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. Author manuscript; available in PMC: 2014 Nov 1.
Published in final edited form as: J Acquir Immune Defic Syndr. 2013 Nov 1;64(3):279–283. doi: 10.1097/qai.0b013e3182a97c39

Effects of Switching from Efavirenz to Raltegravir on Endothelial Function, Bone Mineral Metabolism, Inflammation, and Renal Function: A Randomized, Controlled Trial

Samir K Gupta 1, Deming Mi 2, Sharon M Moe 3, Michael P Dubé 4, Ziyue Liu 5
PMCID: PMC4091630  NIHMSID: NIHMS525967  PMID: 24278992

Abstract

We performed a randomized, controlled trial in 30 HIV-infected participants to either continue tenofovir/emtricitabine/efavirenz (Continuation Group) or switch to tenofovir/emtricitabine/raltegravir (Switch Group) for 24 weeks. There were no significant differences in the changes in flow-mediated dilation, 25(OH)vitamin D, or parathyroid hormone levels. Total cholesterol, high sensitivity C-reactive protein, serum alkaline phosphatase, sCD14 levels, and renal function significantly declined in the Switch Group compared to the Continuation Group; however, sCD163 levels significantly increased in the Switch Group. These findings suggest that raltegravir is not inherently more beneficial to endothelial function compared to efavirenz but may impact renal function and monocyte activation.

Keywords: Efavirenz, raltegravir, endothelial function, vitamin D, monocyte activation, renal function

INTRODUCTION

As HIV-infected patients are achieving nearly normal life expectancies with the use of potent antiretroviral therapies (ART), cardiovascular disease (CVD) has emerged as a leading cause of morbidity and mortality.1 One mechanism by which HIV infection or its therapies may lead to this increased risk in CVD is through impairment of the vascular endothelium. We recently completed a 12 month observational study in which we assessed flow-mediated dilation (FMD), a measure of in vivo endothelial function, over 12 months in HIV-infected patients initiating their first ART regimen.2 Although FMD did not significantly change in the entire group, we observed worsening FMD with efavirenz (EFV)-based treatment and an improvement in FMD in those receiving protease inhibitors. The large reduction in FMD in the EFV group was primarily in those receiving the combination of tenofovir (TDF), emtricitabine (FTC), and EFV. Another recent study also suggested that initiation of EFV-based regimens, most of which also incorporated TDF, also led to a decrease in FMD.3 Although large, observational studies, such as the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study, have suggested no increase in risk of myocardial infarctions with use of non-nucleoside reverse transcriptase inhibitors such as EFV,4 in the randomized trial ACTG 5202, the use of TDF/FTC/EFV was associated with numerically more acute ischemic events compared to other once-daily regimens, including those incorporating abacavir.5 Taken together, these findings suggest a potentially adverse effect of EFV, especially the combination of TDF/FTC/EFV, on cardiovascular health.

One possible mechanism for an adverse effect of TDF/FTC/EFV on CVD risk may involve the calcium-phosphorus homeostasis axis, with reductions of circulating vitamin D levels with EFV and/or increases in parathyroid hormone levels with TDF, respectively; both abnormalities have been associated with endothelial dysfunction.6–9 If secondary hyperparathyroidism due to EFV, especially when coupled with TDF, is the cause of increased CVD risk with this specific combination, then perhaps removing the EFV component of an ART regimen would be beneficial. Therefore, we conducted a randomized trial assessing the effects of switching HIV-infected patients receiving TDF/FTC/EFV to TDF/FTC/Raltegravir (RAL) on endothelial function and markers of bone mineral metabolism.

METHODS

Study design

We performed a single-center, open-label, randomized, controlled trial in 30 HIV-infected study participants who had been receiving TDF/FTC/EFV as their initial HIV treatment regimen (ClinicalTrials.gov NCT01270802). Participants were randomized 1:1 to continuing treatment with TDF/FTC/EFV (‘Continuation Group’) vs. switching their regimen to TDF/FTC plus RAL 400 mg twice daily (‘Switch Group’). Study procedures were performed at entry, week 8, and week 24. Randomization in varying sized blocks (2, 4, or 6) was employed for this study. This trial was approved by the Indiana University Institutional Review Board. All participants provided written, informed consent prior to screening. Merck & Co. provided both an unrestricted research grant in support of this trial and raltegravir for those assigned to the Switch Group but had no role in the design, conduct, or reporting of the study results.

Study population

Participants were recruited from the HIV outpatient clinics associated with the Indiana University Health medical system. Primary inclusion criteria included documented HIV-1 infection, age ≥18 years, receipt of TDF/FTC/EFV as their initial treatment regimen for at least one year prior to screening, and having both an HIV RNA level <50 copies/mL at screening and also between one and six months prior to screening. Major exclusion criteria included diagnosed cardiovascular disease, diabetes, uncontrolled hypertension (screening systolic blood pressure >160 mm Hg or diastolic pressure > 90 mm Hg), other systemic inflammatory disease (although hepatitis B or C co-infection was allowed); estimated creatinine clearance <50 mL/min; or use of lipid-lowering drugs.

Study procedures

Participants were required to fast and not smoke for at least 8 hours prior to all study procedures. FMD and nitroglycerin-mediated dilation (NTGMD) studies were performed using an Acuson CV70 ultrasound machine at all study visits according to recommended guidelines 10 by a single registered vascular ultrasonographer. Images were interpreted by a blinded, single investigator (S.K.G.) using Access Point Web software (Freeland Systems, Westminster, CO). The intraclass correlations for reproducibility for baseline diameter and FMD measured twice in 12 healthy volunteers in our laboratory under these conditions were 0.97 and 0.73, respectively.

Circulating inflammatory markers [high sensitivity C-reactive protein (hsCRP), serum interleukin-6 (IL-6), soluble tumor necrosis factor-α receptors I and II (sTNFRI, sTNFRII), monocyte chemoattractant protein-1 (MCP-1), interferon-γ-inducible protein-10 (IP-10)], endothelial markers [soluble vascular cell adhesion molecule-1 (sVCAM-1), asymmetric dimethylarginine (ADMA)], markers of monocyte/macrophage activation [soluble CD14 (sCD14), soluble CD163 (sCD163)], and metabolic markers [serum cystatin C, lipid fractions, insulin] were measured at the University of Vermont Laboratory for Clinical Biochemistry Research. Serum calcium, phosphorus, parathyroid hormone (PTH), 25(OH)vitamin D, and fibroblast growth factor-23 (FGF-23) were measured in the research laboratory of one investigator (S.M.M.). All of these markers were measured in batch from archived frozen samples kept at −80°C. Serum glucose, creatinine, and CD4 cell count along with urine albumin, protein, phosphorus, and creatinine levels (measured on fasting morning urine samples) were assessed at the Indiana University Health clinical laboratory. Renal function was estimated as creatinine clearance with the Cockcroft-Gault equation11 and as glomerular filtration rates (eGFR) using the 2009 CKD-EPI equation,12 the 2012 CKD-EPI cystatin C equation,13 and the 2012 CKD-EPI combined cystatin C-creatinine equation.13 The homeostasis model assessment-insulin resistance (HOMA-IR) was used to estimate insulin resistance from fasting glucose and insulin measures.14

Statistical analysis

We assumed that the declines in FMD seen with TDF/FTC/EFV in our previous study 2 would fully reverse with switch to TDF/FTC/RAL. Thus, the clinically relevant effect size to be detected for FMD change was +3.12% with a standard deviation of 4% in those switching from EFV to RAL. Using a two-sample, independent, two-tailed t-test with 5% type I error and 20% type II error, a sample size of 13 per group would be needed to find a difference in FMD between groups. Allowing for a 10% dropout rate, we planned to recruit 15 subjects per group.

Categorical variables were examined using Fisher’s exact test. We employed Student’s t-test for comparisons of continuous measures as we found no evidence of violation of the normality assumption for these variables. Of note, serum glucose, calcium, PTH, 25(OH)vitamin D, FGF-23, hsCRP, IL-6, triglycerides, MCP-1, HIV-1 RNA, HOMA-IR, urine albumin/creatinine, urine protein/creatinine, and urine calcium/creatinine required logarithmic transformation to approximate normal distributions prior to such analysis. Wilcoxon rank sum tests were also performed for log-transformed variables, and the same significance levels were obtained (data not shown).

Analyses were performed as intention to treat but without corrections for multiple testing for the secondary analyses. Two-sided P-values <0.05 were considered statistically significant. All analyses were performed in SAS 9.3 (SAS Inc., Cary, NC).

RESULTS

Study cohort characteristics

Enrollment into this trial occurred between April 2011 and May 2012. Thirty-two persons screened for enrollment. Two of these failed screening for having screening HIV-1 RNA levels >50 copies/mL; the remaining 30 were equally randomized into the two study groups. Of these, one participant in the Continuation Group was removed at Entry for confirmed virologic failure (repeat HIV-1 RNA >50 copies/mL). One participant in the Continuation Group withdrew from participation between Entry and week 8 due to moving out of area. One participant in the Switch Group was lost to follow-up between week 8 and week 24. Thus, 13 and 15 participants, respectively, were assessed in the Continuation Group and Switch Group at week 8 whereas 13 and 14 participants, respectively, were assessed at Week 24. Table 1 shows the well-balanced baseline characteristics of the 30 enrolled participants.

TABLE 1.

Baseline Characteristics of the Study Groups

Characteristic Continuation Group (N=15) Switch Group (N=15)
Age, yrs 38 (12.0) 39 (10.6)
Male sex 13 (87%) 14 (93%)
Black race 8 (53%) 10 (67%)
Hispanic ethnicity 0 (0%) 0 (0%)
Current smoker 8 (53%) 9 (60%)
Active hepatitis B 2 (13%) 2 (13%)
Active hepatitis C 1 (7%) 1 (7%)
Weight, kg 88.2 (17.3) 84.7 (17.9)
Body mass index, kg/m2 28.2 (5.5) 27.6 (6.3)
Baseline brachial artery diameter, cm 0.43 (0.07) 0.42 (0.04)
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Data presented as mean (standard deviation) or numbers (percent); active hepatitis B defined as having a positive surface antigen on record or at screening; active hepatitis C defined as having a positive antibody on record or at screening; seasonality data based on those who completed the trial (13 in the Continuation Group and 14 in the Switch Group)

Changes in vascular measures

The vascular results are shown in Table 2 and in Table 3 (Supplemental Digital Content 1, which shows additional secondary data comparisons). There were no significant changes in FMD, ADMA, or sVCAM-1 between groups at either Week 8 or Week 24.

TABLE 2.

Comparisons of Changes in Vascular, Metabolic, Inflammatory, Bone, and Renal Markers at Week 8 and Week 24

Laboratory Marker Continuation Group
Switch Group
Entry 8 Week Change 24 Week Change Entry 8 Week Change 24 Week Change
Vascular Markers
Flow-mediated dilation, % 3.82 (2.71) −0.41 (2.15) −0.67 (3.35) 3.09 (2.36) 1.17 (4.20) −0.10 (3.26)
Nitroglycerin-mediated dilation, %* 17.46 (9.08) 6.88 (9.42) −0.15 (8.55) 17.85 (8.46) −3.02 (6.43) −4.77 (8.95)
Metabolic Markers
HOMA-IR 1.75 (1.31) −0.04 (1.09) 0.58 (1.18) 1.67 (0.94) 0.17 (1.48) 0.60 (1.42)
Serum total cholesterol, mg/dL*‡ 156.87 (32.93) 4.00 (16.86) 1.08 (9.88) 154.07 (36.67) −12.2 (16.95) −12.64 (19.61)
Serum HDL-C, mg/dL 42.27 (10.16) 0.85 (6.62) 0.15 (6.09) 39.33 (11.64) 0.13 (6.48) 0.29 (6.06)
Serum LDL-C, mg/dL* 89.39 (28.93) 6.08 (16.01) −2.23 (15.13) 90.61 (37.78) −8.58 (17.14) −8.65 (18.24)
Serum triglycerides, mg/dL 125 (64) −13(36) 16 (98) 120 (77) −19 (66) −22 (25)
Immunologic/inflammatory Markers
Serum hsCRP, mg/L‡ 2.55 (2.45) 0.99 (6.13) −0.66 (2.07) 3.93 (3.95) −0.84 (2.70) −2.16 (2.20)
Serum IL-6, pg/mL 1.95 (1.42) −0.34 (1.32) −0.62 (1.10) 1.47 (1.66) 0.24 (1.32) −0.10 (0.88)
sCD14, ng/mL*‡ 2441.15 (378.02) −173.28 (321.51) −112.54 (421.26) 2443.2 (283.94) −412.16 (288.84) −458.14 (319.03)
sCD163, ng/mL‡ 575.80 (252.64) −28.96 (60.04) −32.26 (64.18) 577.21 (183.58) 15.24 (90.31) 32.00 (63.57)
Bone Homeostasis Markers
Serum alkaline phosphatase, mg/dL‡ 84.00 (23.15) −7.58 (9.85) −4.92 (8.2) 78.47 (15.25) −7.07 (7.47) −12.46 (9.44)
Serum parathyroid hormone, pg/mL 62.41 (18.39) 0.19 (19.04) 11.45 (39.73) 56.51 (27.70) −5.76 (22.42) −10.08 (25.64)
Serum 25(OH)vitamin D, ng/mL 18.35 (20.31) −1.01 (6.70) −0.58 (9.95) 13.70 (12.86) 5.28 (9.46) 4.50 (12.52)
Renal Function/Injury Markers
Serum creatinine, mg/dL*§ 0.91 (0.23) −0.01 (0.06) −0.02 (0.10) 0.93 (0.16) 0.06 (0.08) 0.08 (0.08)
Serum cystatin C, mg/L†§ 0.80 (0.14) −0.06 (0.07) −0.03 (0.06) 0.75 (0.11) 0.07 (0.09) 0.07 (0.1)
Creatinine clearance, mL/min§ 129.64 (41.61) −2.00 (18.78) 12.25 (23.29) 130.93 (39.88) −7.36 (14.37) −11.69 (12.66)
Estimated GFR (2009 CKD-EPI), mL/min/1.732‡ 110.55 (23.73) 0.51 (4.71) 0.74 (9.40) 111.15 (20.89) −4.77 (9.80) −8.67 (8.78)
Estimated GFR (2012 CKD-EPI Cystatin), mL/min/1.732†§ 110.40 (17.13) 6.86 (11.54) 3.06 (8.07) 115.79 (12.11) −8.43 (11.26) −8.50 (11.04)
Estimated GFR (2012 CKD-EPI Cystatin-Creatinine), mL/min/1.732†§ 100.19 (20.38) 5.24 (7.15) 2.72 (6.48) 102.7 (16.78) −7.09 (9.22) −8.22 (6.70)
Urine albumin/creatinine, mg/g 7.32 (7.39) 0.86 (8.13) −1.57 (2.90) 4.84 (3.98) −1.51 (2.26) 11.99 (44.84)
Urine protein/creatinine, g/g 0.12 (0.07) −0.01 (0.02) −0.01 (0.03) 0.08 (0.05) −0.01 (0.02) 0.01 (0.04)
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Data presented as mean (standard deviation)

HOMA-IR, homeostasis model assessment-insulin resistance; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high sensitivity C-reactive protein; IL-6, interleukin-6; sCD14 and 163, soluble cluster of differentiation 14 and 163; GFR, glomerular filtration rate

*

P<0.05 for differences between groups in the change from Entry to Week 8

†

P<0.01 for differences between groups in the change from Entry to Week 8

‡

P<0.05 for differences between groups in the change from Entry to Week 24

§

P<0.01 for differences between groups in the change from Entry to Week 24

Changes in bone mineral markers

There were no significant differences in the changes between groups in PTH, 25(OH)vitamin D, or FGF-23 levels at either week 8 or week 24 (Tables 2 and 3, Supplemental Digital Content 1). Alkaline phosphatase levels significantly decreased more in the Switch Group than in the Continuation Group at week 24.

Changes in metabolic markers

Total cholesterol levels decreased significantly at both weeks 8 and 24 in the Switch Group compared to the Continuation Group (Table 2). There was also a significant decrease in the Switch Group in LDL-C at week 8, but there no significant differences between groups in LDL-C at week 24.

Changes in inflammatory markers

As shown in Table 2, hsCRP levels and sCD14 levels decreased significantly more so in the Switch Group than the Continuation Group at weeks 8 and 24. There was a significant increase in sCD163 in the Switch Group compared to the Continuation Group at week 24. There were no significant differences between groups in the other inflammatory markers (see Table 3, Supplemental Digital Content 1).

Changes in renal function markers

Interestingly, we found significant decreases in creatinine clearance at week 24 (but not at week 8) and in all three GFR estimates in the Switch Group compared to the Continuation Group at week 8 with significant differences in eGFR persisting using just the two 2012 CKD-EPI equations at week 24 (Table 2). However, there were no significant differences between groups in the changes in urine albumin/creatinine or protein/creatinine ratios at either time point.

Safety

There were no safety concerns in this trial apart from the one participant in the Continuation Group who was removed after fulfilling virologic failure criteria at Entry; there were no virologic failures in the Switch Group. There were no significant differences in numbers or types of adverse events between Groups. None of these adverse events were treatment limiting.

DISCUSSION

In HIV-infected study participants receiving TDF/FTC/EFV as their first regimen and with suppressed viremia, we did not find that switching the EFV component of this regimen to RAL resulted in changes in endothelial function over 24 weeks. These data do not support the hypothesis that RAL is intrinsically more beneficial to the endothelium compared to EFV. Our results are similar to those found by Masia et al15 who also found no change in FMD by switching from a protease inhibitor to RAL or by Hatano et al16 who found no improvement in FMD after RAL intensification.

We had speculated that any potential changes in FMD with switch from EFV to RAL could be due to changes in vitamin D or PTH.17 However, none of the serum or urine bone mineral markers changed significantly apart from a reduction in serum alkaline phosphatase in the Switch Group as expected.18

Total cholesterol levels improved in the Switch Group, which corroborates findings from previous studies assessing switches from protease inhibitors15, 19, 20 or EFV20 to RAL. Similar findings in ART-naïve studies comparing RAL to EFV showed less effects of RAL on lipid profiles.21

We surprisingly found declines in renal function, both in estimated creatinine clearance and in eGFR, in the Switch Group compared to the Continuation Group. The differences between groups in eGFR we observed were approximately 10 mL/min/1.732, which are similar to the declines found in those initiating TDF.5, 22, 23 The integrase inhibitor dolutegravir has been reported to increase serum creatinine through inhibition of creatinine secretion via the human organic cation transporter 2 (hOCT2) in the renal proximal tubule but does not lead to actual declines in directly measured GFR.24 This inhibition of hOCT2 should not lead to changes in serum cystatin C. As such, the increases in both cystatin C and creatinine with RAL in this study may suggest a true negative effect on glomerular function. The mechanism by which RAL may worsen renal function in those who are virologically suppressed is not clear. RAL decreases circulating tenofovir concentrations, so a drug interaction leading to tenofovir nephrotoxicity is unlikely. In addition, blood pressures did not change significantly between groups (data not shown).

Regarding the inflammatory markers assessed in this study, hsCRP levels significantly decreased with switch to RAL compared to continuation with EFV, which is in contrast to the findings by Lake et al who found no change in hsCRP in their trial of protease inhibitor switch to RAL among women with central obesity.20 We also explored potential changes in sCD14 and sCD163 as markers of monocyte activation with switch to RAL. Greater sCD14 levels have been linked to an increased risk of death25 while higher sCD163 levels have been associated with worsening inflammatory atherosclerotic disease in those with HIV infection.26, 27 Similar to our results, a greater reduction in sCD14 with TDF/FTC/RAL compared to non-RAL-based regimens has been previously reported in ART-naïve patients.28 It is possible that the increased penetration of RAL into gut tissue29 may lead to decreased viral replication in this reservoir with consequent reductions in bacterial translocation and the monocyte-secreted lipopolysaccharide receptor sCD14. Similar to sCD14, circulating sCD163 levels are increased by lipopolysaccharide and other inflammatory triggers,30 so it is not clear why switching from EFV to RAL would lead to an apparently paradoxical increase in sCD163.

Limitations to our study should be acknowledged. This study design was open-label as a blinded study with matching placebos was considered too difficult to implement given the differences in dosing schedules between EFV and RAL. We believe this limitation was somewhat mitigated as the vascular ultrasound readings were blinded. We also acknowledge that the sample size was small, although it was based on our previously published data for the primary endpoint of change in FMD. It is unlikely that we would have found clinically meaningful differences between groups in change in FMD with larger sizes given that the minor changes observed. Although the reproducibility of FMD in our laboratory appears modest, the technique in our hands actually compares quite favorably, or even better than, those of other groups.31, 32 Of note, the high variability of FMD was accounted for in our sample size estimate and, as such, likely would not have led to the negative findings. We do acknowledge that it is certainly possible that the study duration was too short to detect changes in FMD and several of the biomarkers. We also performed numerous statistical tests without adjustment for these multiple comparisons, so we caution that some significant differences, especially in regards to the differential findings related to the monocyte activation markers, may have been found by chance. However, the reductions in renal function with RAL were found using two different markers, namely creatinine and cystatin C, and, thus, this finding is more likely to be true. Overall, our results should be considered hypothesis-generating with additional research required to determine the mechanisms underlying the potentially negative effects of RAL on renal function along with the long-term benefits and risks of using raltegravir-based regimens.

Supplementary Material

1

Acknowledgments

This work was supported by an unrestricted research grant from Merck & Co. with additional support from NIH HL095149 and the Indiana Clinical and Translational Sciences Institute funded, in part by Grant Number TR000006 from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award.

We thank Ms. Vicki Mravca-Wilkey for study coordination, Mr. Jeffrey Waltz for performing the vascular ultrasonography studies, and Mr. Jonathon Mathews for data management. We also thank Dr. Russell Tracy, Ms. Elaine Cornell, and Ms. Kali O’Neill for performing the biomarker assays. We also thank Dr. Marshall Glesby for serving as the independent monitor for this study. Most of all, we thank the study participants for their generous participation.

Footnotes

Conflicts of Interest and Source of Funding: SKG has received unrestricted research grants from Merck & Co., Janssen/Tibotec Therapeutics, and Gilead Sciences. SKG received compensation for one lecture in 2012 to Merck & Co. pertaining to HIV-related renal disease and had received travel support from Gilead Sciences in 2011 to present data at IAS for a tenofovir-related study. MPD has received unrestricted research grants from Gilead Sciences and Serono. For the remaining authors none were declared.

Contributor Information

Samir K. Gupta, Indiana University School of Medicine.

Deming Mi, Indiana University School of Medicine.

Sharon M. Moe, Indiana University School of Medicine.

Michael P. Dubé, Keck School of Medicine, University of Southern California.

Ziyue Liu, Indiana University School of Medicine.

References

  • 1.Sackoff JE, Hanna DB, Pfeiffer MR, et al. Causes of death among persons with AIDS in the era of highly active antiretroviral therapy: New York City. Ann Intern Med. 2006;6:397–406. doi: 10.7326/0003-4819-145-6-200609190-00003. [DOI] [PubMed] [Google Scholar]
  • 2.Gupta SK, Shen C, Moe SM, et al. Worsening Endothelial Function with Efavirenz Compared to Protease Inhibitors: A 12-Month Prospective Study. PLoS ONE. 2012;9:e45716. doi: 10.1371/journal.pone.0045716. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Kristoffersen US, Wiinberg N, Petersen CL, et al. Reduction in coronary and peripheral vasomotor function in patients with HIV after initiation of antiretroviral therapy: a longitudinal study with positron emission tomography and flow-mediated dilation. Nucl Med Commun. 2010;10:874–880. doi: 10.1097/MNM.0b013e32833d82e6. [DOI] [PubMed] [Google Scholar]
  • 4.Friis-Moller N, Reiss P, Sabin CA, et al. Class of antiretroviral drugs and the risk of myocardial infarction. N Engl J Med. 2007;17:1723–1735. doi: 10.1056/NEJMoa062744. [DOI] [PubMed] [Google Scholar]
  • 5.Daar ES, Tierney C, Fischl MA, et al. Atazanavir plus ritonavir or efavirenz as part of a 3-drug regimen for initial treatment of HIV-1. Ann Intern Med. 2011;7:445–456. doi: 10.1059/0003-4819-154-7-201104050-00316. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Barenbrock M, Hausberg M, Kosch M, et al. Effect of hyperparathyroidism on arterial distensibility in renal transplant recipients. Kidney Int. 1998;1:210–215. doi: 10.1046/j.1523-1755.1998.00963.x. [DOI] [PubMed] [Google Scholar]
  • 7.Baykan M, Erem C, Erdogan T, et al. Impairment of flow mediated vasodilatation of brachial artery in patients with primary hyperparathyroidism. Int J Cardiovasc Imaging. 2007;3:323–328. doi: 10.1007/s10554-006-9166-8. [DOI] [PubMed] [Google Scholar]
  • 8.Ekmekci A, Abaci N, Colak Ozbey N, et al. Endothelial function and endothelial nitric oxide synthase intron 4a/b polymorphism in primary hyperparathyroidism. J Endocrinol Invest. 2009;7:611–616. doi: 10.1007/BF03346518. [DOI] [PubMed] [Google Scholar]
  • 9.Jolma P, Koobi P, Kalliovalkama J, et al. Treatment of secondary hyperparathyroidism by high calcium diet is associated with enhanced resistance artery relaxation in experimental renal failure. Nephrol Dial Transplant. 2003;12:2560–2569. doi: 10.1093/ndt/gfg374. [DOI] [PubMed] [Google Scholar]
  • 10.Corretti MC, Anderson TJ, Benjamin EJ, et al. Guidelines for the ultrasound assessment of endothelial-dependent flow-mediated vasodilation of the brachial artery: a report of the International Brachial Artery Reactivity Task Force. J Am Coll Cardiol. 2002;2:257–265. doi: 10.1016/s0735-1097(01)01746-6. [DOI] [PubMed] [Google Scholar]
  • 11.Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;1:31–41. doi: 10.1159/000180580. [DOI] [PubMed] [Google Scholar]
  • 12.Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;9:604–612. doi: 10.7326/0003-4819-150-9-200905050-00006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Inker LA, Schmid CH, Tighiouart H, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med. 2012;1:20–29. doi: 10.1056/NEJMoa1114248. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;7:412–419. doi: 10.1007/BF00280883. [DOI] [PubMed] [Google Scholar]
  • 15.Masia M, Martinez E, Padilla S, et al. Endothelial function in HIV-infected patients switching from a boosted protease inhibitor-based regimen to raltegravir: a substudy of the SPIRAL study. J Antimicrob Chemother. 2013;2:409–413. doi: 10.1093/jac/dks412. [DOI] [PubMed] [Google Scholar]
  • 16.Hatano H, Scherzer R, Wu Y, et al. A randomized controlled trial assessing the effects of raltegravir intensification on endothelial function in treated HIV infection. J Acquir Immune Defic Syndr. 2012;3:317–325. doi: 10.1097/QAI.0b013e31826e7d0f. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Brown TT, McComsey GA. Association between initiation of antiretroviral therapy with efavirenz and decreases in 25-hydroxyvitamin D. Antivir Ther. 2010;3:425–429. doi: 10.3851/IMP1502. [DOI] [PubMed] [Google Scholar]
  • 18.Welz T, Childs K, Ibrahim F, et al. Efavirenz is associated with severe vitamin D deficiency and increased alkaline phosphatase. AIDS. 2010;12:1923–1928. doi: 10.1097/QAD.0b013e32833c3281. [DOI] [PubMed] [Google Scholar]
  • 19.Martinez E, Larrousse M, Llibre JM, et al. Substitution of raltegravir for ritonavir-boosted protease inhibitors in HIV-infected patients: the SPIRAL study. AIDS. 2010;11:1697–1707. doi: 10.1097/QAD.0b013e32833a608a. [DOI] [PubMed] [Google Scholar]
  • 20.Lake JE, McComsey GA, Hulgan TM, et al. A Randomized Trial of Raltegravir Replacement for Protease Inhibitor or Non-Nucleoside Reverse Transcriptase Inhibitor in HIV-Infected Women with Lipohypertrophy. Aids Patient Care STDS. 2012;9:532–540. doi: 10.1089/apc.2012.0135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Lennox JL, DeJesus E, Lazzarin A, et al. Safety and efficacy of raltegravir-based versus efavirenz-based combination therapy in treatment-naive patients with HIV-1 infection: a multicentre, double-blind randomised controlled trial. Lancet. 2009;9692:796–806. doi: 10.1016/S0140-6736(09)60918-1. [DOI] [PubMed] [Google Scholar]
  • 22.Gallant JE, Moore RD. Renal function with use of a tenofovir-containing initial antiretroviral regimen. AIDS. 2009;15:1971–1975. doi: 10.1097/QAD.0b013e32832c96e9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Goicoechea M, Liu S, Best B, et al. Greater Tenofovir-Associated Renal Function Decline with Protease Inhibitor-Based versus Nonnucleoside Reverse-Transcriptase Inhibitor-Based Therapy. J Infect Dis. 2008;1:102–108. doi: 10.1086/524061. [DOI] [PubMed] [Google Scholar]
  • 24.Koteff J, Borland J, Chen S, et al. A phase 1 study to evaluate the effect of dolutegravir on renal function via measurement of iohexol and para-aminohippurate clearance in healthy subjects. Br J Clin Pharmacol. 2013;4:990–996. doi: 10.1111/j.1365-2125.2012.04440.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Sandler NG, Wand H, Roque A, et al. Plasma Levels of Soluble CD14 Independently Predict Mortality in HIV Infection. J Infect Dis. 2011;6:780–790. doi: 10.1093/infdis/jiq118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Burdo TH, Lo J, Abbara S, et al. Soluble CD163, a Novel Marker of Activated Macrophages, Is Elevated and Associated With Noncalcified Coronary Plaque in HIV-Infected Patients. J Infect Dis. 2011;8:1227–1236. doi: 10.1093/infdis/jir520. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Subramanian S, Tawakol A, Burdo TH, et al. Arterial inflammation in patients with HIV. JAMA. 2012;4:379–386. doi: 10.1001/jama.2012.6698. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Asmuth DM, Ma Z-M, Mann S, et al. Gastrointestinal-associated lymphoid tissue immune reconstitution in a randomized clinical trial of raltegravir versus non-nucleoside reverse transcriptase inhibitor-based regimens. AIDS. 2012;13:1625–1634. doi: 10.1097/QAD.0b013e3283546595. [DOI] [PubMed] [Google Scholar]
  • 29.Patterson KB, Prince HA, Stevens T, et al. Differential Penetration of Raltegravir throughout Gastrointestinal Tissue: Implications for Eradication and Cure. AIDS. 2013 doi: 10.1097/QAD.0b013e32835f2b49. in press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Nielsen MJ, Moller HJ, Moestrup SK. Hemoglobin and heme scavenger receptors. Antioxidants & Redox Signaling. 2010;2:261–273. doi: 10.1089/ars.2009.2792. [DOI] [PubMed] [Google Scholar]
  • 31.Kathiresan S, Gona P, Larson MG, et al. Cross-sectional relations of multiple biomarkers from distinct biological pathways to brachial artery endothelial function. Circulation. 2006;7:938–945. doi: 10.1161/CIRCULATIONAHA.105.580233. [DOI] [PubMed] [Google Scholar]
  • 32.Yeboah JMRLPTS, et al. COmparison of novel risk markers for improvement in cardiovascular risk assessment in intermediate-risk individuals. JAMA: The Journal of the American Medical Association. 2012;8:788–795. doi: 10.1001/jama.2012.9624. [DOI] [PMC free article] [PubMed] [Google Scholar]

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