash, individual requested antiretroviral break, incarceration and nausea.
Among this group of 526 participants who went off treatment, the most common reasons recorded were clinician/study participant/guardian decision (17%) and noncompliant with study visits medication (16%). Virologic failure was reported as the reason for treatment discontinuation in 13% of cases. Clinical symptoms and signs were reported as an off-treatment reason and were primarily composed of rash/allergic reaction (11%), CNS-related symptoms (10%) and neuropsychiatric/mood alteration (6%). One percent of participants discontinued treatment because they became pregnant. Between year 1 and year 2, the most prevalent reason for discontinuing medication remained clinician/study participant/guardian decision (21%), with virologic failure (16%) and noncompliance (15%) having similar reported rates. Neuropsychiatric/mood alteration (7%) remained a leading reason for discontinuation, whereas there were no reports of rash/allergic reaction and only 3% reported CNS symptoms as a reason to discontinue. Three percent of individuals reported pregnancy as the reason for discontinuation. Reason for study medication discontinuation was only available during the time participants were on parent clinical trials; thus, this information could not be incorporated into the latter years of the analysis.
Factors associated with efavirenz success at year 1
Being older, white or Hispanic/other (vs. black), having no IDU history and having no signs/symptom of grade 3/4 prior to beginning antiretrovirals were associated with EFV success at year 1 (Table 3). Sex, baseline CD4+ T-lymphocyte count, baseline HIV RNA and having an ADE prior to beginning antiretrovirals were not significantly associated with success.
Sex, race, age and IDU were then included in models as covariates to examine the predictive role of baseline signs/symptoms (Table 3; Sensitivity Model: A), ADEs (Sensitivity Model: B) and baseline HIV RNA and CD4+ T-lymphocyte count levels (Sensitivity Model: C). In these models, the absence of signs/symptoms (P = 0.005) was associated with EFV success and history of an ADE prior to baseline (P = 0.13) was not associated with EFV success. Baseline HIV RNA (P = 0.72) was not predictive and low CD4+ T-lymphocyte count was just on the edge of statistical significance (Table 3).
Factors associated with efavirenz success at years 2–5
Among people with EFV success at year 1 (n = 1600), self-reported high adherence to antiretrovirals during the first year and older age were predictive of continued EFV success at years 2–4 (P < 0.05) (Table 4). Persons with year 1 HIV RNA less than 50 (vs. 50–199) copies/ml had greater odds of EFV success at years 2–3 (P < 0.05), but this was not evident at years 4–5. As percentage of year 1 missed visits increased, probability of remaining on suppressive EFV decreased; this relationship was significant at years 2, 4 and 5 (P < 0.05). People with no history of IDU were approximately two times more likely to have EFV success at years 2–5. For years 2–5, sex, race, baseline CD4+ T-lymphocyte count and HIV RNA and year 1 CD4+ T-lymphocyte count did not predict EFV success; neither did diagnosis with an ADE, nor signs/symptoms (including CNS signs/symptoms) at baseline nor reported toxicities during year 1.
Of note, 75% of participants who discontinued EFV between year 1 and year 2 had HIV RNA less than 50 copies/ml and 42% had CD4+ T-lymphocyte count at least 500 cells/μl at the point closest to when they stopped EFV; this trend continued with the percentages rising in years 4–5 (Year 4/Year 5: 87%/78% viral load <50 copies/ml; 64%/62% CD4+ T-lymphocyte count ≥500 cells/μl).
CYP2B6 metabolizer genotype/subgroups
In the subgroup analysis of CYP2B6 metabolizer genotype polymorphisms, there was no association (P > 0.05) seen between metabolizer polymorphisms and EFV success, separately by race. At year 1, when adding this variable to the final multivariable model, no significant relationship was seen between intermediate vs. intensive metabolizers and EFV success [black: odds ratio (OR) 1.1, P = 0.63; white: OR 0.8, P = 0.24; Hispanic: OR 0.9, P = 0.70] and slow vs. intensive metabolizers and EFV success (black: OR 1.1, P = 0.86; white: OR 0.6, P = 0.23; Hispanic: OR 1.0, P > 0.9). Similar findings were identified in years 2–4, although a statistically significant association was seen among blacks at year 5 (intermediate vs. intensive metabolizer: OR 2.1, P = 0.008; slow vs. intensive metabolizer: OR 1.1, P = 0.8).
A majority (74%) of 2220 ACTG study participants randomized to initiate HAART-containing EFV with concurrent NRTIs remained on an EFV-containing regimen with virologic suppression after 1 year, based on methods that address informative loss-to-follow-up; 88% and 50% of these participants continued to have EFV success after 2 and 5 years. Factors associated with year 1 EFV success included being older, white or Hispanic, having no or minimal clinical signs/symptoms prior to antiretroviral initiation and no HxIDU. Factors that were not significant included sex, pretreatment CD4+ T-lymphocyte count and HIV RNA, and pre-antiretroviral ADEs.
Older participants were more likely to remain on EFV than younger participants; this association remained after adjusting for adherence and missed visits. As expected, higher adherence  and a lower number of missed visits  during year 1 were predictive of long-term EFV success. In persons with HIV, pain and mood disorders (such as depression) have been associated with missed clinic visits ; unmeasured behavioural factors related to pain, mood disorders or other behavioural issues might affect medication and visit adherence and thus impact subsequent EFV success. Factors potentially amenable to interventions, such as attention to pain issues, treatment of mood disorders and support to facilitate clinic attendance and guidance on how to enhance linkage to and retention in HIV clinic care, could potentially increase EFV success .
Self-reported race/ethnicity was related to successfully remaining on EFV in the first year, but not related to long-term continued EFV success. At year 1, whites and Hispanics were more likely to remain on EFV than people who self-identified as black race. Although we anticipated that CYP2B6 polymorphisms that impact EFV metabolism might explain these findings [16,26], the results did not support this hypothesis.. Other potential explanations include that these polymorphisms do not significantly affect EFV effectiveness, or that unmeasured confounders obscured the relationship between CYP2B6 polymorphisms and EFV success. Additional data on social characteristics that impact antiretroviral adherence may have helped to address these issues; however, these analyses could not be explored given limited data on social characteristics.
Signs/symptoms of grades 3/4 prior to ART initiation were associated with discontinuation of EFV during year 1, but as might be expected, having a grade 3/4 sign/symptom during year 1 was not related to success in later years. Participants experiencing complications pretreatment or with active symptoms at antiretrovirals initiation may have had a lower tolerance for drug-associated side effects or side effects in addition to preexisting signs/symptoms may make it more difficult to continue an antiretrovirals regimen. Another possibility is that individuals reporting signs/symptoms of grade 3/4 may have immune reconstitution inflammatory syndrome (IRIS); IRIS could dissipate and will not be relevant to success in later years, if someone remains on EFV through the end of year 1.
A history of IDU was negatively associated with EFV success; participants who reported being current (<1%) or prior (10%) IDU were more likely to discontinue EFV during year 1, and if still on an EFV-containing regimen at year 1, in subsequent years. Others have reported that persons with a history of IDU, taking EFV-based regimens, were less likely to achieve viral suppression than persons taking atazanavir/ritonavir-based regimens ; thus, EFV may not be the ideal third drug for some persons with IDU history. One potential explanation could be differences in pharmacokinetics among substance vs. nonsubstance users , although most participants did not report current use. Other possible explanations for failure to remain on EFV with history of IDU include higher rates of concomitant hepatitis C viral (HCV) infection, which is associated with higher rates of hepatotoxicity , the need for, but potential unavailability of, increased doses of methadone in drug substitution programmes, to achieve similar effects among former IDUs receiving EFV ; higher rates of depression, poorer social support and/or lower tolerance for side effects. HCV serologic results and diagnoses were not available at baseline for all individuals and thus were not included as a potential predictor of EFV success. However, among the subset with HCV data available (n = 1972), a larger percentage of participants with HxIDU had detectable HCV antibody (40%) than participants without HxIDU (<4%). It seems likely that HCV coinfection and accompanying complications  may have contributed to lower EFV success rates.
CD4+ T-lymphocyte counts were not predictive of EFV success. A large proportion of people who discontinued EFV in years 2–5 had CD4+ T-lymphocyte count more than 500 cells/μl (40–62%) and the majority (75–87%) had HIV RNA less than 50 copies/ml, suggesting that factors other than virologic and immunologic failure are related to EFV discontinuation. Portions of follow-up among these participants occurred when CD4+ T-lymphocyte-guided and structured treatment interruptions were popular treatment startegies, prior to the Strategies for Management of Antiretroviral Therapy (SMART) Study findings ; thus, discontinuation may be construed as a treatment success rather than a failure.
IPCW methods were used to account for possible informative dropout; this method can be compared with the redistribute-to-the-right algorithm that leads to the Kaplan–Meier estimator . In this analysis, weights never became extreme (range in year 1: 1.011–1.079; years 2–5: 1.047–3.395). Using the IPCW method, the percentage of individuals successfully remaining on EFV at year 7 is estimated to be 45. By contrast, the Kaplan–Meier method (52% EFV success rate at year 7) likely provides an overestimate of success, as it is based on the assumption that censoring is noninformative.
Even with appropriate statistical methods, a limitation of our study is that outcomes were not available for all study enrolees. There may be variables related to remaining on EFV that were not measured in ALLRT or the clinical trials; HIV-1 drug resistance (EFV-resistant minority HIV variants), host inflammatory markers or additional genetic traits could potentially, significantly affect EFV success. In addition, generalizability is a potential concern when reporting clinical trial results; however, when specifically comparing virologic failure outcomes from two of these clinical trials with the Antiretroviral Therapy Cohort Collaboration, results were similar, demonstrating that findings from these trials may be generalizable to a wider group of HIV patients .
These analyses focused on baseline and characteristics during year 1 of EFV-containing ART that predicted longer term successful EFV use. Whereas selected baseline factors were associated with first year success, other than HxIDU, baseline factors were not predictive of longer term success on EFV over 5 years. In contrast, behavioural characteristics during the initial year of treatment were associated with long-term EFV success. These results suggest that assessment of behaviour after initiating ART and interventions designed to improve clinic attendance, increase medication adherence and better linkage to and retention in HIV care might result in longer term success on first-line EFV-containing regimens.
The authors recognize the generous dedication of the many participants volunteering for the ALLRT study and for the clinical trials, and thank them for their time and effort. In addition, the authors acknowledge the contributions of the investigators and staff, at the AIDS Clinical Research Sites, who collected samples and clinical data used to complete analysis. We would also like to thank the ALLRT (A5001) team members and team members of the contributing ACTG clinical trials (ACTG 384, A5095, A5142, A5202) for their efforts.
This work was supported by the Statistical and Data Management Center of the AIDS Clinical Trials Group, under the National Institute of Allergy and Infectious Diseases grant [1 UM1 AI068634] and the Leadership grant [1 UM1 AI068636]. Members of the team were also supported under the following National Institute of Allergy and Infectious Diseases grants: UAB Center for AIDS Research [P30AI27767], Alabama Clinical Trials Unit [UM1AI069452], UW Clinical HIV Integrated Research Program [5 UM1 AI 69434–06] and [R01AI100762].
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Allergy And Infectious Diseases or the National Institutes of Health.
Findings from this analysis have not been previously published, but were presented at the 49th Annual Meeting of the Infectious Diseases Society of America (IDSA), 20–23 October 2011, in Boston, Massachusetts, USA [Abstract 32306].
Conflicts of interest
There are no conflicts of interest.
2. Thompson MA, Aberg JA, Hoy JF, Telenti A, Benson C, Cahn P, et al. Antiretroviral treatment of adult HIV infection. 2012 Recommendations of the International Antiviral Society-USA Panel
3. Staszewski S, Morales-Ramirez J, Tashima KT, Rachlis A, Skiest D, Stanford J, et al. Efavirenz plus zidovudine and lamivudine, efavirenz plus indinavir, and indinavir plus zidovudine and lamivudine in the treatment of HIV-1 infection in adults. Study 006 Team
. N Engl J Med
4. Lucas GM, Chaisson RE, Moore RD. Comparison of initial combination antiretroviral therapy with a single protease inhibitor, ritonavir and saquinavir, or efavirenz
5. Kuritzkes DR, Ribaudo HJ, Squires KE, Koletar SL, Santana J, Riddler SA, et al. ACTG A5166s Protocol TeamPlasma HIV-1 RNA dynamics in antiretroviral-naive subjects receiving either triple-nucleoside or efavirenz-containing regimens: ACTG A5166s
. J Infect Dis
6. Edén A, Andersson LM, Andersson O, Flamholc L, Josephson F, Nilsson S, et al. Differential effects of efavirenz, lopinavir/r, and atazanavir/r on the initial viral decay rate in treatment naïve HIV-1-infected patients
. AIDS Res Hum Retroviruses
7. The HIV-CAUSAL CollaborationThe effect of efavirenz versus nevirapine-containing regimens on immunologic, virologic and clinical outcomes in a prospective observational study
8. Haas DW, Ribaudo HJ, Kim RB, Tierney C, Wilkinson GR, Gulick RM, et al. Pharmacogenetics of efavirenz and central nervous system side effects: an Adult AIDS Clinical Trials Group study
9. Clifford DB, Evans S, Yang Y, Acosta EP, Goodkin K, Tashima K, et al. Impact of efavirenz on neuropsychological performance and symptoms in HIV-infected individuals
. Ann Intern Med
10. Palella FJ Jr, Chmiel JS, Moorman AC, Holmberg SD. HIV Outpatient Study InvestigatorsDurability and predictors of success of highly active antiretroviral therapy for ambulatory HIV-infected patients
11. Willig JH, Abroms S, Westfall AO, Routman J, Adusumilli S, Varshney M, et al. Increased regimen durability in the era of once-daily fixed-dose combination antiretroviral therapy
12. Chen RY, Westfall AO, Mugavero MJ, Cloud GA, Raper JL, Chatham AG, et al. Duration of highly active antiretroviral therapy regimens
. Clin Infect Dis
13. Ahdieh-Grant L, Tarwater PM, Schneider MF, Anastos K, Cohen M, Khalsa A, et al. Women's Interagency HIV StudyFactors and temporal trends associated with highly active antiretroviral therapy discontinuation in the Women's Interagency HIV Study
. J Acquir Immune Defic Syndr
14. Gulick RM, Ribaudo HJ, Shikuma CM, Lalama C, Schackman BR, Meyer WA 3rd, et al. AIDS Clinical Trials Group (ACTG) A5095 Study TeamThree- vs four-drug antiretroviral regimens for the initial treatment of HIV-1 infection: a randomized controlled trial
15. Schackman BR, Ribaudo HJ, Krambrink A, Hughes V, Kuritzkes DR, Gulick RM. Racial differences in virologic failure associated with adherence and quality of life on efavirenz-containing regimens for initial HIV therapy: results of ACTG A5095
. J Acquir Immune Defic Syndr
16. Ribaudo HJ, Haas DW, Tierney C, Kim RB, Wilkinson GR, Gulick RM, et al. Adult AIDS Clinical Trials Group StudyPharmacogenetics of plasma efavirenz exposure after treatment discontinuation: an Adult AIDS Clinical Trials Group Study
. Clin Infect Dis
17. Maggiolo F. Efavirenz: a decade of clinical experience in the treatment of HIV
. J Antimicrob Chemother
18. Shafer RW, Smeaton LM, Robbins GK, De Gruttola V, Snyder SW, D’Aquila RT, et al. AIDS Clinical Trials Group 384 TeamComparison of four-drug regimens and pairs of sequential three-drug regimens as initial therapy for HIV-1 infection
. N Engl J Med
19. Riddler SA, Haubrich R, DiRienzo AG, Peeples L, Powderly WG, Klingman KL, et al. AIDS Clinical Trials Group Study A5142 TeamClass-sparing regimens for initial treatment of HIV-1 infection
. N Engl J Med
20. Sax PE, Tierney C, Collier AC, Daar ES, Mollan K, Budhathoki C, et al. AIDS Clinical Trials Group Study A5202 TeamAbacavir/lamivudine versus tenofovir DF/emtricitabine as part of combination regimens for initial treatment of HIV: final results
. J Infect Dis
21. Smurzynski M, Collier AC, Koletar SL, Bosch RJ, Wu K, Bastow B, Benson CA. AIDS clinical trials group longitudinal linked randomized trials (ALLRT): rationale, design, and baseline characteristics
. HIV Clin Trials
22. National Institute of Allergy and Infectious Diseases, Division of AIDSDivision of AIDS Table for grading the severity of adult and pediatric adverse events
. Bethesda, MD:US Department of Health and Human Services; 2004.
23. National Institute of Allergy and Infectious Diseases, Division of AIDSDivision of AIDS Table for grading the severity of adult adverse events
. Bethesda, MD:US Department of Health and Human Services; 1992.
24. Smurzynski M, Wu K, Benson CA, Bosch RJ, Collier AC, Koletar SL. Relationship between CD4+ T-cell counts/HIV-1 RNA plasma viral load and AIDS-defining events among persons followed in the ACTG Longitudinal Linked Randomized Trials Study
. J Acquir Immune Defic Syndr
25. Reynolds NR, Sun J, Nagaraja HN, Gifford AL, Wu AW, Chesney MA. Optimizing measurement of self-reported adherence with the ACTG Adherence Questionnaire: a cross-protocol analysis
. J Acquir Immune Defic Syndr
26. Ribaudo HJ, Liu H, Schwab M, Schaeffeler E, Eichelbaum M, Motsinger-Reif AA, et al. Effect of CYP2B6, ABCB1, and CYP3A5 polymorphisms on efavirenz pharmacokinetics and treatment response: an AIDS Clinical Trials Group study
. J Infect Dis
27. Robins JM, Rotnitzky A, Zhao LP. Analysis of semiparametric regression models for repeated outcomes in the presence of missing data
. J Am Stat Assoc
28. Cole RC, Hernan MA. Constructing inverse probability weights for marginal structural models
. Am J Epidemiol
29. Lok JJ, Bosch RJ, Benson CA, Collier AC, Robbins GK, Shafer RW, Hughes MD. ALLRT teamLong-term increase in CD4+ T-cell counts during combination antiretroviral therapy for HIV-1 infection
30. Krishnan S, Wu K, Smurzynski M, Bosch RJ, Benson CA, Collier AC, et al. ALLRT/A5001 TeamIncidence rate of and factors associated with loss to follow-up in a longitudinal cohort of antiretroviral-treated HIV-infected persons: an AIDS Clinical Trials Group (ACTG) Longitudinal Linked Randomized Trials (ALLRT) analysis
. HIV Clin Trials
31. Bartlett JA. Addressing the challenges of adherence
. J Acquir Immune Defic Syndr
2002; 29 (Suppl 1):S2–S10.
32. Mugavero MJ, Lin HY, Allison JJ, Giordano TP, Willig JH, Raper JL, et al. Racial disparities in HIV virologic failure: do missed visits matter?
. J Acquir Immune Defic Syndr
33. Merlin JS, Westfall AO, Raper JL, Zinski A, Norton WE, Willig JH, et al. Pain, mood, and substance abuse in HIV: implications for clinic visit utilization, antiretroviral therapy adherence, and virologic failure
. J Acquir Immune Defic Syndr
34. Thompson MA, Mugavero MJ, Amico KR, Cargill VA, Chang LW, Gross R, et al. Guidelines for improving entry into and retention in care and antiretroviral adherence for persons with HIV: evidence-based recommendations from an International Association of Physicians in AIDS Care panel
. Ann Intern Med
35. Lima VD, Nosyk B, Wood E, Kozai T, Zhang W, Chan K, Montaner JS. Assessing the effectiveness of antiretroviral regimens in cohort studies involving HIV-positive injection drug users
36. Ma Q, Zingman BS, Luque AE, Fischl MA, Gripshover BM, Venuto CS, et al. Therapeutic drug monitoring of protease inhibitors and efavirenz in HIV-infected individuals with active substance-related disorders
. Ther Drug Monit
37. Fuping G, Wei L, Yang H, Zhifeng Q, Lingyan Z, Yanling L, Taisheng L. Impact of hepatitis C virus coinfection on HAART in HIV-infected individuals: multicentric observation cohort
. J Acquir Immune Defic Syndr
38. Tossonian HK, Raffa JD, Grebely J, Trotter B, Viljeon M, Mead A, et al. Methadone dosing strategies in HIV-infected injection drug users enrolled in a directly observed therapy program
. J Acquir Defic Syndr
39. El-Sadr WM, Lundgren JD, Neaton JD, Gordin F, Abrams D, Arduino RC, et al. Strategies for Management of Antiretroviral Therapy (SMART) Study GroupCD4+ count-guided interruption of antiretroviral treatment
. N Engl J Med
40. Efron B. The two sample problem with censored data
. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Volume 4. June 21-July 18, 1965 and December 27, 1965-January 7, 1966, Berkeley, CA. University of California Press; 1967. 831–853.
41. Mugavero MJ, May M, Ribaudo HJ, Gulick RM, Riddler SA, Haubrich R, et al. AIDS Clinical Trial Group DACS 241 Team; AIDS Clinical Trial Group Study 5095 Team; AIDS Clinical Trial Group Study 5142 team; Antiretroviral Cohort CollaborationComparative effectiveness of initial antiretroviral therapy regimens: ACTG 5095 and 5142 clinical trials relative to ART-CC cohort study
. J Acquir Immune Defic Syndr
clinical trials; cohort study; efavirenz; HAART; HIV
© 2013 Lippincott Williams & Wilkins, Inc.
What does "Remember me" mean?
By checking this box, you'll stay logged in until you logout. You'll get easier access to your articles, collections,
media, and all your other content, even if you close your browser or shut down your
To protect your most sensitive data and activities (like changing your password),
we'll ask you to re-enter your password when you access these services.
What if I'm on a computer that I share with others?
If you're using a public computer or you share this computer with others, we recommend
that you uncheck the "Remember me" box.
Highlight selected keywords in the article text.
Data is temporarily unavailable. Please try again soon.