Treatment failure and mortality factors in patients receiving second-line HIV therapy in resource-limited countries

Context Long-term antiretroviral therapy (ART) use in resource-limited countries leads to increasing numbers of patients with HIV taking second-line therapy. Limited access to further therapeutic options makes essential the evaluation of second-line regimen efficacy in these settings. Objectives To investigate failure rates in patients receiving second-line therapy and factors associated with failure and death. Design, Setting, and Participants Multicohort study of 632 patients >14 years old receiving second-line therapy for more than 6 months in 27 ART programs in Africa and Asia between January 2001 and October 2008. Main Outcome Measures Clinical, immunological, virological, and immunovirological failure (first diagnosed episode of immunological or virological failure) rates, and mortality after 6 months of second-line therapy use. Sensitivity analyses were performed using alternative CD4 cell count thresholds for immunological and immunovirological definitions of failure and for cohort attrition instead of death. Results The 632 patients provided 740.7 person-years of follow-up; 119 (18.8%) met World Health Organization failure criteria after a median 11.9 months following the start of second-line therapy (interquartile range [IQR], 8.7-17.0 months), and 34 (5.4%) died after a median 15.1 months (IQR, 11.9-25.7 months). Failure rates were lower in those who changed 2 nucleoside reverse transcriptase inhibitors (NRTIs) instead of 1 (179.2 vs 251.6 per 1000 person-years; incidence rate ratio [IRR], 0.64; 95% confidence interval [CI], 0.42-0.96), and higher in those with lowest adherence index (383.5 vs 176.0 per 1000 person-years; IRR, 3.14; 95% CI, 1.67-5.90 for <80% vs ≥95% [percentage adherent, as represented by percentage of appointments attended with no delay]). Failure rates increased with lower CD4 cell counts when second-line therapy was started, from 156.3 vs 96.2 per 1000 person-years; IRR, 1.59 (95% CI, 0.78-3.25) for 100 to 199/μL to 336.8 per 1000 person-years; IRR, 3.32 (95% CI, 1.81-6.08) for less than 50/μL vs 200/μL or higher; and decreased with time using second-line therapy, from 250.0 vs 123.2 per 1000 person-years; IRR, 1.90 (95% CI, 1.19-3.02) for 6 to 11 months to 212.0 per 1000 person-years; 1.71 (95% CI, 1.01-2.88) for 12 to 17 months vs 18 or more months. Mortality for those taking second-line therapy was lower in women (32.4 vs 68.3 per 1000 person-years; hazard ratio [HR], 0.45; 95% CI, 0.23-0.91); and higher in patients with treatment failure of any type (91.9 vs 28.1 per 1000 person-years; HR, 2.83; 95% CI, 1.38-5.80). Sensitivity analyses showed similar results. Conclusions Among patients in Africa and Asia receiving second-line therapy for HIV, treatment failure was associated with low CD4 cell counts at second-line therapy start, use of suboptimal second-line regimens, and poor adherence. Mortality was associated with diagnosed treatment failure.

Viral suppression rates in salvage treatment with raltegravir improved with the administration of genotypic partially active or inactive nucleoside/tide reverse transcriptase inhibitors

Nucleoside reverse transcriptase inhibitors (NRTIs) are often administered in salvage therapy even if genotypic resistance tests (GRTs) indicate high-level resistance, but little is known about the benefit of these additional NRTIs.

Long-lasting protection of activity of nucleoside reverse transcriptase inhibitors and protease inhibitors (PIs) by boosted PI containing regimens

Background The accumulation of mutations after long-lasting exposure to a failing combination antiretroviral therapy (cART) is problematic and severely reduces the options for further successful treatments. Methods We studied patients from the Swiss HIV Cohort Study who failed cART with nucleoside reverse transcriptase inhibitors (NRTIs) and either a ritonavir-boosted PI (PI/r) or a non-nucleoside reverse transcriptase inhibitor (NNRTI). The loss of genotypic activity <3, 3–6, >6 months after virological failure was analyzed with Stanford algorithm. Risk factors associated with early emergence of drug resistance mutations (<6 months after failure) were identified with multivariable logistic regression. Results Ninety-nine genotypic resistance tests from PI/r-treated and 129 from NNRTI-treated patients were analyzed. The risk of losing the activity of ≥1 NRTIs was lower among PI/r- compared to NNRTI-treated individuals <3, 3–6, and >6 months after failure: 8.8% vs. 38.2% (p = 0.009), 7.1% vs. 46.9% (p<0.001) and 18.9% vs. 60.9% (p<0.001). The percentages of patients who have lost PI/r activity were 2.9%, 3.6% and 5.4% <3, 3–6, >6 months after failure compared to 41.2%, 49.0% and 63.0% of those who have lost NNRTI activity (all p<0.001). The risk to accumulate an early NRTI mutation was strongly associated with NNRTI-containing cART (adjusted odds ratio: 13.3 (95% CI: 4.1–42.8), p<0.001). Conclusions The loss of activity of PIs and NRTIs was low among patients treated with PI/r, even after long-lasting exposure to a failing cART. Thus, more options remain for second-line therapy. This finding is potentially of high relevance, in particular for settings with poor or lacking virological monitoring.

Minor protease inhibitor mutations at baseline do not increase the risk for a virological failure in HIV-1 subtype B infected patients

Background Minor protease inhibitor (PI) mutations often exist as polymorphisms in HIV-1 sequences from treatment-naïve patients. Previous studies showed that their presence impairs the antiretroviral treatment (ART) response. Evaluating these findings in a larger cohort is essential. Methods To study the impact of minor PI mutations on time to viral suppression and time to virological failure, we included patients from the Swiss HIV Cohort Study infected with HIV-1 subtype B who started first-line ART with a PI and two nucleoside reverse transcriptase inhibitors. Cox regression models were performed to compare the outcomes among patients with 0 and ≥1 minor PI mutation. Models were adjusted for baseline HIV-1 RNA, CD4 cell count, sex, transmission category, age, ethnicity, year of ART start, the presence of nucleoside reverse transcriptase inhibitor mutations, and stratified for the administered PIs. Results We included 1199 patients of whom 944 (78.7%) received a boosted PI. Minor PI mutations associated with the administered PI were common: 41.7%, 16.1%, 4.7% and 1.9% had 1, 2, 3 or ≥4 mutations, respectively. The time to viral suppression was similar between patients with 0 (reference) and ≥1 minor PI mutation (multivariable hazard ratio (HR): 1.1 [95% confidence interval (CI): 1.0–1.3], P = .196). The time to virological failure was also similar (multivariable HR:.9 [95% CI:.5–1.6], P = .765). In addition, the impact of each single minor PI mutation was analyzed separately: none was significantly associated with the treatment outcome. Conclusions The presence of minor PI mutations at baseline has no effect on the therapy outcome in HIV infected individuals.

Renal function in patients with HIV starting therapy with tenofovir and either efavirenz, lopinavir or atazanavir

Tenofovir is associated with reduced renal function, but it is not clear whether there is a greater decline in renal function when tenofovir is co-administered with a boosted protease inhibitor rather than with a nonnucleoside reverse transcriptase inhibitor (NNRTI).

Are plasma levels valid surrogates for cellular concentrations of antiretroviral drugs in HIV-infected patients?

Total plasma concentrations are currently measured for therapeutic drug monitoring of HIV protease inhibitors (PIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs). However, the pharmacological target of antiretroviral drugs reside inside cells. To study the variability of their cellular accumulation, and to determine to which extent total plasma concentrations (TPC) correlate with cellular concentrations (CC), plasma and peripheral blood mononuclear cells (PBMCs) were simultaneously collected at single random times after drug intake from 133 HIV infected patients. TPC levels were analysed by high-performance liquid chromatography with ultraviolet detection and CC by LC-MS/MS from peripheral blood mononuclear cells. The best correlations between TPC and CC were observed for nelfinavir (NFV, slope=0.93, r=0.85), saquinavir (SQV, slope=0.76, r=0.80) and lopinavir (LPV, slope=0.87, r=0.63). By contrast, TPC of efavirenz (EFV) exhibited a moderate correlation with CC (slope=0.69, r=0.58), while no correlation was found for nevirapine (NVP, slope=-0.3, r=0.1). Interindividual variability in the CC/TPC ratio was lower for protease inhibitors (coefficients of variation 76%, 61%, and 80% for SQV, NFV and LPV, respectively) than for nonnucleoside reverse transcriptase inhibitors (coefficients of variation 101% and 318%, for EFV and NVP). As routine CC measurement raises practical difficulties, well-correlated plasma concentrations (ie, NFV, SQV and LPV) can probably be considered as appropriate surrogates for cellular drug exposure. For drugs such as EFV or NVP, there may be room for therapeutic drug monitoring improvement using either direct CC determination or other predictive factors such as genotyping of transporters or metabolizing enzyme genes.

Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries

BACKGROUND: Highly active antiretroviral therapy (HAART) is being scaled up in developing countries. We compared baseline characteristics and outcomes during the first year of HAART between HIV-1-infected patients in low-income and high-income settings. METHODS: 18 HAART programmes in Africa, Asia, and South America (low-income settings) and 12 HIV cohort studies from Europe and North America (high-income settings) provided data for 4810 and 22,217, respectively, treatment-naive adult patients starting HAART. All patients from high-income settings and 2725 (57%) patients from low-income settings were actively followed-up and included in survival analyses. FINDINGS: Compared with high-income countries, patients starting HAART in low-income settings had lower CD4 cell counts (median 108 cells per muL vs 234 cells per muL), were more likely to be female (51%vs 25%), and more likely to start treatment with a non-nucleoside reverse transcriptase inhibitor (NNRTI) (70%vs 23%). At 6 months, the median number of CD4 cells gained (106 cells per muL vs 103 cells per muL) and the percentage of patients reaching HIV-1 RNA levels lower than 500 copies/mL (76%vs 77%) were similar. Mortality was higher in low-income settings (124 deaths during 2236 person-years of follow-up) than in high-income settings (414 deaths during 20,532 person-years). The adjusted hazard ratio (HR) of mortality comparing low-income with high-income settings fell from 4.3 (95% CI 1.6-11.8) during the first month to 1.5 (0.7-3.0) during months 7-12. The provision of treatment free of charge in low-income settings was associated with lower mortality (adjusted HR 0.23; 95% CI 0.08-0.61). INTERPRETATION: Patients starting HAART in resource-poor settings have increased mortality rates in the first months on therapy, compared with those in developed countries. Timely diagnosis and assessment of treatment eligibility, coupled with free provision of HAART, might reduce this excess mortality.

Immunologic response to antiretroviral therapy in hepatitis C virus-coinfected adults in a population-based HIV/AIDS treatment program

BACKGROUND: We sought to characterize the impact that hepatitis C virus (HCV) infection has on CD4 cells during the first 48 weeks of antiretroviral therapy (ART) in previously ART-naive human immunodeficiency virus (HIV)-infected patients. METHODS: The HIV/AIDS Drug Treatment Programme at the British Columbia Centre for Excellence in HIV/AIDS distributes all ART in this Canadian province. Eligible individuals were those whose first-ever ART included 2 nucleoside reverse transcriptase inhibitors and either a protease inhibitor or a nonnucleoside reverse transcriptase inhibitor and who had a documented positive result for HCV antibody testing. Outcomes were binary events (time to an increase of > or = 75 CD4 cells/mm3 or an increase of > or = 10% in the percentage of CD4 cells in the total T cell population [CD4 cell fraction]) and continuous repeated measures. Statistical analyses used parametric and nonparametric methods, including multivariate mixed-effects linear regression analysis and Cox proportional hazards analysis. RESULTS: Of 1186 eligible patients, 606 (51%) were positive and 580 (49%) were negative for HCV antibodies. HCV antibody-positive patients were slower to have an absolute (P<.001) and a fraction (P = .02) CD4 cell event. In adjusted Cox proportional hazards analysis (controlling for age, sex, baseline absolute CD4 cell count, baseline pVL, type of ART initiated, AIDS diagnosis at baseline, adherence to ART regimen, and number of CD4 cell measurements), HCV antibody-positive patients were less likely to have an absolute CD4 cell event (adjusted hazard ratio [AHR], 0.84 [95% confidence interval [CI], 0.72-0.98]) and somewhat less likely to have a CD4 cell fraction event (AHR, 0.89 [95% CI, 0.70-1.14]) than HCV antibody-negative patients. In multivariate mixed-effects linear regression analysis, HCV antibody-negative patients had increases of an average of 75 cells in the absolute CD4 cell count and 4.4% in the CD4 cell fraction, compared with 20 cells and 1.1% in HCV antibody-positive patients, during the first 48 weeks of ART, after adjustment for time-updated pVL, number of CD4 cell measurements, and other factors. CONCLUSION: HCV antibody-positive HIV-infected patients may have an altered immunologic response to ART.

Factors associated with the incidence of type 2 diabetes mellitus in HIV-infected participants in the Swiss HIV Cohort Study

BACKGROUND: Human immunodeficiency virus (HIV)-infected persons may be at increased risk for developing type 2 diabetes mellitus because of viral coinfection and adverse effects of treatment. METHODS: We studied associations of new-onset diabetes mellitus with hepatitis B virus and hepatitis C virus coinfections and antiretroviral therapy in participants in the Swiss HIV Cohort Study, using Poisson regression. RESULTS: A total of 123 of 6513 persons experienced diabetes mellitus during 27,798 person-years of follow-up (PYFU), resulting in an incidence of 4.4 cases per 1000 PYFU (95% confidence interval [CI], 3.7-5.3 cases per 1000 PYFU). An increased incidence rate ratio (IRR) was found for male subjects (IRR, 2.5; 95% CI, 1.5-4.2), older age (IRR for subjects >60 years old, 4.3; 95% CI, 2.3-8.2), black (IRR, 2.1; 95% CI, 1.1-4.0) and Asian (IRR, 4.9; 95% CI, 2.2-10.9) ethnicity, Centers for Disease Control and Prevention disease stage C (IRR, 1.6; 95% CI, 1.04-2.4), and obesity (IRR, 4.7; 95% CI, 3.1-7.0), but results for hepatitis C virus infection or active hepatitis B virus infection were inconclusive. Strong associations were found for current treatment with nucleoside reverse-transcriptase inhibitors (IRR, 2.22; 95% CI, 1.11-4.45), nucleoside reverse-transcriptase inhibitors plus protease inhibitors (IRR, 2.48; 95% CI, 1.42-4.31), and nucleoside reverse-transcriptase inhibitors plus protease inhibitors and nonnucleoside reverse-transcriptase inhibitors (IRR, 3.25; 95% CI, 1.59-6.67) but were not found for treatment with nucleoside reverse-transcriptase inhibitors plus nonnucleoside reverse-transcriptase inhibitors (IRR, 1.47; 95% CI, 0.77-2.82). CONCLUSIONS: In addition to traditional risk factors, current treatment with protease inhibitor- and nucleoside reverse-transcriptase inhibitor-containing regimens was associated with the risk of developing type 2 diabetes mellitus. Our study did not find a significant association between viral hepatitis infection and risk of incident diabetes.

Predictors of optimal viral suppression in patients switched to abacavir, lamivudine, and zidovudine: the Swiss HIV Cohort Study

OBJECTIVE: To investigate predictors of continued HIV RNA viral load suppression in individuals switched to abacavir (ABC), lamivudine (3TC) and zidovudine (ZDV) after successful previous treatment with a protease inhibitor or non-nucleoside reverse transcriptase inhibitor-based combination antiretroviral therapy. DESIGN AND METHODS: An observational cohort study, which included individuals in the Swiss HIV Cohort Study switching to ABC/3TC/ZDV following successful suppression of viral load. The primary endpoint was time to treatment failure defined as the first of the following events: two consecutiveviral load measurements > 400 copies/ml under ABC/3TC/ZDV, one viral load measurement > 400 copies/ml and subsequent discontinuation of ABC/3TC/ZDV within 3 months, AIDS or death. RESULTS: We included 495 individuals; 47 experienced treatment failure in 1459 person-years of follow-up [rate = 3.22 events/100 person-years; 95% confidence interval (95% CI), 2.30-4.14]. Of all failures, 62% occurred in the first year after switching to ABC/3TC/ZDV. In a Cox regression analysis, treatment failure was independently associated with earlier exposure to nucleoside reverse transcriptase inhibitor (NRTI) mono or dual therapy [hazard ratio (HR), 8.02; 95% CI, 4.19-15.35) and low CD4 cell count at the time of the switch (HR, 0.66; 95% CI, 0.51-0.87 by +100 cells/microl up to 500 cells/microl). In patients without earlier exposure to mono or dual therapy, AIDS prior to switch to simplified maintenance therapy was an additional risk factor. CONCLUSIONS: The failure rate was low in patients with suppressed viral load and switch to ABC/3TC/ZDV treatment. Patients with earlier exposure to mono or dual NRTI therapy, low CD4 cell count at time of switch, or AIDS are at increased risk of treatment failure, limiting the use of ABC/3TC/ZDV in these patient groups.

Emergence of HIV-1 drug resistance in previously untreated patients initiating combination antiretroviral treatment: a comparison of different regimen types

BACKGROUND: Standard first-line combination antiretroviral treatment (cART) against human immunodeficiency virus 1 (HIV-1) contains either a nonnucleoside reverse transcriptase inhibitor (NNRTI) or a ritonavir-boosted protease inhibitor (PI/r). Differences between these regimen types in the extent of the emergence of drug resistance on virological failure and the implications for further treatment options have rarely been assessed. METHODS: We investigated virological outcomes in patients from the Swiss HIV Cohort Study initiating cART between January 1, 1999, and December 31, 2005, with an unboosted PI, a PI/r, or an NNRTI and compared genotypic drug resistance patterns among these groups at treatment failure. RESULTS: A total of 489 patients started cART with a PI, 518 with a PI/r, and 805 with an NNRTI. A total of 177 virological failures were observed (108 [22%] PI failures, 24 [5%] PI/r failures, and 45 [6%] NNRTI failures). The failure rate was highest in the PI group (10.3 per 100 person-years; 95% confidence interval [CI], 8.5-12.4). No difference was seen between patients taking a PI/r (2.7; 95% CI, 1.8-4.0) and those taking an NNRTI (2.4; 95% CI, 1.8-3.3). Genotypic test results were available for 142 (80%) of the patients with a virological treatment failure. Resistance mutations were found in 84% (95% CI, 75%-92%) of patients taking a PI, 30% (95% CI, 12%-54%) of patients taking a PI/r, and 66% (95% CI, 49%-80%) of patients taking an NNRTI (P < .001). Multidrug resistance occurred almost exclusively as resistance against lamivudine-emtricitabine and the group-specific third drug and was observed in 17% (95% CI, 9%-26%) of patients taking a PI, 10% (95% CI, 0.1%-32%) of patients taking a PI/r, and 50% (95% CI, 33%-67%) of patients taking an NNRTI (P < .001). CONCLUSIONS: Regimens that contained a PI/r or an NNRTI exhibited similar potency as first-line regimens. However, the use of a PI/r led to less resistance in case of virological failure, preserving more drug options for the future.

Lipid profiles for antiretroviral-naive patients starting PI- and NNRTI-based therapy in the Swiss HIV cohort study

BACKGROUND: Blood lipid abnormalities in patients on highly active antiretroviral therapy (HAART) have been associated with exposure to protease inhibitors (PIs), particularly ritonavir. First therapy with a non-nucleoside reverse transcriptase inhibitor (NNRTI) leads to relatively favourable lipid profiles. We report on medium-term lipid profiles (up to 5 years) for antiretroviral-naive patients starting NNRTI- and PI-based HAART in the Swiss HIV Cohort Study. METHODS: Since April 2000, blood samples taken at visits scheduled every 6 months have been analysed for cholesterol and triglyceride concentrations. For 1065 antiretroviral-naive patients starting HAART after April 2000, we estimated changes in concentration over time using multivariate linear regression with adjustment for baseline covariates, use of lipid-lowering drugs and whether the sample was taken in a fasting state. RESULTS: Non-high density lipoprotein (HDL) cholesterol levels increase with increasing exposure to either PI- or NNRTI-based therapy, HDL cholesterol levels increase and triglyceride levels decrease with increasing exposure to NNRTI-based therapy, whereas triglyceride levels increase with increasing exposure to PI-based therapy. Between NNRTI-based therapies, there is a slight difference in triglyceride levels, which tend to increase with increasing exposure to efavirenz and to decrease with increasing exposure to nevirapine. Of the three common PI-based therapies, nelfinavir appears to have a relatively favourable lipid profile, with little change with increasing exposure. Of the other two PI therapies, lopinavir with ritonavir has a more favourable profile than indinavir with ritonavir, with smaller increases in both non-HDL cholesterol and triglycerides and an increase in HDL cholesterol. Increasing exposure to abacavir is associated with a decrease in the level of triglycerides. CONCLUSION: In general, NNRTI-based therapy is associated with a more favourable lipid profile than PI-based therapy, but different PI-based therapies are associated with very different lipid profiles. Nelfinavir appears to have a relatively favourable lipid profile. Of the two boosted PI therapies, lopinavir appears to have a more favourable lipid profile than indinavir.

Body fat changes among antiretroviral-naive patients on PI- and NNRTI-based HAART in the Swiss HIV cohort study

BACKGROUND: Body fat changes are common in patients with HIV. For patients on protease inhibitor (PI)-based highly active antiretroviral therapy (HAART), these changes have been associated with increasing exposure to therapy in general and to stavudine in particular. Our objective is to show whether such associations are more or less likely for patients on non-nucleoside reverse transcriptase inhibitor (NNRTI)-based HAART. METHODS: We included all antiretroviral-naive patients in the Swiss HIV Cohort Study starting HAART after April 2000 who had had body weight, CD4 cell count and plasma HIV RNA measured between 6 months before and 3 months after starting HAART, and at least one assessment of body fat changes after starting HAART. At visits scheduled every 6 months, fat loss or fat gain is reported by agreement between patient and physician. We estimate the association between reported body fat changes and both time on therapy and time on stavudine, using conditional logistical regression. RESULTS: Body fat changes were reported for 85 (9%) out of 925 patients at their first assessment; a further 165 had only one assessment. Of the remaining 675 patients, body fat changes were reported for 156 patients at a rate of 13.2 changes per 100 patient-years. Body fat changes are more likely with increasing age [odds ratio (OR) 1.18 (1.00-1.38) per 10 years], with increasing BMI [OR 1.06 (1.01-1.11)] and in those with a lower baseline CD4 cell count [OR 0.91 (0.83-1.01) per 100 cells/microl]. There is only weak evidence that body fat changes are more likely with increasing time on HAART [OR 1.16 (0.93-1.46)]. After adjusting for time on HAART, fat loss is more likely with increasing stavudine use [OR 1.70 (1.34-2.15)]. There is no evidence of an association between reported fat changes and time on NNRTI therapy relative to PI therapy in those patients who used either one therapy or the other [OR 0.98 (0.56-1.63)]. CONCLUSION: Fat loss is more likely to be reported with increasing exposure to stavudine. We find no evidence of major differences between PI and NNRTI therapy in the risk of reported body fat changes.

CD4+ T cell count recovery in HIV type 1-infected patients is independent of class of antiretroviral therapy

BACKGROUND: In recent years, treatment options for human immunodeficiency virus type 1 (HIV-1) infection have changed from nonboosted protease inhibitors (PIs) to nonnucleoside reverse-transcriptase inhibitors (NNRTIs) and boosted PI-based antiretroviral drug regimens, but the impact on immunological recovery remains uncertain. METHODS: During January 1996 through December 2004 [corrected] all patients in the Swiss HIV Cohort were included if they received the first combination antiretroviral therapy (cART) and had known baseline CD4(+) T cell counts and HIV-1 RNA values (n = 3293). For follow-up, we used the Swiss HIV Cohort Study database update of May 2007 [corrected] The mean (+/-SD) duration of follow-up was 26.8 +/- 20.5 months. The follow-up time was limited to the duration of the first cART. CD4(+) T cell recovery was analyzed in 3 different treatment groups: nonboosted PI, NNRTI, or boosted PI. The end point was the absolute increase of CD4(+) T cell count in the 3 treatment groups after the initiation of cART. RESULTS: Two thousand five hundred ninety individuals (78.7%) initiated a nonboosted-PI regimen, 452 (13.7%) initiated an NNRTI regimen, and 251 (7.6%) initiated a boosted-PI regimen. Absolute CD4(+) T cell count increases at 48 months were as follows: in the nonboosted-PI group, from 210 to 520 cells/muL; in the NNRTI group, from 220 to 475 cells/muL; and in the boosted-PI group, from 168 to 511 cells/muL. In a multivariate analysis, the treatment group did not affect the response of CD4(+) T cells; however, increased age, pretreatment with nucleoside reverse-transcriptase inhibitors, serological tests positive for hepatitis C virus, Centers for Disease Control and Prevention stage C infection, lower baseline CD4(+) T cell count, and lower baseline HIV-1 RNA level were risk factors for smaller increases in CD4(+) T cell count. CONCLUSION: CD4(+) T cell recovery was similar in patients receiving nonboosted PI-, NNRTI-, and boosted PI-based cART.