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JAIDS Journal of Acquired Immune Deficiency Syndromes:
doi: 10.1097/QAI.0b013e31804216cf
Clinical Science

Long-Term Body Composition and Metabolic Changes in Antiretroviral Naive Persons Randomized to Protease Inhibitor-, Nonnucleoside Reverse Transcriptase Inhibitor-, or Protease Inhibitor Plus Nonnucleoside Reverse Transcriptase Inhibitor-Based Strategy

Shlay, Judith C MD, MSPH*; Bartsch, Glenn ScD†; Peng, Grace MS†; Wang, Jack MS‡; Grunfeld, Carl MD, PhD§; Gibert, Cynthia L MD∥; Visnegarwala, Fehmida MD¶; Raghavan, Sai Subhasree PhD#; Xiang, Ying MS†; Farrough, Martha BSN**; Perry, Harold E††; Kotler, Donald MD‡‡; El-Sadr, Wafaa M MD, MPH¶; for the Terry Beirn Community Programs for Clinical Research on AIDS

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Abstract

Objective: To assess changes in metabolic parameters and body composition among 422 antiretroviral-naive patients randomized to 3 antiretroviral therapy (ART) strategies: protease inhibitor (PI; n = 141)-, nonnucleoside reverse transcriptase inhibitor (NNRTI; n = 141)-, or PI + NNRTI (n = 140)-based strategies with a median follow-up of 5 years.

Methods: At baseline and 1-month (metabolic parameters only) and 4-month follow-up intervals, fat-free mass (FFM) and total body fat were calculated, anthropometric measurements were performed, and fasting metabolic parameters were obtained. Rates of change and mean change were compared.

Results: The PI + NNRTI strategy resulted in greater increases in triglycerides and low-density lipoprotein cholesterol compared with the PI and the NNRTI strategies (P < 0.005), with no differences between the PI and NNRTI strategies. High-density lipoprotein cholesterol increased significantly more in the NNRTI strategy than in the PI strategy (P < 0.005). Insulin and insulin resistance increased similarly with all 3 strategies. Changes in total and regional body composition (loss of subcutaneous tissue area and gains in FFM, nonsubcutaneous tissue area, and visceral tissue area) were observed but did not differ by strategy.

Conclusions: Long-term follow-up of participants initiating 3 ART strategies demonstrated similar changes in total and regional fat, with no differences by ART strategy. The differential effects on lipid metabolism by strategy and the overall increases in insulin and insulin resistance with all 3 strategies necessitate close monitoring of patients on ART.

Morphologic changes (lipoatrophy and lipohypertrophy), insulin resistance, and dyslipidemia are important metabolic consequences of antiretroviral therapy (ART) in patients with HIV/AIDS.1-5 The pathogenesis of these metabolic abnormalities has implicated protease inhibitors (PIs)6-8 and certain nucleoside reverse transcriptase inhibitors (NRTIs).9-22 Although short-term studies have implicated individual drugs with specific complications, long-term comparative data on the metabolic effects of initiating different ART strategies in ART-naive patients are limited. Because the risk of complications from metabolic disturbances is linked to their duration, it is important to understand the long-term effects of strategies for combination ART.

The metabolic study was a substudy of a long-term randomized clinical trial (Flexible Initial Retrovirus Suppressive Therapies [FIRST]) conducted by the Community Programs for Clinical Research on AIDS (CPCRA).23 Patients who were naive to antiretroviral drugs and enrolled in the FIRST study (CPCRA 058) were offered coenrollment in the metabolic study (CPCRA 061). The FIRST study compared 3 initial treatment strategies for clinical and immunologic outcomes, with the goal of determining whether it was better to initiate ART with a 3-class strategy than with a 2-class strategy and to determine which of the 2-class strategies, PI or nonnucleoside reverse transcriptase inhibitor (NNRTI), was better for initial therapy. For the trial, triple-class therapy consisting of a PI plus an NNRTI plus 1 or 2 NRTI(s) was compared with a PI-based strategy (PI + NRTI) and an NNRTI-based strategy (NNRTI + NRTI). As part of the FIRST study design, the selection of specific drugs within a class was made by the treating clinician in partnership with the participant and was not specified by the study. Thus, the ART regimen used during the study represented those in common use at the time. The FIRST study demonstrated that the 3-class strategy was not superior to the 2-class strategy and was associated with more treatment-limiting toxicity, although metabolic toxicities were not analyzed. The study also demonstrated superior virologic response with the NNRTI strategy compared with the PI strategy but no differences in immunologic or clinical outcomes.23

Few prospective randomized studies have compared body composition and metabolic changes focusing on various ART class strategies.8 The purpose of this study was to assess changes in metabolic parameters and body composition among ART-naive patients randomized to 3 highly active ART strategies: a PI strategy, an NNRTI strategy, or a PI + NNRTI strategy.

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METHODS

Eligibility criteria included documented HIV infection and being at least 13 years of age. Patients were excluded if they were pregnant or breast-feeding, had any prior use of PIs or NNRTIs, or had a cumulative total of more than 4 weeks of NRTI use or more than 1 week of lamivudine (3TC) use. The metabolic study opened for enrollment in August 1999 and closed for follow-up in September 2005, with 14 CPCRA units participating. One research unit closed after 1 year of follow-up (n = 21 participants) for administrative reasons. A consent form approved by the institutional review board of each site was signed by each participant.

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Patient Assessment and Follow-Up

At enrollment, a baseline history and targeted physical examination were completed, including demographic characteristics, current medications, and prior AIDS-related diagnoses.24 CD4+ lymphocyte count and glucose levels were determined at local laboratories, and plasma HIV RNA level (Roche Amplicor 1.0; Roche Diagnostics, Basel, Switzerland) was determined at a central CPCRA laboratory. Blood, collected after a minimum 8-hour fast at baseline and at 1 month, 4 months, and every 4 months thereafter, was shipped to a central laboratory for measurement of total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, and insulin concentrations. Low-density lipoprotein (LDL) cholesterol values were calculated. If the triglyceride level was greater than 400 mg/dL, LDL cholesterol levels were directly measured.25 Insulin concentration was used to calculate insulin resistance using the homeostasis model.26,27

At each study visit, information was collected regarding metabolic complications, hepatic and gastrointestinal illnesses, cardiovascular diseases, renal complications, and lipodystrophy (ie, self-reported body composition changes).

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Body Composition Measurements

Body composition measurements were performed by staff who received extensive centralized training and were certified at study initiation and annually.28 Initially, bioelectric impedance analysis (BIA), anthropometric measures, and calculation of body mass index (BMI) were done at baseline and then every 4 months during the first year and annually. The protocol was modified in July 2001 to require anthropometric measurements at each follow-up visit instead of only annually to maintain competency in performing the anthropometric measurements. Height and weight were measured according to standard procedures.29 Fat-free mass (FFM) and total body fat (TBF) were estimated by BIA measurements using a BIA-10IQ analyzer (RJL Systems, Clinton Township, MI). The FFM and TBF were calculated as specified by Kotler et al.30

Anthropometric measurements and weight were obtained after an 8-hour fast and included 5 skinfold measurements using a Lange caliper (triceps, subscapular, abdomen, suprascapular, and thigh) and 4 body circumference measurements (midarm, waist, hip, and midthigh) using a Dritz sewing tape,29 all measured twice on the right side and averaged for analyses. Four of the measurements (triceps, subscapular, abdomen, and thigh) were performed as previously described.29 The suprascapular measurement was used to assess changes at the back of the neck.31 Anthropometric measurements were discontinued in April 2004 based on recommendations from the Data Safety Monitoring Board.

The subcutaneous tissue areas for the midarm, midthigh, and waist were estimated using skinfold measurements of the triceps, thigh, and abdomen in addition to using body circumferences of the midarm, midthigh, and waist,30,32,33 with results expressed in square centimeters to reflect the size of subcutaneous fat compartments. The visceral tissue area, representing the visceral content of the abdomen, was calculated by subtracting the subcutaneous tissue area from the total area of the cross section of the abdomen, with results expressed in square centimeters. The nonsubcutaneous areas for the midarm and midthigh were calculated as the total cross section of the limb minus the subcutaneous tissue area and included the muscular and skeletal contents of those areas.

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Statistical Analysis

The primary analyses were by intent-to-treat, because the purpose was to understand the long-term effects of strategy choice. For selected body composition measurements and metabolic parameters, the mean change from baseline to each follow-up visit by ART strategy was calculated. The means of the early change from baseline to the first follow-up visit (1 month for metabolic parameters and 4 months for anthropometric measurements) adjusted for the baseline value for the 3 ART strategies were compared using analysis of variance. For pairwise comparisons involving the 3 strategies, the nominal significance of the Student's t test is given and should be <0.017 to be significant at the 5% level using a Bonferroni adjustment. The analyses were repeated using the average change from baseline over all follow-up visits adjusted for the baseline value. The interaction between the baseline value and strategy group on the mean response at 1 or 4 months and during all follow-up visits was investigated in the analysis of variance model. An on-treatment analysis (not presented) was also performed, yielding similar results as the intent-to-treat analysis.

Using repeat measurement analyses34 with random intercepts and random slopes, linear regression lines were fitted to follow-up data (beginning at 1 month for metabolic parameters and at 4 months for anthropometric measurements) by strategy assignment. Slopes of the lines were used to estimate the rates of change for body composition measurements (at 4 months and thereafter) and metabolic parameters (at 1 month and thereafter).

Cox proportional hazards models were used to compare rates of hyperlipidemia; hazard ratios (HRs) are cited with 95% confidence intervals (CIs). All statistical analyses were performed using SAS (version 8.2; SAS Institute, Cary, NC).

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RESULTS

Baseline Characteristics

Between August 1999 and January 2002, 422 (30%) of 1397 participants in the FIRST study were coenrolled in the metabolic study and randomized to the PI strategy (n = 141), NNRTI strategy (n = 141), or PI + NNRTI strategy (n = 140). The only difference in baseline characteristics between participants enrolled in the metabolic study and the other FIRST participants was that the former had a lower mean triglyceride value (134 vs. 167 mg/dL; P < 0.01), reflecting metabolic study requirements to obtain fasting laboratory specimens, which was not a requirement for the FIRST study.

The participants in the 3 strategy arms of the study were well balanced in terms of baseline characteristics (Table 1). Overall, the mean age of participants was 38 years; 22% were female; and 73% were nonwhite, with 60% black and 10% Latino. At baseline, the mean CD4+ lymphocyte count was 215 cells/mm3, the mean log10 HIV RNA level was 5.0 copies/mL, 36% of participants reported a prior AIDS event, 7% were diagnosed with hepatitis B virus infection by hepatitis B surface antigen testing, and 21% were diagnosed with hepatitis C virus infection by antibody testing. At enrollment, few participants were on treatment for hyperlipidemia (n = 1) or diabetes (n = 11).

Table 1
Table 1
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Findings related to metabolic and anthropometric measurements at baseline by strategy are shown in Table 1. For triglycerides, LDL cholesterol, and total cholesterol, mean levels differed significantly among the strategies, with the highest mean value in the PI + NNRTI strategy. In addition, the nonsubcutaneous tissue areas for the midarm and midthigh and the visceral tissue area of the waist were significantly different, with the highest mean baseline value for the PI + NNRTI strategy. The mean changes from baseline were adjusted for in all analyses.

Table 2 summarizes the treatment regimens used by study participants within each treatment strategy. The most commonly used PI was nelfinavir (61%) for the PI and PI + NNRTI strategies, followed by ritonavir-boosted PIs (24%) and indinavir (12%). For the NNRTI strategy, most participants used efavirenz (63%), whereas in the PI + NNRTI strategy, nevirapine or efavirenz use was equivalent. For the PI and NNRTI strategies, similar NRTI combinations were used, with some differences noted for the PI + NNRTI strategy (see Table 2). Overall, approximately 36% of patients were on stavudine (d4T)-containing regimens in the 3 ART strategies.

Table 2
Table 2
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Follow-Up Results

Median follow-up was 62 months (interquartile range: 56-66 months). There was at least 1 switch from the randomized treatment strategy during follow-up for 51.1%, 37.6%, and 77.9% of the participants in the PI, NNRTI, and PI + NNRTI strategies, respectively. Reasons for first switch in strategy included viral burden, any type of toxicity, and other unspecified reasons. Among those who switched strategies, the median times to first switch in strategy were 17.1, 24.8, and 10.7 months for the 3 strategies, respectively. The percent of follow-up time on the assigned strategy was significantly different among the 3 strategies (60.4%, 66.0%, and 51.3% for the PI, NNRTI, and PI + NNRTI strategies, respectively; P < 0.005). During follow-up, 87% of required anthropometric and metabolic measurements were obtained. The overall lost-to-follow-up rate (defined as missing the last 2 required measurements) was 13.8% for the metabolic measurements and 9.4% for the anthropometric measurements, with no differences by treatment strategy.

The rates of drug treatment for hyperlipidemia were 1.6, 1.7, and 5.4 per 100 person-years for the PI, NNRTI, and PI + NNRTI strategies, respectively (HR = 3.07, 95% CI: 1.53 to 6.17 for the PI + NNRTI vs. NNRTI strategy comparison; HR = 3.29, 95% CI: 1.60 to 6.77 for the PI + NNRTI vs. PI strategy comparison). Overall, 12 participants required initiation of drug therapy for diabetes and 38 required antihypertensive therapy, with no significant differences seen by strategy. No differences were seen in the incidence of hepatic, gastrointestinal, cardiovascular, renal, or lipodystrophy events (data not shown).

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Changes in Lipid Levels

The initial effects on lipids of the ART strategies (defined as change from baseline to 1 month) showed increases in all 3 strategies for mean LDL and HDL cholesterol (Table 3). Triglycerides increased only in the PI + NNRTI strategy. Comparing the initial 1-month changes among the 3 strategies, there was a significantly greater increase in triglycerides and LDL cholesterol in the PI + NNRTI strategy compared with the other strategies, with no differences noted between the PI and NNRTI strategies. Also, a significantly greater increase was noted in HDL cholesterol in the NNRTI strategy compared with the PI strategy, whereas for the PI + NNRTI strategy, the initial effect fell somewhere between those of the other 2 strategies.

Table 3
Table 3
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Overall mean changes over the course of therapy (see Table 3), as a reflection of the average toxicity, were examined, and rates of change during study follow-up for each lipid parameter were calculated and compared with 0 (Fig. 1). For triglycerides, the rates of change were positive and significantly different from 0 for the PI and NNRTI strategies (see Fig. 1A), whereas only the rates for the NNRTI and PI + NNRTI strategies were significantly different from each other (data not shown). The average change for the PI + NNRTI strategy remained relatively stable after the initial increase (rate of change: −0.14 mg/dL/month; P = 0.49). Overall, during the follow-up period, mean triglyceride levels increased in the PI and NNRTI strategies (rate of change for PI: 0.50 mg/dL/month; P = 0.01 and rate of change for NNRTI: 0.68 mg/dL/month; P < 0.005), although declining over time in the PI + NNRTI strategy (rate of change of −0.14 mg/dL/month; P = 0.49). The mean increase from baseline in triglyceride levels was significantly greater in the PI + NNRTI strategy compared with the PI strategy.

Figure 1
Figure 1
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For LDL cholesterol, the rates of change showed a significant decline for all 3 strategies that did not differ by strategy (see Fig. 1B). The mean change in LDL cholesterol for all follow-up visits was lower than at the 1-month follow-up for each of the 3 strategy groups (see Table 3). Mean LDL cholesterol increases in the PI strategy were similar to the NNRTI strategy over the course of the study. However, the increase in the PI + NNRTI strategy was significantly greater than either the PI or NNRTI treatment strategies.

For HDL cholesterol, the average change increased significantly during the first month for the 3 strategies and continued to rise after 1 month of follow-up, leveling off between 4 and 8 months with the plateau sustained through the study (see Fig. 1C). The average increase over all follow-up visits was significantly greater in the NNRTI strategy compared with the PI strategy, whereas the increase in the PI + NNRTI strategy was of borderline significance compared with the increase in the PI strategy.

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Changes in Measures of Glucose Metabolism

After 1 month of follow-up from initiation of the ART treatment strategy, there was a mean increase in insulin (3.01 μIu/mL; P < 0.005) and insulin resistance (0.78; P < 0.005) for the PI strategy, with no significant increases noted for the other strategies (see Table 3). Over the course of the study, for all 3 strategies, there was a significant increase in overall mean insulin levels (PI: 3.86 μIu/mL, P < 0.01; NNRTI: 2.95 μIu/mL, P < 0.01; and PI + NNRTI: 2.69 μIu/mL, P < 0.01). At 1 month and over the entire follow-up period, mean changes did not differ by strategy for insulin or insulin resistance. During the duration of the study, the mean change for insulin levels for all 3 strategies increased during follow-up (the rates of change were positive and significant), with no differences seen by strategy (see Fig. 1D).

At 1 month, there was little increase in mean glucose levels for any strategy. Over the course of the study, there were significant increases in glucose from baseline, with no significant differences in mean changes among the strategies (see Table 3). The rates of change in the PI and PI + NNRTI strategies were positive and significant (P < 0.05), but it was not significant for the NNRTI strategy (data not shown).

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Changes in Body Composition

Table 4 includes mean changes in anthropometric measurements performed at 4 months of follow-up after the initiation of ART and mean change during all the follow-up visits. The initial effects of ART (defined as change from baseline to 4 months) showed mean increases in all 3 ART strategies in the various components of body mass (ie, total body weight, BMI, TBF, FFM), with no significant differences noted among the 3 strategies. The mean changes in weight, BMI, and FFM were sustained or increased over the entire follow-up period (see Table 4), with no significant differences seen by strategy.

Table 4
Table 4
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In terms of regional body composition, similar increases were observed from baseline to 4 months for the nonsubcutaneous tissue areas for the midarm and midthigh, with the exception of the midthigh in the PI + NNRTI strategy (see Table 4). The mean changes in the nonsubcutaneous tissue areas for the midarm and midthigh were sustained or increased over the follow-up period, with no differences seen by strategy (see Table 4; Figs. 2B, D).

Figure 2
Figure 2
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For the 3 subcutaneous tissue areas (midarm, midthigh, and waist), which represent predominantly adipose tissue, all areas increased by the 4-month follow-up, with no significant differences seen by strategy (see Table 4). For the waist subcutaneous tissue area, changes from baseline were sustained for 20 months and then declined to baseline levels, such that the overall mean change for the waist subcutaneous tissue area was lower than the 4-month levels, with the mean for the NNRTI strategy no longer being significantly different from baseline (see Fig. 2E). For the midthigh subcutaneous tissue area, changes from baseline were sustained for the first 12 months and then declined to baseline, whereas for the midarm subcutaneous tissue area, changes were sustained only for the first 8 months and then declined to less than baseline (see Figs. 2A, C). For the midthigh subcutaneous tissue area, the mean change for the PI + NNRTI strategy was not significantly different from baseline. For the midarm subcutaneous tissue area, no differences in the overall mean change were noted compared with baseline. For the visceral tissue area of the waist, which is a surrogate for visceral adipose tissue, early significant increases were noted for the PI and NNRTI strategies but not for the PI + NNRTI strategy, with no differences seen by strategy. Over the course of the study, the mean change in visceral tissue area from baseline was significant and sustained for all strategies, with no differences among the strategies (see Fig. 2F).

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Subgroup Analyses

To address the imbalances at randomization, we performed subgroup analyses among the strategies for all baseline variables. Initially, we assessed whether there were any interactions between the baseline variables and strategy. No interactions were seen with any of the baseline variables, with the exception of triglycerides, for which there was a significant interaction between baseline triglyceride levels and strategy assignment (P < 0.005 for the first month of follow-up and P = 0.003 for all follow-up visits).

To investigate this interaction further, we assessed the differences between pairs of strategies by the tertile of the baseline triglyceride level. In Table 5, the mean triglyceride values during follow-up by tertile of baseline triglyceride level and treatment strategy at 1 month of follow-up and during all follow-up visits and the pairwise comparisons of the strategies are presented. At 1 month of follow-up, we found that the PI + NNRTI strategy had more of an effect with regard to the mean response in triglyceride level overall compared with the PI or NNRTI strategy (see Table 5). These findings were more marked in those whose baseline triglycerides were in the higher tertile, but similar and smaller responses were seen in the other tertiles. In contrast, the PI strategy compared with the NNRTI strategy demonstrated no significant differences.

Table 5
Table 5
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Over the course of the study, the findings were less pronounced (see Table 5). The PI + NNRTI strategy continued to have significantly higher mean responses compared with the PI strategy, being different overall, whereas neither the PI + NNRTI strategy compared with the NNRTI strategy nor the NNRTI strategy compared with the PI strategy was significantly different. Focusing on the differences between the PI + NNRTI strategy compared with the PI strategy, the difference was only seen with the higher tertile.

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DISCUSSION

This long-term randomized clinical trial was uniquely able to assess the effects of 3 ART strategies:-PI-based, NNRTI-based, and PI + NNRTI-based strategies-on metabolic parameters and body composition. Early measurements taken before significant switches in regimens occurred allowed us to assess the direct effects of the initial strategy, whereas measurements over the course of the study allowed us to assess the effects of the long-term consequences of the strategy. Study findings indicate that the PI + NNRTI strategy was associated with greater increases in triglycerides and LDL cholesterol compared with the PI and NNRTI strategies, although no significant differences were noted in these parameters between the PI and NNRTI strategies. For triglycerides, these differences by strategy were more prominent among those participants who initiated the study at higher triglyceride levels. For participants assigned to the NNRTI strategy, there was a significantly greater increase in average HDL cholesterol compared with the PI strategy. For LDL cholesterol, the magnitude of the increases occurred primarily within the first month after initiation of ART, with subsequent declines such that by 40 months, the average LDL cholesterol level approximated the baseline values, suggesting that the changes were attributable to a direct effect of ART.8 Additional findings showed an increase in insulin, insulin resistance, and glucose levels after initiation of ART, which did not differ by strategy and continued to increase throughout the duration of follow-up as opposed to the early increases noted in LDL cholesterol levels. Furthermore, the changes noted in total and regional body composition did not differ significantly by strategy.

Previous studies have reported the development of hyperlipidemia in conjunction with ART use, particularly PI use,1,35-39 with fewer atherogenic lipid changes noted with NNRTI-based regimens compared with PI-based regimens, particularly when compared with a boosted PI-based regimen.40-43 Our study corroborates the previously reported finding of a favorable effect on HDL cholesterol levels with use of NNRTI-containing regimens compared with PI-containing regimens.40,41 Our study demonstrated deleterious effects on triglycerides associated with the initiation and long-term use of a PI + NNRTI-containing strategy, however, in contrast to prior studies that primarily implicated PI-containing regimens.1,35-39,44 These differences were more pronounced among those participants who initiated the study at higher triglyceride levels. These results were further supported by the need for initiation of antihyperlipidemic drugs in a larger proportion of participants assigned to the PI + NNRTI strategy. The rapidity with which triglycerides and LDL cholesterol changes occurred in this ART-naive group highlights the importance of close monitoring of these lipid values after initiation of ART therapy, particularly for those individuals using a PI + NNRTI-based strategy who initially have elevated triglyceride levels. The long-term implications of these various lipid changes require longitudinal assessments for ongoing coronary artery disease risk.

Marked differences have been noted on the effects of different PIs on lipid metabolism in short-term studies of HIV-infected and noninfected subjects. We found little effect of PIs on triglycerides. These results should be viewed as consistent with data previously reported by Periard et al39 and others, such that for increasing triglycerides, there is a hierarchy, with the greatest effects seen with full-dose ritonavir,6,39 followed by boosted regimens39,45-48 and then other PIs.7,39,46,48 In HIV-infected subjects, all PIs, except atazanavir and some NNRTIs, have been shown to raise LDL cholesterol,39,49,50 although none raise LDL cholesterol in healthy volunteers.6,7,45,46 It should be noted, however, that in this study, the commonly prescribed PIs were nelfinavir, indinavir, and ritonavir-boosted PIs. Given that this is the first large study comparing the effects of regimens with a PI, NNRTI, or PI + NNRTI strategy, it is of particular concern that increases in levels of triglycerides and LDL cholesterol, which are usually attributed to PI therapy, were higher in the PI + NNRTI-based strategy than in the other strategies; thus, such regimens that combine a PI with an NNRTI should be avoided if other effective ART options are available.

Increases in insulin, insulin resistance, and glucose were noted during follow-up after initiation of ART with all 3 strategies, with no differences noted by strategy. Compared with the more immediate changes and subsequent declines observed in LDL cholesterol after the initiation of ART, however, increases in insulin, insulin resistance, and glucose were more gradual and continued to increase over the duration of follow-up. Although the causes of insulin resistance are multifactorial, some PI regimens37,51,52 and NRTI use53 as well as the presence of lipodystrophy (ie, lipoatrophy, lipohypertrophy)54-56 have previously been demonstrated to be associated with the development of insulin resistance. There are no previous reports of the development of insulin resistance with the use of an NNRTI- or a PI + NNRTI-containing regimen, however. Thus, these gradual increases in insulin, insulin resistance, and glucose with all 3 strategies support the need for ongoing monitoring of glucose levels as well as monitoring for the development of diabetes, irrespective of the ART regimen used. The cause of these changes may be associated with the accompanying body composition changes as described here.

Studies have associated NRTIs, particularly d4T, with the development of lipoatrophy.12,14,18,19,22,57,58 The long-term effects of PIs and NNRTIs on body composition have not been as carefully elucidated, however.58-60 In this study, regardless of strategy, all body composition measurements changed significantly during follow-up, with increases noted in most components of body mass. Assessment of regional body composition revealed an increase in nonsubcutaneous tissue areas (midarm and midthigh) and visceral tissue area (waist), with a loss in subcutaneous tissue areas in all regional areas regardless of strategy. Accumulation of trunk fat, particularly visceral fat and loss of lower extremity peripheral fat, has been noted in non-HIV-infected populations and has been associated with the development of insulin resistance and adult-onset diabetes.61-63 Thus, the changes in body composition noted in our study may have contributed to the gradual development of insulin resistance. The central adiposity and loss of subcutaneous fat and evidence of insulin resistance that occurred irrespective of strategy suggest that the NRTIs may be responsible for the development of lipoatrophy and insulin resistance, as described in other studies.17-19,53,58

The study is strengthened by its randomized study design and is uniquely characterized by the long duration of follow-up of participants, a median of 5 years. This allowed assessment of the short-term and long-term effects after the initiation of 3 different ART strategies. Additionally, although a focused group of metabolic parameters was evaluated, these measurements provide clinically relevant information that is useful for the long-term management of HIV-infected patients. Furthermore, anthropometry performed by well-trained individuals using standardized measurement protocols and tools31 is a reliable tool for measuring body composition in HIV-infected participants.64,65

Limitations include the fact that at the time of the study's design and implementation, nelfinavir and indinavir were the primary PIs available; thus, the study does not provide information on the effects of newer PIs, which may have different long-term effects on body composition and metabolic parameters. Our study assessed the effects of antiretroviral drug classes rather than specific drugs. As anticipated, switches from the randomized treatment strategy occurred, which may have affected study findings. Nonetheless, the purpose of the study was to evaluate the effects associated with initiation of various ART strategies, recognizing that changes in treatment are likely to occur, particularly with a longer duration of follow-up.

In summary, this long-term study demonstrates that the 3 ART strategies assessed were associated with substantial changes in metabolic parameters and body composition. The data indicate that use of the PI + NNRTI strategy is associated with the least favorable metabolic effects. Because some effects were ubiquitous across ART strategies, this supports the possible fundamental effects of NRTIs on changes in body composition and lipid and glucose metabolism. The close follow-up of study participants also offers guidance to clinicians on optimal timing for monitoring of changes in lipid and glucose levels. In conclusion, the choice of ART regimen should not only take into account its potency and tolerability but its toxicities, including potential effects on various metabolic parameters. Long-term follow-up is critical to defining these effects and to determining the eventual clinical consequences of these metabolic changes.

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ACKNOWLEDGMENTS

The authors acknowledge all the patients who participated in the study and all the research nurses who carefully performed all the anthropometric measurements. They acknowledge the referees for this manuscript, who recommended additional analyses to investigate the impact of baseline differences by strategy on study outcomes.

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REFERENCES

1. Carr A, Samaras K, Burton S, et al. A syndrome of peripheral lipodystrophy and insulin resistance due to HIV protease inhibitors. AIDS. 1998;12(Suppl):F51-F58.

2. Miller KD, Jones E, Jack A, et al. Visceral abdominal-fat accumulation associated with the use of indinavir. Lancet. 1998;351:871-875.

3. Lo JC, Mulligan K, Tai VW, et al. ‘Buffalo hump’ in men with HIV infection. Lancet. 1998;351:867-870.

4. Dube MP. Disorders of glucose metabolism in patients infected with human immunodeficiency virus. Clin Infect Dis. 2000;31:1467-1475.

5. Martinez E, Mocroft A, Garcia-Viejo MA, et al. Risk of lipodystrophy in HIV-1 patients treated with protease inhibitors: a prospective cohort study. Lancet. 2001;357:592-598.

6. Purnell J, Zambon A, Knopp R, et al. Effect of ritonavir on lipids and post-heparin lipase activities in normal subjects. AIDS. 2000;14:51-57.

7. Noor M, Lo J, Mulligan K, et al. Metabolic effects of indinavir in healthy HIV-seronegative men. AIDS. 2001;15:11-15.

8. Dube M, Parker R, Tebas P, et al. Glucose metabolism, lipid, and body fat changes in antiretroviral-naive subjects randomized to nelfinavir or efavirenz plus dual nucleosides. AIDS. 2005;19:1807-1818.

9. Kakuda TN, Brundage R, Anderson P, et al. Nucleoside reverse transcriptase inhibitor-associated mitochondrial toxicity as an etiology for lipodystrophy. AIDS. 1999;13:2311-2312.

10. Brinkman K, Smeitink J, Fomijn J, et al. Mitochondrial toxicity induced by nucleoside-analogue reverse-transcriptase inhibitors is a key factor in the pathogenesis of antiretroviral therapy-related lipodystrophy. Lancet. 1999;354:1112-1115.

11. Nolan D, Mallal S. Thymidine analogue-sparing highly active antiretroviral therapy (HAART). J HIV Ther. 2003;8:2-6.

12. Carr A, Workman C, Smith D, et al. Abacavir substitution for nucleoside analogs in patients with HIV lipoatrophy: a randomized trial. JAMA. 2002;288:207-215.

13. Lichtenstein KA, Ward DJ, Moorman AC, et al. Clinical assessment of HIV-associated lipodystrophy in an ambulatory population. AIDS. 2001;15:1389-1398.

14. Bogner JR, Vielhauer V, Beckmann R, et al. Stavudine versus zidovudine and the development of lipodystrophy. J Acquir Immune Defic Syndr. 2001;27:237-244.

15. Saint-Marc T, Partisani M, Poizot-Martin I, et al. Fat distribution evaluation by computed tomography and metabolic abnormalities in patients undergoing antiretroviral therapy: preliminary results of the LIPCO study. AIDS. 2000;14:37-49.

16. Bernasconi E, Boubaker K, Junghans C, et al. Abnormalities of body fat distribution in HIV-infected persons treated with antiretroviral drugs: the Swiss HIV Cohort Study. J Acquir Immune Defic Syndr. 2002;31:50-55.

17. Mallon PWG, Miller J, Cooper D, et al. Prospective evaluation of the effects of antiretroviral therapy on body composition in HIV-1-infected men starting therapy. AIDS. 2003;17:971-979.

18. Mallal SA, John M, Moore C, et al. Contribution of nucleoside analogue reverse transcriptase inhibitors to subcutaneous fat wasting in patients with HIV infection. AIDS. 2000;14:1309-1316.

19. Joly V, Flandre P, Meiffredy V, et al. Increased risk of lipoatrophy under stavudine in HIV-1-infected patients: results of a substudy from a comparative trial. AIDS. 2002;16:2447-2454.

20. Lichtenstein KA, Delaney K, Armon C, et al. Incidence of and risk factors for lipoatrophy (abnormal fat loss) in ambulatory HIV-1-infected patients. J Acquir Immune Defic Syndr. 2003;32:48-56.

21. Galli M, Ridolfo A, Fulvio A, et al. Body habitus changes and metabolic alterations in protease inhibitor-naive HIV-1-infected patients treated with 2 nucleoside reverse transcriptase inhibitors. J Acquir Immune Defic Syndr. 2002;29:21-31.

22. Shlay J, Visnegarwala F, Bartsch G, et al. Body composition and metabolic changes in antiretroviral-naive patients randomized to didanosine and stavudine versus abacavir and lamivudine. J Acquir Immune Defic Syndr. 2005;38:147-155.

23. MacArthur R, Novak R, Peng G, et al. A comparison of three highly active antiretroviral treatment strategies consisting of non-nucleoside reverse transcriptase inhibitors, protease inhibitors, or both in the presence of nucleoside reverse transcriptase inhibitors as initial therapy (CPCRA 058 FIRST study): a long-term randomised trial. Lancet. 2006;368:2125-2135.

24. Centers for Disease Control and Prevention. 1993 Revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR Morb Mortal Wkly Rep. 1993;41:1-19.

25. Friedewald WT, Levy R, Fredrickson D. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499-502.

26. Yeni-Komshian H, Carantoni M, Abbasi F, et al. Relationship between several surrogate estimates of insulin resistance and quantification of insulin-mediated glucose disposal in 490 healthy nondiabetic volunteers. Diabetes Care. 2000;23:171-175.

27. Mathews DR, Hosker J, Rudenski A, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412-419.

28. Wang J, Bartsch G, Raghavan S, et al. Reliability of body composition and skinfold measurements by observers trained in groups. International Journal of Body Composition Research. 2004;2:31-36.

29. Lohman TG, Roche A, Martorell R. Anthropometric Standard Reference Manual. Champaign, IL: Human Kinetics; 1988.

30. Kotler DP, Burastero S, Wang J, et al. Prediction of body cell mass, fat-free mass and total body water with bioelectrical bioimpedance analysis: effects of race, gender and disease. Am J Clin Nutr. 1996;64(3 Suppl):489-497.

31. Wang J, Thorton J, Kolesnik S, et al. Anthropometry in body composition: an overview. Ann NY Acad Sci. 2000;904:317-326.

32. Kotler DP, Rosenbaum K, Wang J, et al. Studies of body composition and fat distribution in HIV-infected and control subjects. J Acquir Immune Defic Syndr. 1999;20:228-237.

33. Wang J, Thorton J, Russell M, et al. Asians have lower body mass index (BMI) but higher percent body fat than do whites: comparisons of anthropometric measurements. Am J Clin Nutr. 1994;60:23-28.

34. Laird NM, Ware J. Random-effects models for longitudinal data. Biometrics. 1982;38:963-974.

35. Carr A, Samaras K, Thorisdottir A, et al. Diagnosis, prediction, and natural course of HIV-1 protease-inhibitor-associated lipodystrophy, hyperlipidaemia, and diabetes mellitus: a cohort study. Lancet. 1999;353:2093-2099.

36. Dong K, Bausserman L, Flynn M, et al. Changes in body habitus and serum lipid abnormalities in HIV-positive women on highly active antiretroviral therapy (HAART). J Acquir Immune Defic Syndr. 1999;21:107-113.

37. Mulligan K, Grunfeld C, Tai V, et al. Hyperlipidemia and insulin resistance are induced by protease inhibitors independent of changes in body composition in patients with HIV infection. J Acquir Immune Defic Syndr. 2000;23:35-43.

38. Riddler SA, Smit E, Cole S, et al. Impact of HIV infection and HAART on serum lipids in men. JAMA. 2003;289:2978-2982.

39. Periard D, Telenti A, Sudre P, et al. Atherogenic dyslipidemia in HIV-infected individuals treated with protease inhibitors. Circulation. 1999;100:700-705.

40. van Leth F, Phanuphak P, Stroes E, et al. Nevirapine and efavirenz elicit different changes in lipid profiles in antiretroviral-therapy-naive patients infected with HIV-1. PLoS Med. 2004;1:e19.

41. Clotet B, van der Valk M, Negredo E, et al. Impact of nevirapine on lipid metabolism. J Acquir Immune Defic Syndr. 2003;34(Suppl):S79-S84.

42. Young J, Weber R, Rickenbach M, et al. Lipid profiles for antiretroviral-naive patients starting PI- and NNRTI-based therapy in the Swiss HIV Cohort Study. Antivir Ther. 2005;10:585-591.

43. Fontas E, van Leth F, Sabin C, et al. Lipid profiles in HIV-infected patients receiving combination antiretroviral therapy: are different antiretroviral drugs associated with different lipid profiles? J Infect Dis. 2004;189:1056-1074.

44. Grover S, Coupal L, Gilmore N, et al. Impact of dyslipidemia associated with highly active antiretroviral therapy (HAART) on cardiovascular risk and life expectancy. Am J Cardiol. 2005;95:586-591.

45. Lee G, Seneviratne T, Noor M, et al. The metabolic effects of lopinavir/ritonavir in HIV-negative men. AIDS. 2004;18:641-649.

46. Noor M, Parker R, O'Mara E, et al. The effects of HIV protease inhibitors atazanavir and lopinavir/ritonavir on insulin sensitivity in HIV-seronegative healthy adults. AIDS. 2004;18:2137-2144.

47. Gathe J, Ive P, Wood R, et al. SOLO: 48-week efficacy and safety comparison of once-daily fosamprenavir/ritonavir versus twice-daily nelfinavir in naive HIV-1-infected patients. AIDS. 2004;18:1529-1537.

48. Cohen C, Nieto-Cisneros L, Zala C, et al. Comparison of atazanavir with lopinavir/ritonavir in patients with prior protease inhibitor failure: a randomized multinational trial. Curr Med Res Opin. 2005;21:1683-1692.

49. van der Valk M, Gisolf E, Wit F, et al. Increased risk of lipodystrophy when nucleoside analogue reverse transcriptase inhibitors are included with protease inhibitors in the treatment of HIV-1 infection. AIDS. 2001;15:847-855.

50. Murphy R, Sanne I, Cahn P, et al. Dose-ranging, randomized, clinical trial of atazanavir with lamivudine and stavudine in antiretroviral-naive subjects: 48-week results. AIDS. 2003;17:2603-2614.

51. Walli R, Herfort O, Michl G, et al. Treatment with protease inhibitors associated with peripheral insulin resistance and impaired oral glucose tolerance in HIV-1-infected patients. AIDS. 1998;12(Suppl):F167-F173.

52. Walli RK, Michl G, Bogner J, et al. Improvement of HAART-associated insulin resistance and dyslipidemia after replacement of protease inhibitors with abacavir. Eur J Med Res. 2001;6:413-421.

53. Brown T, Xiuhong L, Cole S, et al. Cumulative exposure to nucleoside analogue reverse transcriptase inhibitors is associated with insulin resistance markers in the Multicenter AIDS Cohort Study. AIDS. 2005;19:1375-1383.

54. Palacios R, Merchante N, Macias J, et al. Prospective study of glucose metabolism in antiretroviral naive HIV-infected patients: incidence of insulin resistance at 48 weeks of HAART. Presented at: Programs and Abstracts of the 45th Interscience Conference of Antimicrobial Agents and Chemotherapy; 2005; Washington, DC.

55. Hadigan C, Meigs J, Corcoran C, et al. Metabolic abnormalities and cardiovascular disease risk factors in adults with human immunodeficiency virus infection and lipodystrophy. Clin Infect Dis. 2001;32:130-139.

56. Mallon P, Wand H, Law M, et al. Buffalo hump seen in HIV-associated lipodystrophy is associated with hyperinsulinemia but not dyslipidemia. J Acquir Immune Defic Syndr. 2005;38:156-162.

57. Martin A, Carr A, Ringland D, et al. Long-term changes in lipodystrophy after switching from thymidine nucleoside analogues to abacavir. Antivir Ther. 2003;8:L15.

58. Bacchettti P, Gripshoever B, Grunfeld C, et al. Fat distribution in men with HIV infection. J Acquir Immune Defic Syndr. 2005;40:121-131.

59. Lichtenstein KA. Redefining lipodystrophy syndrome: risks and impact on clinical decision making. J Acquir Immune Defic Syndr. 2005;39:395-400.

60. Dube MP. HIV-associated lipoatrophy: what are the kinder gentler agents? Clin Infect Dis. 2006;42:281-282.

61. Snijder M, Visser M, Dekker J, et al. Low subcutaneous thigh fat is a risk factor for unfavorable glucose and lipid levels, independently of high abdominal fat. The Health ABC Study. Diabetologia. 2005;48:301-308.

62. Snijder M, Dekker J, Visser M, et al. Associations of hip and thigh circumferences independent of waist circumference with the incidence of type 2 diabetes: the Hoorn Study. Am J Clin Nutr. 2003;77:1192-1197.

63. Snijder M, Dekker J, Visser M, et al. Trunk fat and leg fat have independent and opposite associations with fasting and postload levels. Diabetes Care. 2004;27:372-377.

64. Wang J, Kotler D, Russell M, et al. Body-fat measurement in patients with acquired immunodeficiency syndrome: which method should be used? Am J Clin Nutr. 1992;56:963-967.

65. Knox T, Zafonte-Sanders M, Fields-Gardner C, et al. Assessment of nutritional status, body composition, and human immunodeficiency virus-associated morphologic changes. Clin Infect Dis. 2003;36(Suppl 2):S63-S68.

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APPENDIX
Credit Roster

Wayne State University, Detroit MI: Lawrence R. Crane, MD, Rodger D. MacArthur, MD, and Marti Farrough, BSN, RN

Harlem AIDS Treatment Group, New York, NY: Sharon Mannheimer, MD, Susan Caras, RN, MA, and Rosetta Contrerras, RN

Denver Community Program for Clinical Research on AIDS, Denver, CO: David L. Cohn, MD, Frances Moran, RN, and Diane States, RN

Henry Ford Hospital, Detroit, MI: Bonita K. Braxton, RN, BSN, Beverly Campbell, RN, BSN, and Leslie L. Faber, RN, BSN

Research and Education Group, Portland, OR: James Sampson, MD, Doug Beers, MD, and Toni Kempner, RN, BSN, CCRC

Louisiana Community AIDS Research Program, New Orleans, LA: Janice Y. Walker, RN, MN,CCRC, APRN-BC, Sr. Sue Ann Pablovich, RN, MPH, APRN-BC, and Connie Z. Scott, RN, BSN

Richmond AIDS Consortium, Richmond, VA: Evelyn Fisher, MD, Carol Clark, RN, and Martha Pittman, RN

Southern New Jersey AIDS Clinical Trials, Camden, NJ: Deborah Goraj, RN, Pamela Gorman, RN, and Dawn McIntyre, RN

AIDS Research Consortium of Atlanta, Atlanta, GA: Bentley Sweeton, RPh, Lynwood Miller, RN, and Kathy Williams, MLT

AIDS Research Alliance: Chicago, Chicago, IL: Jonathan P. Uy, MD, Roberta Luskin-Hawk, MD, and Marc Giles

Wide-Reaching AIDS Program, Washington, DC: Barbara Standridge, RN, BSN, Margaret A. Lankford, CNP, ACRN, and Shirley Cummins, AA

Community Consortium of San Francisco, San Francisco CA: Pierre Crouch, RN, Michael Jones, RN

Partners in Research New Mexico, Albuquerque, NM: S. Bruce Williams, MD, Cynthia S. Nicholson, MS, CCRC, and Katherine Hammer, RN

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Keywords:

antiretroviral drugs; body composition; dyslipidemia; HIV; insulin resistance; randomized controlled trial

© 2007 Lippincott Williams & Wilkins, Inc.

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