JAIDS Journal of Acquired Immune Deficiency Syndromes:
Body Composition and Metabolic Changes in Antiretroviral-Naive Patients Randomized to Didanosine and Stavudine vs. Abacavir and Lamivudine
Shlay, Judith C MD, MSPH*; Visnegarwala, Fehmida MD†; Bartsch, Glenn PhD‡; Wang, Jack MS§; Peng, Grace MS‡; El-Sadr, Wafaa M MD, MPH∥; Gibert, Cynthia MD¶; Kotler, Donald MD§; Grunfeld, Carl MD, PhD#; Raghavan, Subhasree PhD∥; for the Terry Beirn Community Programs for Clinical Research on AIDS (CPCRA)
From the *Denver Community Programs for Clinical Research on AIDS, Denver Public Health, University of Colorado Health Sciences Center, Denver, CO; †Houston AIDS Research Team, Baylor College of Medicine, Houston, TX; ‡CPCRA Statistical and Data Management Center, University of Minnesota, Minneapolis, MN; §Body Composition Unit of St. Lukes-Roosevelt Hospital, Columbia University College of Physicians and Surgeons, New York, NY; ∥Harlem AIDS Treatment Group, Harlem Hospital, Columbia University College of Physicians and Surgeons, New York, NY; ¶Wide-Reaching AIDS Partnership, Veterans Affairs Medical Center, Washington, DC; and #Veterans Affairs Medical Center and University of California, San Francisco, CA.
Received for publication April 22, 2004; accepted August 16, 2004.
The National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health, 5U01AI042170-10 and 5U01AI046362-03, provided financial support for this study as part of the Flexible Initial Retrovirus Suppressive Therapies (FIRST) study (CPCRA 058) and the Metabolic Substudy of FIRST (CPCRA 061).
This paper was presented in part at the 15th International AIDS Conference in Bangkok, Thailand as an oral presentation, July 11-16, 2004.
Reprints: Fehmida Visnegarwala, Baylor College of Medicine, Department of Medicine, Section of Infectious Diseases, Room #424, 2015 Thomas Street, Houston, TX 77009 (e-mail: email@example.com).
Comparisons of body composition and metabolic changes among antiretroviral-naive patients randomly assigned to didanosine and stavudine- (ddI + d4T) vs. abacavir and lamivudine- (ABC + 3TC) containing regimens were assessed in a nested substudy of an ongoing multicenter randomized trial. At baseline and every 4 months, body cell mass and total body fat were calculated, anthropometric measurements were performed, and fasting metabolic parameters were obtained. The rates of change (unit/mo) estimated using the slopes of regression lines and overall mean changes from baseline were compared by study assignment. Among 96 patients enrolled, 46 received ddI + d4T- and 50 received ABC + 3TC-containing regimens with a median follow-up of 32.4 months. For both study arms, an overall increase in the rates of change was seen for body cell mass. For ddI + d4T, after an initial increase, the rates of change declined for regional fat and total body fat compared with an increase for ABC + 3TC, with the 2 arms being significantly different (P < 0.05). For high-density lipoprotein cholesterol rates of change, ddI + d4T decreased, while ABC + 3TC increased. For both arms, low-density lipoprotein cholesterol decreased, while triglycerides increased. Early and sustained increases in insulin and insulin resistance were seen only for ddI + d4T. In this prospective study, metabolic and body composition changes varied according to whether subjects received ddI + d4T or ABC + 3TC.
Morphologic changes (lipoatrophy and lipohypertrophy), insulin resistance (IR), and dyslipidemia are emerging as important metabolic consequences of antiretroviral therapy in patients with HIV/AIDS.1-5 Currently, the etiology of these metabolic abnormalities is unclear, with prior studies suggesting a direct role for protease inhibitors (PIs).6-8 Subsequently, the use of nucleoside reverse transcriptase inhibitors (NRTIs) has been implicated in the development of the lipoatrophy component of the HIV lipodystrophy syndrome9-12 with associations identified with both cumulative duration of NRTI exposure and the current use of thymidine analogues, particularly stavudine (d4T).13-21 However, previously published studies have not clearly determined the relative contribution of various HIV therapies and duration of these therapies with the development of lipoatrophy.13,22
Few prospective randomized studies have compared body composition and metabolic changes in thymidine analogue-containing regimens to thymidine analogue-sparing regimens.23-26 These comparisons are clinically important in antiretroviral-naive patients, as recent results have demonstrated a modest improvement in fat mass among patients changing from a thymidine analogue-containing regimen to a thymidine analogue-sparing regimen.12,27-29 We compared changes in metabolic parameters and body composition among antiretroviral-naive patients in a study conducted by the Community Program for Clinical Research on AIDS (CPCRA). Patients were randomly assigned to receive either didanosine and stavudine (ddI + d4T)- vs. abacavir and lamivudine (ABC + 3TC)-containing regimens to determine differences in a thymidine analogue-containing regimen vs. a thymidine analogue-sparing regimen, respectively.
Study Design and Patient Population
Figure 1 illustrates the Flexible Initial Retrovirus Suppressive Therapies (FIRST, CPCRA 058) study, which is a multicenter randomized clinical trial designed to compare the initiation of antiretroviral treatment with a PI-containing regimen, a nonnucleoside reverse transcriptase inhibitor (NNRTI)-containing regimen, or a PI plus NNRTI-containing regimen, each in combination with 2 nucleoside analogues in antiretroviral-naive, nonpregnant HIV-infected individuals. Eligibility criteria included HIV-infected persons at least 13 years of age, who gave written informed consent, and for women agreement to use a barrier method of birth control throughout the course of the study. The FIRST study enrolled 1397 patients with an equal distribution in each of the 3 treatment strategies, and follow-up is ongoing.
In FIRST, there are 3 nested substudies, of which the NRTI substudy, the focus of this report, consisted of randomization to 1 of 2 specific NRTI combinations (ddI + d4T vs. ABC + 3TC). The NRTI substudy opened in November 1999 and closed in January 2002 with 182 patients enrolling in 1 of the 2 treatment arms (ddI + d4T: n = 89; ABC + 3TC: n = 93). Patients from the FIRST study were offered coenrollment in a metabolic substudy (CPCRA 061) in which additional metabolic and body composition assessments were conducted. Only patients enrolled in the NRTI substudy of FIRST who coenrolled in the metabolic substudy were included in this analysis. The institutional review board at each of the local sites approved the study protocol.
At enrollment, a baseline history and a targeted physical examination were conducted. Prior to enrollment, demographic characteristics, listing of current medications, and HIV-related diagnoses were collected. The definition of an AIDS-defining illness was based on a modified version of the Centers for Disease Control and Prevention's classification system.30 In addition, the CD4+ lymphocyte count was determined by the local laboratories at CPCRA units with the plasma HIV RNA (reverse transcription polymerase chain reaction; HIV Monitor, Roche Diagnostics) measured at a central CPCRA laboratory.
Body Composition Measurements
All body composition measurements were performed by research nurses who were centrally trained and certified at the beginning of the study and annually thereafter.31 Initially, the study required at baseline, then every 4 months during the 1st year of the study and annually thereafter, obtaining a bioelectric impedance analysis (BIA), performing anthropometric measures, and calculation of body mass index (BMI). However, after the study was initiated, the protocol was modified to require collection of skinfold and body circumference measurements at each follow-up visit (ie, every 4 months). Height and weight were measured following a standard procedure.32 Body cell mass (BCM) and total body fat (TBF) were estimated by BIA measurements, which were obtained using a BIA-10IQ analyzer (RJL Systems, Inc., Clinton Twp., MI). BCM and TBF were calculated using the formula provided by the manufacturer as specified by Kotler et al.33
Anthropometric measurements and weight were obtained after an 8-hour fast. The anthropometric measurements included 5 skinfold measurements (ie, triceps, subscapular, abdomen, suprascapular, thigh) and 4 body circumference measurements (ie, mid-arm, waist, hip, mid-thigh). Two measurements for each body circumference and skinfold site were performed, with the average of the 2 measurements used for analysis. All skinfold thicknesses were measured using a Lange caliper. Four of the measurements (ie, triceps, subscapular, abdomen, thigh) were performed as described by Lohman et al.32 The suprascapular measurement was used to assess changes at the back of neck.34 Body circumferences were obtained using a Dritz sewing tape.32
The 5 skinfolds were used as a surrogate for subcutaneous fat compartment at different regions of the body. The triceps and subscapular skinfold measurements were used for estimating TBF using the Durnin and Womersley (DW) equation.35 The skinfold fat areas for the mid-arm, waist, and mid-thigh were estimated using the skinfold measurements of the triceps, abdomen, and thigh in addition to using the body circumferences of the mid-arm, waist, and mid-thigh33,36 with results expressed as cm2 to reflect the size of the subcutaneous fat compartments. Fat-free areas, expressed as cm2, reflected the size of lean body mass compartments at various regions.
Blood was collected after a minimum 8-hour fast prior to enrollment, 1 month after randomization, then at 4-month intervals thereafter. Aliquots of serum were stored at −70°C and shipped on dry ice to a central CPCRA laboratory. Using standardized procedures at the central laboratory, concentrations of total cholesterol, triglycerides, and high-density lipoprotein (HDL) cholesterol were measured, while low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) cholesterols were calculated. If triglyceride levels were >400 mg/dL, LDL and VLDL cholesterol levels were directly measured.37 The glucose concentration was determined by the local Clinical Laboratory Improvement Amendments (CLIA)-certified laboratories. Fasting insulin concentration was measured at a central CPCRA laboratory and was used as a measure of insulin-mediated glucose disposal or insulin resistance (IR).38 Using the homeostasis model of assessment (HOMA), IR was calculated by the following formula: HOMA (IR) = fasting glucose (mg/dL) × insulin (microunits/mL) × 0.0555/22.5.39
The primary analyses were by intent to treat. For each body composition measurement and each metabolic parameter, graphs were prepared of the average change from baseline to each follow-up visit by treatment assignment. The averages of the change from baseline to the first follow-up visit (1 month for metabolic parameters and 4 months for anthropometric measurements) for the 2 arms were compared to ascertain early differential changes in measures by treatment assignment. An on-treatment analysis (not presented) was also performed, yielding similar results as the intent-to-treat analysis.
Using repeat-measurement analyses40 with random intercepts and random slopes, linear regression lines were fitted to the follow-up data (beginning at 1 month for the metabolic parameters and at 4 months for the anthropometric measurements) by treatment arm. The slopes of the lines were used to estimate the rate of change for the body composition measurements (at 4 months and beyond) and the metabolic parameters (at 1 month and beyond). Additionally, the mean change for each measurement from baseline for all follow-up visits was determined for each arm and compared adjusting for the baseline value.
Of the 182 patients enrolled into the NRTI substudy, 96 coenrolled in the metabolic substudy (46 assigned to the ddI + d4T arm and 50 assigned to the ABC + 3TC arm). Among the NRTI substudy patients, those coenrolled in the metabolic substudy had a higher mean CD4+ lymphocyte count (251 cells/mm3 vs. 168 cells/mm3, P < 0.01) and fewer prior AIDS-defining illnesses (32 vs. 52%, P = 0.01) than those participating only in the NRTI substudy.
The demographic and clinical characteristics of the study population are shown in Table 1. At baseline, the median CD4+ lymphocyte count was 237 cells/mm3 and the median log10 HIV RNA was 5.07 copies/mL. As noted in the table, there were no significant differences in any of the demographic or clinical characteristics or body composition measurements with the following exceptions. A larger proportion of patients assigned to the ddI + d4T arm had a history of IV drug use and hepatitis C than those randomly allocated to the ABC + 3TC arm (19.6 vs. 4.0%, P = 0.02; 28.3 vs. 12.2%, P = 0.05, respectively), while fewer patients assigned to the ddI + d4T arm were current cigarette smokers (37.0 vs. 54.0%, P = 0.09). All of the baseline metabolic parameters were within normal limits (Table 2). In both treatment arms, use of antiretroviral therapy was similar, with initially 69% receiving a PI and 68% receiving an NNRTI. The predominant PIs used were nelfinavir (38%), indinavir (27%), and indinavir + ritonavir (20%).
Discontinuation of assigned NRTI regimen was similar between the treatment groups at 32.4 months of follow-up (65% ddI + d4T vs. 56% ABC + 3TC, P = 0.36) and no difference was seen in the percentage using PIs or NNRTIs. The median time on the assigned NRTI treatment was similar between the 2 arms (ddI + d4T: 16.7 months vs. ABC + 3TC: 20.1 months, P = 0.89). At follow-up, the mean change from baseline for the total CD4+ lymphocyte count was 115 cells/mm3 for ddI + d4T and 141 cells/mm3 for ABC + 3TC (P = 0.50). The mean log10 HIV RNA changes from baseline were −2.0 copies/mL for ddI + d4T and −2.1 copies/mL for ABC + 3TC (P = 0.86), with the most significant decline in viral load occurring within the 1st month of therapy in both arms.
For selected metabolic parameters, the mean change from baseline to each follow-up visit stratified by study arm is presented in Figure 2. For each treatment regimen, the rate of change and its standard error after the 1-month follow-up are calculated. In addition, for all of the metabolic parameters measured, the mean changes after a month of therapy and after all of the follow-up visits are presented in Table 2. The initial effect of therapy (defined as change from baseline to 1 month) showed average increases in both arms for fasting HDL cholesterol and LDL cholesterol, while initially fasting triglycerides increased only in the ABC + 3TC arm. Subsequently, more so for the ddI + d4T arm than the ABC + 3TC arm, the overall rate of change increased for triglycerides (2.14 mg/dL/mo vs. 0.07 mg/dL/mo, P = 0.08). For HDL cholesterol, even though there was an overall increase from baseline for both treatment arms, the rate of change declined for the ddI + d4T arm after the 1-month follow-up visit, while the rate increased for the ABC + 3TC arm, with these 2 rates being significantly different from each other (P = 0.03). In terms of LDL cholesterol, despite an overall increase from baseline for both the ddI + d4T and ABC + 3TC arms (10.1 mg/dL vs. 14.2 mg/dL), there was a decline in the rate of change for both arms after the 1-month follow-up visit, with the trend being greater for the ddI + d4T arm than for the ABC + 3TC (−0.66 mg/dL/mo vs. −0.26 mg/dL/mo, P = 0.08).
For fasting insulin, the rate of change beyond the 1-month follow-up visit did not differ by study assignment (Fig. 2). But initially, there was a significant increase in mean fasting insulin for the ddI + d4T arm when compared with the ABC + 3TC arm (5.9 microunits/mL vs. −0.3 microunits/mL, P = 0.04), which persisted throughout follow-up (Table 2). Similarly, an increase in the initial mean value for IR as measured by HOMA was seen for the ddI + d4T arm, but not for the ABC + 3TC arm (1.4 vs. −0.3, P = 0.05), which also persisted throughout follow-up. However, while mean fasting glucose levels increased slightly in both study arms, no significant differences were seen between the 2 treatment groups (Table 2). Only one person developed diabetes and was in ABC + 3TC arm.
Body Composition Changes
Figures 3 and 4 show changes from baseline for selected body composition measurements by the 2 treatment arms. For BCM, the rates of change increased after the 4-month follow-up visit for both study arms, but the rates did not differ significantly (P = 0.30). However, TBF declined significantly beyond the 4-month follow-up visit for the ddI + d4T arm as measured by BIA (rate: −0.08 kg/mo, P = 0.04) but not by the DW equation (rate: −0.05 kg/mo, P = 0.18), while TBF significantly increased for the ABC + 3TC arm both by BIA (0.08 kg/mo, P = 0.05) and DW equation (0.08 kg/mo, P = 0.01), with the rates being significantly different from each other (P < 0.01) (Fig. 3). Changes in the hip circumference followed a similar pattern, while changes in the waist circumferences did not differ significantly by study assignment. For the hip circumference, beyond the 4-month follow-up visit, the rate of change for the ddI + d4T arm showed a decline, with rate being significantly different from zero, whereas for the ABC + 3TC arm, the rate increased, with the rates of change between the 2 study arms being significantly different.
Regional body composition beyond the 4-month follow-up visit differed significantly by study assignment (Fig. 4). For the mid-arm skinfold fat area, there was a significant decrease in regional fat for patients assigned to the ddI + d4T arm (P < 0.01), while there was a slight increase for the ABC + 3TC arm, with both being significantly different from each other (P < 0.01). For the waist skinfold fat area, a significant decline in the rate of change from zero was seen for the ddI + d4T arm (P = 0.03), while the ABC + 3TC arm had a significant increase (P = 0.02), with these 2 rates being significantly different from each other (P < 0.01). The skinfold fat-free areas for the mid-arm and waist increased from baseline to the 4-month follow-up visit in both arms, with no apparent change in the rates beyond that time point.
As part of a subgroup analysis, we assessed the relationship between hepatitis C infection and body composition changes. Within each of the treatment arms, no differences were seen in the rates of change for any of the body composition or metabolic measurements for those with or without hepatitis C infection. Furthermore, comparisons by treatment assignment did not identify any significant differences.
Use of thymidine analogue NRTIs has been associated with the occurrence of HIV-associated lipoatrophy.5,16-19,41,42 In this prospective evaluation comparing a thymidine analogue-containing regimen consisting of ddI + d4T to a thymidine analogue-sparing regimen consisting of ABC + 3TC in antiretroviral-naive patients initiating highly active antiretroviral therapy (HAART), our data demonstrated an initial increase in all body composition parameters (ie, BCM, TBF, and subcutaneous fat) regardless of treatment assignment. This initial increase was followed by a progressive and preferential loss of subcutaneous fat and TBF among those randomly assigned to treatment with ddI + d4T when compared with ABC + 3TC. The lack of decline in the thymidine analogue-sparing regimen supports recent findings of improvement in lipoatrophy being associated with the switch to thymidine analogue-sparing regimens.28,29 While initially all lipid parameters increased in both treatment arms, long-term treatment with ddI + d4T was associated with a decline in HDL cholesterol compared with ABC + 3TC. Furthermore, while both arms showed a decreasing LDL cholesterol, triglycerides increased more so for the ddI + d4T arm than the ABC + 3TC arm. Finally, a significant early and sustained increase in insulin and IR was seen in the ddI + d4T arm compared with the ABC + 3TC arm, despite a similar proportion of PI use in each study arm. While prior studies have demonstrated a dose-dependent early increase in IR associated with the use of HIV PIs,43,44 our findings support a potential role of ddI + d4T or ddI + d4T-related lipoatrophy in the development of IR.
Prospective randomized comparisons evaluating body composition changes among antiretroviral-naive patients are limited.6,23,24,26 In our study, body composition changes were demonstrated by an initial increase in the BCM and TBF in both arms, followed by a decrease in body fat noted only in patients assigned to the ddI + d4T arm, with the fat-free mass remaining relatively stable, consistent with previous studies.6,17 The gains noted during the first few months after initiation of HAART in BCM and TBF were coupled with the decrease in viral load. Similarly, the magnitude of the metabolic changes (ie, increases in triglycerides, HDL cholesterol, and LDL cholesterol) was greatest in the 1st month after initiation of antiretroviral therapy, regardless of treatment assignment, again paralleling the decline in HIV RNA, suggesting a direct effect of ongoing viral replication on the lipid parameters.
In our study, we noted the development of lipoatrophy with a progressive loss of subcutaneous fat with increasing cumulative antiretroviral exposure as previously reported.17,21,42 Diminished mitochondrial function has been proposed as causing lipoatrophy as well as a wide range of adverse events in HIV-infected persons taking NRTIs. However, the relationship between nucleoside analogues and lipoatrophy is confounded by the fact that NRTIs are not the only relevant cause of mitochondrial toxicity.45 Several studies of peripheral blood mononuclear cells and adipose tissue have shown evidence of mitochondrial DNA depletion in untreated HIV-infected subjects.46,47 While the mechanism by which nucleoside analogues contribute to the syndrome of lipoatrophy has not been fully elucidated, differential effects with certain NRTI combinations have been reported.26,45 Significant reductions in mitochondrial DNA have been observed in individuals receiving the combination of ddI and d4T, but not with the use of zidovudine, 3TC, or ABC, potentially indicating an additive effect of mitochondrial toxicity associated with certain NRTIs.48 Other studies in which patients on thymidine-containing regimens were switched from these agents to an ABC-containing regimen, improvement was noted in the peripheral lipoatrophy, with continued fat loss seen in those continuing their original regimen.12,27-29 Moreover, ABC and 3TC have not been associated with significant mitochondrial toxicity based on both in vitro and clinical experience.26,49 Nonetheless, our study is the first randomized study to assess the comparative effect of these 2 types of NRTIs in antiretroviral-naive patients.
Prior investigators have reported central obesity and lipoatrophy both prior to the initiation of antiretroviral therapy50 and with the use of HAART.5,15 In this study, with the initiation of HAART therapy, there was an initial increase in abdominal fat for both treatment arms, followed by a progressive loss for the ddI + d4T arm, but continued increase in abdominal fat for the ABC + 3TC arm. As abdominal obesity has been associated with higher risk of cardiovascular events,51 the ongoing effects of continued ABC + 3TC and its long-term implications require further investigation.
Waist-to-hip ratio (WHR) has been used as a marker of central obesity, which usually is accompanied by an increase in the waist circumference. However, WHR can also appear to increase when the hip circumference decreases. As seen in Figure 3, for the ddI + d4T arm, while the rates of change for both the waist and hip circumferences decreased, the decline was more rapid for the hip circumference, resulting in the WHR actually increasing. An opposite effect was seen with the ABC + 3TC arm, with both circumferences increasing but more slowly for the waist circumference, resulting in a declining WHR. These findings suggest that changes in the WHR may be misleading with respect to central obesity.
Consistent with other studies,21,52 we found a significant increase in fasting total cholesterol, LDL cholesterol, and triglycerides following the initiation of HAART in both study arms. These initial increases in lipid parameters may be related to an increase in body weight or improved immune function,53 but the long-term effects of HAART on lipids have not been fully elucidated. The lower levels of HDL cholesterol seen in the ddI + d4T arm may have implications in terms of risk factors for the development of arteriosclerosis.51 Thus, while the central obesity noted in association with the ABC + 3TC-containing regimens may be associated with increased risk of cardiovascular events, lipoatrophy, IR, and decreasing HDL cholesterol in association with ddI + d4T-containing regimens may also be associated with increased risk of cardiovascular events.54
In this study, we used BIA and anthropometric measurements to assess body composition. Measurement of body composition in the clinical setting is hampered by the lack of a single method that is accurate, readily available, and affordable. Dual-energy x-ray absorptiometry (DEXA) is currently the most accepted laboratory technique for measuring body composition, because it is noninvasive, requires minimum efforts from the subjects, and is reliable.55 However, anthropometry performed by well-trained observers using standardized measurement protocols and tools34 has been used as a reliable tool for measuring body composition in HIV-infected patients.56,57 Recently, He et al58 compared anthropometric measurements of subcutaneous fat and lean areas to measurements obtained by MRI, supporting the comparability of our demonstrated changes in body composition with similarly designed prospective studies using DEXA.6,17
In summary, this prospective evaluation provides evidence that prolonged use of a thymidine analogue-containing regimen consisting of ddI + d4T compared with a thymidine analogue-sparing regimen consisting of ABC + 3TC in antiretroviral-naive patients resulted in the development of lipoatrophy as demonstrated by progressive loss of subcutaneous and TBF. The significant increase in insulin and IR noted in the ddI + d4T arm compared with the ABC + 3TC arm necessitates close monitoring for the development of diabetes or switching therapy to a thymidine analogue-sparing regimen. Conversely, the development of abdominal obesity in association with ABC + 3TC is also of concern. The demonstrated differential effect on lipid metabolism by treatment assignment necessitates ongoing longitudinal assessment of the effects of the different treatment strategies. Furthermore, this study highlights the importance of metabolic complications and the need for new agents not associated with these effects.
The authors thank all of the patients who participated in the study and all of the research nurses who carefully performed all of the anthropometric measurements.
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