Open Access

Changes in lipid profiles after switching to a protease inhibitor-containing cART - unfavourable effect of fosamprenavir in obese patients

European Journal of Medical Research201116:85

https://doi.org/10.1186/2047-783X-16-2-85

Received: 1 November 2010

Accepted: 1 November 2010

Published: 24 February 2011

Abstract

Objective

One focus in the medical care of HIV-infected patients today is cardiovascular risk reduction. Metabolic disturbances occur frequently in patients taking protease inhibitors (PI) and are a major risk factor for atherosclerosis. With few published head-to head studies substance-specific differences concerning metabolic effects are insufficiently defined. Therefore this cohort study directly compared the metabolic profiles of boosted atazanavir (ATV/r), fosamprenavir (FPV/r) and saquinavir (SQV/r).

Methods

Data from a cohort of 124 HIV patients initiating a boosted regimen with one of the PIs at the University of Munich (LMU) infectious diseases outpatient clinic were retrospectively analyzed. The main outcome measures were median absolute total cholesterol levels and median relative change of total cholesterol levels after six months of PI-therapy. A multivariate linear regression model was built to identify and control for potential confounders of the association between PI-therapy and serum cholesterol level.

Results

84 patients were treated with ATV/r, 23 patients received FPV/r and 17 patients SQV/r. Demographically the cohort constituted a representative sample of HIV-infected patients in Germany. There were no statistically significant differences between the comparison groups at baseline.

After six months of therapy median serum cholesterol in the ATV/r group dropped significantly from 204 mg/dl to 186 mg/dl, while in the FPV/r and SQV/r groups a rise in serum cholesterol levels was observed from 179 mg/dl to 204 mg/dl and from 173 mg/ddl to 209 mg/dl respectively. The multivariate linear regression model identified a significant interaction between BMI at baseline and treatment with FPV/r: patients with higher BMI showed more prominent increases in serum cholesterol while taking FPV/r compared to patients with lower BMI.

Conclusion

This cohort study demonstrated the most favourable impact on serum cholesterol levels and thus cardiovascular risk for ATV/r compared to FPV/r and SQV/r under real-life conditions. Given the statistical interaction detected between FPV/r and BMI further studies assessing metabolic profiles of different antiretroviral drugs in specific patient populations are urgently needed.

Keywords

HIVcARTprotease inhibitoratazanavirfosamprenavirsaquinavirlipidscholesteroltriglyceridesglucosemetabolismbody mass indexdyslipidemiaobesitycardiovascular riskmultivariate linear regressionstatistical interaction

Introduction and Objectives

Metabolic and cardiovascular health issues are becoming an increasing problem in Germany and other industrialized countries. Cardiovascular complications [18] now are among the leading causes of mortality in these countries [912].

Since the introduction of combination antiretroviral therapy (cART) mortality due to AIDS-defining illnesses has considerably decreased among people living with HIV/AIDS (PLHA), resulting in an increase of life expectancy to almost that of the general population [13, 14]. Therefore non-HIV-related causes of death, among them cardiovascular diseases, are becoming more relevant among PLHA [1417]. In addition, both HIV-infection itself [1821] and various antiretroviral drugs are also associated with increased cardiovascular risk [2224]. Elevated serum cholesterol has been shown to be a major cause for atherosclerosis in numerous studies [35, 8] and this association has also been confirmed in PLHA [25].

With a broad spectrum of antiretroviral drugs available, the focus of HIV therapy today lies on managing the patients' overall health situation, including metabolic and cardiovascular as well as quality of life issues [26]. Choosing antiretroviral drugs with a favourable metabolic profile is the primary specific intervention recommended to minimize the cardiovascular risk burden in HIV-patients even before identification of other modifiable cardiovascular risk factors potentially requiring drug therapy [27].

Protease inhibitors (PIs) are an essential part of modern cART and recommended as part of first-line HIV-therapy in different guidelines [2831]. However, unfavourable metabolic effects like elevation of serum lipids, impaired glucose tolerance, and increased risk of myocardial infarction have mainly been associated with this drug class [22, 24, 25, 3237]. The metabolic effects, especially the impact on serum lipids, is a class effect of PIs, however there seem to be substance- specific differences [24]. Thus, knowledge of the different metabolic profiles of the various PIs offers the possibility to optimize cART efficacy while keeping cardiovascular risk as low as possible. Several newer PIs show fewer metabolic side effects than have been observed for ritonavir-boosted lopinavir (LPV/r) or ritonavir (RTV) in therapeutic dosage [24, 3235, 3841]. Especially atazanavir (ATV) so far has shown a relatively favourable lipid profile [4245]. Saquinavir (SQV) as well has been observed to have few negative effects on the serum lipids [4649]. Data about the metabolic properties of fosamprenavir (FPV) are conflicting [5052].

Currently available data do not allow for a concluding assessment of the differences of the various PIs' effect on lipid and glucose metabolism and cardiovascular risk. Moreover, to date little is known about the various interactions of the PIs' metabolic effects with other patient characteristics such as body mass index (BMI), blood pressure, or smoking habits, which influence a patient's metabolic situation as well.

The aims of the present study were to directly compare the three PIs ATV, FPV and SQV, for which favourable metabolic profiles have been observed in different studies, with regard to their influence on metabolic parameters affecting cardiovascular risk as well as assessing possible interactions of the PIs with patient characteristics like BMI and blood pressure.

Methods and Statistics

This study took place at the Ludwig-Maximilians-University of Munich infectious diseases outpatient clinic. The University of Munich ethics committee approved the study. All HIV-infected patients seen between January 1, 2000 and March 31, 2008 were screened for their eligibility. All adult patients initiating therapy with ATV 300 mg qd, FPV 700 mg bid, or SQV 1000 mg bid within a RTV-boosted cART-regimen (ATV/r, FPV/r or SQV/r) for whom a follow-up of at least six months was available were included into the analysis. Double-PI therapy and changes of the cART regimen as well as initiation or changes of a lipid-lowering medication during the first six months of PI-therapy were not allowed.

Patients were usually seen at the clinic every three months. At these visits serum levels of cholesterol, triglycerides, and glucose, CD4 cell count and viral load, as well as blood pressure, weight, and current medication were routinely documented. All demographic, HIV-related, and metabolic data were extracted from patient files and the outpatient clinic database.

Cardiovascular risk was calculated for each patient at baseline and after 6 months of PI therapy using the HeartScore-tool developed by the European Society of Cardiology in the version specific for Germany [2, 3, 53]. The Score value is calculated on the basis of age, gender, smoking behaviour, systolic blood pressure and serum cholesterol level and describes the risk of a fatal cardiovascular event within the next 10 years. According to European Joint Task Force guidelines a patient is considered at high cardiovascular risk if the score is above 5% [3, 54].

This study was carried out as a retrospectively analyzed cohort study, the main outcome measures were median absolute total cholesterol levels and median relative change of total cholesterol levels after 6 months of PI-therapy.

To identify potential confounding variables influencing the association between PI-therapy and serum cholesterol level a multivariate linear regression model was designed. The outcome variable was serum cholesterol level after 6 months of therapy with one of the PIs, main predictor variables were PI used and baseline cholesterol. Collinearity was ruled out by assessing variance inflation. Potential confounding covariates known from the literature were assessed, variables shown to be confounders were included in the final model. All parameters in the final model were tested for two-way interaction.

All statistical analyses were performed using SPSS™ software, version 15.0 (SPSS, Munich, Germany). For comparison of the cohorts Kruskal-WallisH-test and Chi2-test were used, as applicable. Intragroup analyses of the changes of parameters over time were performed using the Wilcoxon-test for metric variables and the McNemar-test for categorical variables.

Results

Patients and Baseline Characteristics

During the study period 444 patients starting a PI containing regimen were seen at the outpatient clinic, 124 patients met eligibility criteria for inclusion into the analysis. Of these, 84 patients (68%) initiated therapy with ATV/r, 23 patients (19%) initiated therapy with FPV/r, and 17 patients (14%) with SQV/r. The remaining patients were excluded because they were treated with a different PI (199 patients), received a double-PI-regimen or an unusual dosage of the PI (87 patients), or insufficient follow-up was available (34 patients). Additional follow up documentation of 24 months after starting PI-therapy was available for 86 patients. The baseline demographic and clinical characteristics of the patients are shown in Table 1. There were no significant differences with regard to demographic characteristics, HIV disease characteristics, antiretroviral therapy, or cardiovascular risk factors between the 3 groups receiving different Pi-based cART at baseline.
Table 1

Baseline demographic and clinical characteristics of patients starting a new PI-based cART regimen

  

Starting therapy with

ATV/r

FPV/r

SQV/r

pa

Characteristic

      

Number of patients

 

N

84

23

17

 

DEMOGRAPHIC CHARACTERISTICS

      

Male patients

 

n (%)

62 (74)

18 (78)

14 (82)

0.72

Age (years)

 

Median

43

44

41

0.69

  

(IQR b )

(37; 54)

(38; 50)

(35; 50)

 

Caucasian patients

 

n (%)

66 (79)

21 (91)

14 (82)

0.71

HIV risk category

MSM c

n (%)

41 (49)

14 (61)

12 (70)

 
 

heterosexual

n (%)

17 (20)

4 (17)

2 (12)

0.76

 

Other

n (%)

26 (31)

5 (22)

3 (18)

 

HIV DISEASE CHARACTERISTICS

      

Duration of known HIV infection (years)

 

Median

8.8

10.5

8.8

0.41

  

(IQR)

(5.4; 12.8)

(6.3; 15.3)

(4.7; 10.5)

 

Previous AIDS

 

n (%)

34 (40)

8 (35)

9 (53)

0.53

CD4 cell count (cells/μl blood)

 

Median

343

320

262

0.59

  

(IQR)

(221; 496)

(138; 595)

(81; 551)

 

Patients with undetectable viral load d

 

n (%)

37 (44)

8 (35)

6 (35)

0.73

ANTIRETROVIRAL THERAPY

      

Previous cART exposure

 

n (%)

79 (94)

20 (87)

16 (94)

0.50

Previous PI exposure

 

n (%)

55 (66)

15 (65)

14 (82)

0.40

Cumulative cART exposure (years)

 

Median

6,9

7,3

5,2

0.30

  

(IQR)

(3.2; 8.7)

(3.8; 9.6)

(3.5; 8.7)

 

previous cART

no cART

n (%)

15 (18)

8 (35)

1 (6)

0.35

 

other PI

n (%)

40 (48)

11 (48)

10 (59)

0.69

 

NRTI and/or NNRTI only

n (%)

29 (35)

4 (17)

6 (35)

0.12

CARDIOVASCULAR RISK FACTORS

      

BMI

 

Median

23,7

23,6

21,5

0.50

  

(IQR)

(21.3; 25.4)

(20.5; 25.1)

(19.3; 23.2)

 

Current smoker

 

n (%)

39 (46)

9 (39)

6 (35)

0.23

Arterial hypertension e

 

n (%)

35 (42)

11 (48)

6 (35)

0.73

Diabetes mellitus

 

n (%)

7 (8)

1 (4)

0 (0)

0.40

Current lipid-lowering therapy

 

n (%)

5 (6)

2 (9)

2 (12)

0.67

a : Kruskal-Wallis-H-test for metric variables, Chi2 -test for categorical variables; p-value for inter-group comparisons

b : inter quartile range

c : Men having sex with men

d : less than 50 copies per ml of plasma

e : diastolic blood pressure ≥90mmHg and/or systolic blood pressure ≥140mmHg or antihypertensive medication

Metabolic Profile and Cardiovascular Risk

The changes of different metabolic parameters examined during the first 6 months after initiating therapy with one of the PIs are shown in Table 2.
Table 2

Changes in the metabolic and cardiovascular profile during PI-therapy

PI group

 

ATV/r

FPV/r

SQV/r

p-valuea

Characteristic

     

Number of patients

 

84

23

17

 

Serum cholesterol

    at baseline [mg/dl]

Median

204

179

173

 
 

(IQR)

(159; 251)

(148; 217)

(143; 221)

0.19

    at month 6 [mg/dl]

Median

186

204

209

 
 

(IQR)

(157; 228)

(177; 284)

(164; 278)

0.055

    relative change at month 6

% (Median)

-6

+21

+8

0.0002

Serum triglycerides

    at baseline [mg/dl]

Median

187

136

205

 
 

(IQR)

(113; 334)

(87; 289)

(143; 366)

0.20

    at month 6 [mg/dl]

Median

186

169

218

 
 

(IQR)

(119; 280)

(122; 239)

(120; 342)

0.90

Serum glucose

    at baseline [mg/dl]

Median

90

87

89

 
 

(IQR)

(82; 101)

(83; 97)

(78; 99)

0.70

    at month 6 [mg/dl]

Median

91

90

97

 
 

(IQR)

(83; 101)

(83; 103)

(89; 118)

0.17

High cardiovascular risk b

    at baseline

n (%)

23 (27)

2 (9)

2 (12)

0.088

    at month 6

n (%)

20 (24)

3 (13)

3 (18)

0.50

a : Kruskal-Wallis-H-test for metric variables; p-value for inter-group comparisons

b : risk of developing a fatal cardiovascular event over the next ten years >5%, according to the HeartScore [2, 3, 53]

At the time of starting PI-based therapy, the median serum cholesterol level was highest at 204 mg/dl in the ATV/r-group. In the FPV/r- and SQV/r-groups the median values were 179 mg/dl and 173 mg/dl, respectively. The differences between the groups were not statistically significant (p = 0.19; inter-group comparison). After six months of therapy the median serum cholesterol level significantly decreased to 186 mg/dl in the patients taking ATV/r (p = 0.009; intragroup comparison). The median value rose to 204 mg/dl in the patients taking FPV/r (p = 0.03; intragroup comparison), and to 209 mg/dl in the patients taking SQV/r (p = 0.15; intra-group comparison). At month 6 of therapy there was a trend towards a lower median serum cholesterol in patients taking ATV/r (p = 0.055; inter-group comparison) (Figure 1). Regarding the relative change of the serum cholesterol levels at month 6 compared to baseline values, a significant difference between the PI groups was seen (p = 0.0002; inter-group comparison): In the ATV/r-group serum cholesterol had decreased by -6%, in contrast to both the FPV/r- and SQV/r-group, in which a respective increase of +21% (p = 0.0002; comparison of ATV/r and FPV/r) and +6% (p = 0.016; comparison of ATV/r and SQV/r) was observed. No significant difference could be found between the patients taking FPV/r and those taking SQV/r (p = 0.28; comparison of FPV/r and SQV/r) (Table 2).
Figure 1

Change of serum cholesterol levels in the course of the therapy. In the boxplot, the central line represents the median, the box denotes the inter quartile range, the whiskers encompass the 1,5- fold inter quartile range, outliers are not indicated.

In the further course between 6 and 24 months after initiating PI therapy cholesterol levels in patients on ATY/r were continuously lower than in the other groups. In the ATV/r-group the median serum cholesterol at month 24 was 198 mg/dl, in the FPV/r- and SQV/r-group the values were 228 mg/dl and 214 mg/dl, respectively.

The median serum triglyceride level at baseline in the FPV/r-group was at 136 mg/dl and thus in the favourable range below 150 mg/dl [3, 4, 55, 56]. In the patients starting therapy with ATV/r and SQV/r the median baseline values for the triglycerides were 187 mg/dl and 205 mg/dl, respectively. After the first 6 months of PI therapy the median value in the ATV/r- collective remained basically unchanged at 187 mg/dl whereas an increase to 169 mg/dl in the FPV/r group and an increase to 218 mg/dl in the SQV/r group were observed. However, neither the inter-group differences nor the changes over time within the different PI groups were statistically significant (Table 2).

Median serum glucose values showed no significant variation between the comparison groups and no relevant changes over the time course of the therapy with the PIs. The majority of the patients in all three groups had normal fasting serum glucose levels below 110 mg/dl throughout the study period (Table 2).

At baseline the proportion of patients with high cardiovascular risk, i.e., a HeartScore-risk of >5% [2, 3, 54], was highest at 27% in the group starting therapy with ATV/r. In the FPV/r-group and SQV/r- group the prevalence was 9% and 12%, respectively. After 6 months of PI therapy the proportion of high- risk patients was slightly lower in the ATV/r-group at 24%. In the other groups a trend towards a rise to 13% and 18% could be observed in the patients taking FPV/r and SQV/r, respectively (Table 2).

There were no statistically significant differences between the PIs regarding their efficacy in suppressing HIV. Less than half of the patients in all PI-groups had a non-detectable viral load at baseline. After 6 months of therapy the proportion had risen to >70%. The median CD4-cell count was between 262 and 343 cells/μl at baseline and rose to values between 292 and 400 cells /μl after 6 months of therapy.

Multivariate Linear Regression

Among the covariates tested only BMI at baseline was identified as confounding the association between PI group (ATV/r vs. SQV/r vs. FPV/r) and cholesterol level at month 6 and therefore was included in the final model. In addition, significant interaction between treatment with FPV/r and BMI at baseline was detected (Table 3).
Table 3

Multivariate linear regression model for serum cholesterol levels after 6 months of PI-therapy

Parameter

Coefficient

p-value

R2 a

intercept

59.9

0.071

 

Therapy using ATV/r

reference

  

Therapy using SQV/r

34.5

0.007

 

Therapy using FPV/r

-83.8

0.15

 

FPV/r×BMI at baseline

5.6

0.021

 

BMI at baseline

1.5

0.26

 

Serum cholesterol at baseline

0.5

< 0.001

 
   

0.49

a: Coefficient of determination of the regression model

The effect of this interaction can be illustrated by dichotomizing BMI at the median value of 23.5 kg/m2 (Table 4). While for patients with higher BMI values the use of FPV/r was associated with the highest cholesterol levels after 6 months, for patients with lower BMI predicted serum cholesterol in the FPV/r group was identical to those in the SQV/r group (all compared to therapy with ATV/r).
Table 4

Influence of BMI stratum on the effect of FPV/r on the serum cholesterol level after 6 months of PI therapy

Parameter

Coefficient

p-value

ATV/r

reference

 

SQV/r

36.6

0.004

FPV/r

  

    for BMI >23.5 kg/m 2

58.1

<0.001

    for BMI ≤23.5 kg/m 2

36.6

0.023

Serum cholesterol at baseline

0.5

<0.001

BMI of >23.5 kg/m 2 at baseline

15.0

0.13

Discussion

In this cohort study comparing the effect of cART either containing ATV/r, SQV/r, or FPV/r on serum cholesterol levels after 6 months of therapy under real-life conditions we demonstrated the lowest serum cholesterol levels in the ATV/r treated patients. This is even more remarkable considering that at baseline the median serum cholesterol level was highest in the ATV/r group. During the first 6 months of therapy the median serum cholesterol significantly decreased by 18 mg/dl in the ATV/r-group (p = 0.009), whereas in the FPV/r and SQV/r-groups an increase in median cholesterol was observed. Thus, in contrast to baseline the serum cholesterol profile at month 6 was most favourable in the patients taking ATV/r. The observed differences of >20 mg/dl in median serum cholesterol between the groups appear clinically relevant, especially in patients at a high cardiovascular risk, even though predefined statistical significance was missed for the bivariate inter-group comparison (p = 0.055), likely due to the differences in baseline median cholesterol values between the PI groups. When adjusting for different baseline levels by comparing the median relative changes in serum cholesterol during the first 6 months of therapy the difference between the PI-groups is significant (p = 0.0002) and strongly in favour of therapy with ATV/r. Therefore our study confirms the favourable influence of ATV/r on serum cholesterol described in current literature [4245, 52, 5760].

For SQV/r several trials have indicated a comparatively beneficial influence on serum cholesterol [24, 39, 46, 47], an effect not replicated in our study where treatment with SQV/r was associated with a modest increase in serum cholesterol.

In contrast to the Alert-study [52], our findings confirm the rather disadvantageous effect of FPV/r on serum cholesterol [27] found in several other studies [50, 51, 61]. However, considering the interaction identified in the multivariate linear regression model, this unfavourable effect of FPV/r on serum cholesterol may not be universal but seems to mainly affect patients with a higher BMI. This suggests that while it might be prudent to avoid therapy with FPV/r in obese patients, FPV/r may be a relatively safe treatment option in patients with normal weight.

With serum cholesterol being one of the main established cardiovascular risk factors [35, 8], calculated cardiovascular risk within the first 6 months of PI therapy parallelled the changes in cholesterol values: in the group taking ATV/r the proportion of patients with high cardiovascular risk decreased, whereas in the patients using FPV/r and SQV/r the proportion with high cardiovascular risk increased.

The HeartSCORE used here for determining the patients' cardiovascular risk has not been validated in HIV-infected populations so far. However, its advantage over other available cardiovascular risk calculators is its validation specifically in European populations. Furthermore, based on parameters readily available through measurements in clinical routine, it describes the risk of a fatal cardiovascular event rather than other, less clearly defined endpoints [2].

It is well known that atherosclerosis is most strongly associated with levels of LDL-cholesterol [4, 26], which were not available for many patients in this study. However, there is a robust correlation between LDL-cholesterol and total serum cholesterol, therefore the latter can well serve as a surrogate variable for determining a patient's cardiovascular risk profile [4].

Another limitation of the study is the relatively small sample size and the unbalanced distribution of patients between the comparison groups, potentially leading to an impairment of statistical significance of some of the analyses. However, the group of patients examined here can be regarded as a representative sample of HIV-infected individuals in Germany based on their demographic characteristics [62]. Furthermore, different univariate and multivariate approaches to analyze the effect of the examined PIs on serum cholesterol yielded consistent results, demonstrating the robustness of the statistical analyses. An immanent limitation of a non-interventional, retrospectively analyzed study is the potential problem of missing data and incomplete data standardization. This was minimized by the use of different data sources including chart documentation of regular clinic visits scheduled every three months and a standardized patient database established at the clinic since 1997. In addition, a main strength of this study is the analysis of data derived from a real-life patient population. In this way clinical reality can be better represented than by the highly selected patient populations used for interventional studies.

In conclusion, in a real-life patient population we confirmed that treatment of HIV infection with a ATV/r based regimen had a more favourable impact on serum cholesterol levels and therefore cardiovascular risk compared to SQV/r or FPV/r based regimens. FPV/r was associated with the highest increase in serum cholesterol, specifically in overweight patients, whereas its effects on cholesterol may be comparable to SQV/r in patients with a BMI ≤23,5 kg/m2. In the light of growing interest in personalized medicine [63] and with obesity and cardiovascular disease getting ever more prevalent [4, 6468] this may be an example of how to better tailor cART regimens considering a patient's metabolic and cardiovascular profile.

Based on these results more and larger studies should be undertaken to specifically address the multiple interdependencies between effects of cART and patient characteristics affecting cardiovascular risk.

Abbreviations

ATV/r: 

boosted atazanavir

BMI: 

body mass index

cART: 

combination antiretroviral therapy

FPV/r: 

boosted fosamprenavir

LPV/r: 

boosted lopinavir

PI: 

protease inhibitor

PLHA: 

people living with HIV/AIDS

RTV: 

ritonavir

SQV/r: 

boosted saquinavir.

Authors’ Affiliations

(1)
Infektionsabteilung der Medizinischen Poliklinik, Campus Innenstadt, Ludwig-Maximilians-Universität

References

  1. Assmann G, Schulte H, Cullen P, Seedorf U: Assessing risk of myocardial infarction and stroke: new data from the Prospective Cardiovascular Munster (PROCAM) study. European Journal of Clinical Investigation 2007,37(12):925–32. 10.1111/j.1365-2362.2007.01888.xPubMedView ArticleGoogle Scholar
  2. Conroy RM, Pyorala K, Fitzgerald AP, et al.: Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. European Heart Journal 2003,24(11):987–1003. 10.1016/S0195-668X(03)00114-3PubMedView ArticleGoogle Scholar
  3. Graham I, Atar D, Borch-Johnsen K, et al.: European guidelines on cardiovascular disease prevention in clinical practice: executive summary. European Heart Journal 2007,28(19):2375–414.PubMedView ArticleGoogle Scholar
  4. Adult Treatment Panel III: Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Paneflll). JAMA 2001,285(19):2486–97. 10.1001/jama.285.19.2486View ArticleGoogle Scholar
  5. Lloyd-Jones DM, Wilson PWF, Larson MG, et al.: Lifetime Risk of Coronary Heart Disease by Cholesterol Levels at Selected Ages. Archives of Internal Medicine 2003,163(16):1966–72. 10.1001/archinte.163.16.1966PubMedView ArticleGoogle Scholar
  6. Bhargava A: A longitudinal analysis of the risk factors for diabetes and coronary heart disease in the Framingham Offspring Study. Popul Health Metr 2003,1(3):1–16.Google Scholar
  7. Greenland P, Knoll MD, Stamler J, et al.: Major Risk Factors as Antecedents of Fatal and Nonfatal Coronary Heart Disease Events. JAMA Vol. 290: Am Med Assoc 2003, 891–7.Google Scholar
  8. Lewington S, Whitlock G, Clarke R, et al.: Blood cholesterol and vascular mortality by age, sex, and blood pressure: a meta-analysis of individual data from 61 prospective studies with 55,000 vascular deaths. Lancet 2007,370(9602):1829–39.PubMedView ArticleGoogle Scholar
  9. Niederlaender E: Causes of death in the EU. A report by the EU's statistical office, Eurostat European Communities 2006.Google Scholar
  10. Kung HC, Hoyert DL, Xu J, Murphy SL: Deaths: final data for 2005. Natl Vital Stat Rep 2008,56(10):1–120.PubMedGoogle Scholar
  11. Bundesamt S: Todesursachen - Sterbefalle insgesamt 2007 nach den 10 haufigsten Todesursachen. 2008. [http://www.destatis.de/jetspeed/portal/cms/Sites/destatis/Internet/DE/Content/Statistiken/Gesundheit/Todesursachen/Tabellen/Content75/SterbefaelleInsgesamt,templateId=renderPrint.psml]Google Scholar
  12. Bundesamt S: Todesursachen in Deutschland - Gestor- bene in Deutschland an ausgewahlten Todesursachen - 2006. Statistisches Bundesamt 2006.Google Scholar
  13. Detels R, Munoz A, McFarlane G, et al.: Effectiveness of potent antiretroviral therapy on time to AIDS and death in men with known HIV infection duration. Multicenter AIDS Cohort Study Investigators. JAMA 1998,280(17):1497–503. 10.1001/jama.280.17.1497PubMedView ArticleGoogle Scholar
  14. Bhaskaran K, Hamouda O, Sannes M, et al.: Changes in the risk of death after HIV seroconversion compared with mortality in the general population. JAMA 2008,300(1):51–9. 10.1001/jama.300.1.51PubMedView ArticleGoogle Scholar
  15. Lewden C, May T, Rosenthal E, et al.: Causes de décès en France en 2005 des adultes infectées par le VIH et évolution par rapport à 2000. Bulletin épidémiologique hebdomadaire 2006 2006, (48):379–82.Google Scholar
  16. Palella FJ, Baker RK, Moorman AC, et al.: Mortality in the highly active antiretroviral therapy era: changing causes of death and disease in the HIV outpatient study. J Acquir Immune Defic Syndr 2006,43(1):27–34. 10.1097/01.qai.0000233310.90484.16PubMedView ArticleGoogle Scholar
  17. Crum NF, Riffenburgh RH, Wegner S, et al.: Comparisons of causes of death and mortality rates among HIV- infected persons: analysis of the pre-, early, and late HAART (highly active antiretroviral therapy) eras. J Acquir Immune Defic Syndr 2006,41(2):194–200. 10.1097/01.qai.0000179459.31562.16PubMedView ArticleGoogle Scholar
  18. El-Sadr WM, Lundgren JD, Neaton JD, et al.: CD4+ Count-guided interruption of antiretroviral treatment. New England Journal of Medicine 2006,355(22):2283–96.PubMedView ArticleGoogle Scholar
  19. Phillips AN, Carr A, Neuhaus J, et al.: Interruption of antiretroviral therapy and risk of cardiovascular disease in persons with HIV-1 infection: exploratory analyses from the SMART trial. Antivir Ther 2008,13(2):177–87.PubMedGoogle Scholar
  20. Grunfeld C, Pang M, Doerrler W, Shigenaga JK, Jensen P, Feingold KR: Lipids, lipoproteins, triglyceride clearance, and cytokines in human immunodeficiency virus infection and the acquired immunodeficiency syndrome. J Clin Endocrinol Metab 1992,74(5):1045–52. 10.1210/jc.74.5.1045PubMedGoogle Scholar
  21. Neumann T, Miller M, Esser S, Gerken G, Erbel R: Arteriosklerose bei HIV-positiven Patienten. Zeitschrift für Kardiologie 2002,91(11):879–88. 10.1007/s00392-002-0855-6PubMedView ArticleGoogle Scholar
  22. Friis-Moller N, Weber R, Reiss P, et al.: Cardiovascular disease risk factors in HIV patients--association with antiretroviral therapy. Results from the DAD study. AIDS 2003,17(8):1179–93. 10.1097/00002030-200305230-00010PubMedView ArticleGoogle Scholar
  23. Friis-Moller N, Sabin CA, Weber R, et al.: Combination antiretroviral therapy and the risk of myocardial infarction. N Engl J Med 2003,349(21):1993–2003.PubMedView ArticleGoogle Scholar
  24. Fellay J, Boubaker K, Ledergerber B, et al.: Prevalence of adverse events associated with potent antiretroviral treatment: Swiss HIV Cohort Study. Lancet 2001,358(9290):1322–7. 10.1016/S0140-6736(01)06413-3PubMedView ArticleGoogle Scholar
  25. Friis-Moller N, Reiss P, Sabin CA, et al.: Class of antiretroviral drugs and the risk of myocardial infarction. N Engl J Med 2007,356(17):1723–35.PubMedView ArticleGoogle Scholar
  26. Baigent C, Keech A, Kearney PM, et al.: Efficacy and safety of cholesterol-lowering treatment: prospective metaanalysis of data from 90,056 participants in 14 randomised trials of statins. Lancet 2005,366(9493):1267–78.PubMedView ArticleGoogle Scholar
  27. Lundgren JD, Battegay M, Mallon P, et al.: European AIDS Clinical Society (EACS) guidelines: Prevention and management of non-infectious co-morbidities in HIV, version 5. 2009. [http://wwweuropeanaidsclinicalsocietyorg/guideline-spdf/2_Non_Infectious_Co_Morbidities_in_HIVpdf]Google Scholar
  28. Clumeck N, Dedes N, Pozniak A, Raffi F: the EACS Executive Committee. European AIDS Clinical Society (EACS) guidelines for the clinical management and treatment of HIV-infected adults, version 5. 2009. [http://www.europeanaidsclinicalsociety.org/Guidelines/index.htm]Google Scholar
  29. Centers for Disease Control and Prevention. About BMI for Adults. Healthy Weight 2009. [http://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html]
  30. Thompson MA, Aberg JA, Cahn P, et al.: Antiretroviral treatment of adult HIV infection: 2010 recommendations of the International AIDS Society-USA panel. JAMA 2010,304(3):321–33. 10.1001/jama.2010.1004PubMedView ArticleGoogle Scholar
  31. Deutsche AIDS Gesellschaft, Österreichische AIDS Gesellschaft Deutsch-Österreichische Leitlinien zur antiretroviralen Therapie der HIV-1-Infektion Last access on September 9, 2010 [http://www.daignet.de/site-content/hiv-therapie/leitlinien-1/resolveuid/4e09c351567524bfd215f4d46a9b6f5a]
  32. Purnell JQ, Zambon A, Knopp RH, et al.: Effect of ritonavir on lipids and post-heparin lipase activities in normal subjects. AIDS 2000,14(1):51–7. 10.1097/00002030-200001070-00006PubMedView ArticleGoogle Scholar
  33. Sullivan AK, Nelson MR: Marked hyperlipidaemia on ritonavir therapy. AIDS 1997,11(7):938–9.PubMedGoogle Scholar
  34. Martinez E, Domingo P, Galindo MJ, et al.: Risk of metabolic abnormalities in patients infected with HIV receiving antiretroviral therapy that contains lopinavir-ritonavir. Clin Infect Dis 2004,38(7):1017–23. 10.1086/382531PubMedView ArticleGoogle Scholar
  35. Walmsley S, Bernstein B, King M, et al.: Lopinavir-ritonavir versus nelfinavir for the initial treatment of HIV infection. N Engl J Med 2002,346(26):2039–46. 10.1056/NEJMoa012354PubMedView ArticleGoogle Scholar
  36. Dube MP, Stein JH, Aberg JA, et al.: Guidelines for the evaluation and management of dyslipidemia in human immunodeficiency virus (HIV)-infected adults receiving antiretroviral therapy: recommendations of the HIV Medical Association of the Infectious Disease Society of America and the Adult AIDS Clinical Trials Group. Clin Infect Dis 2003,37(5):613–27. 10.1086/378131PubMedView ArticleGoogle Scholar
  37. Tsiodras S, Mantzoros C, Hammer S, Samore M: Effects of protease inhibitors on hyperglycemia, hyperlipidemia, and lipodystrophy: a 5-year cohort study. Arch Intern Med 2000,160(13):2050–6. 10.1001/archinte.160.13.2050PubMedView ArticleGoogle Scholar
  38. Periard D, Telenti A, Sudre P, et al.: Atherogenic dyslipidemia in HIV-infected individuals treated with protease inhibitors. The Swiss HIV Cohort Study. Circulation 1999,100(7):700–5.PubMedView ArticleGoogle Scholar
  39. Fontas E, van Leth F, Sabin CA, 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(6):1056–74. 10.1086/381783PubMedView ArticleGoogle Scholar
  40. Lee GA, Seneviratne T, Noor MA, et al.: The metabolic effects of lopinavir/ritonavir in HIV-negative men. AIDS 2004,18(4):641–9. 10.1097/00002030-200403050-00008PubMed CentralPubMedView ArticleGoogle Scholar
  41. Lafeuillade A, Hittinger G, Philip G, Lambry V, Jolly P, Poggi C: Metabolic evaluation of HIV-infected patients receiving a regimen containing lopinavir/ritonavir (Kaletra). HIV Clinical Trials 2004,5(6):392–8. 10.1310/Q0TG-0V50-9JML-638UPubMedView ArticleGoogle Scholar
  42. Gatell J, Salmon-Ceron D, Lazzarin A, et al.: Efficacy and safety of atazanavir-based highly active antiretroviral therapy in patients with virologic suppression switched from a stable, boosted or unboosted protease inhibitor treatment regimen: the SWAN Study (AI424–097) 48-week results. Clin Infect Dis 2007,44(11):1484–92. 10.1086/517497PubMedView ArticleGoogle Scholar
  43. Molina JM, Andrade-Villanueva J, Echevarria J, et al.: Once-daily atazanavir/ritonavir versus twice-daily lopinavir/ritonavir, each in combination with tenofovir and emtricitabine, for management of antiretroviral-naive HIV-1-infected patients: 48 week efficacy and safety results of the CASTLE study. Lancet 2008,372(9639):646–55. 10.1016/S0140-6736(08)61081-8PubMedView ArticleGoogle Scholar
  44. Mobius U, Lubach-Ruitman M, Castro-Frenzel B, et al.: Switching to atazanavir improves metabolic disorders in antiretroviral-experienced patients with severe hyperlipidemia. J Acquir Immune Defic Syndr 2005,39(2):174–80.PubMedGoogle Scholar
  45. Cahn PE, Gatell JM, Squires K, et al.: Atazanavir-a once-daily HIV protease inhibitor that does not cause dyslipidemia in newly treated patients: results from two randomized clinical trials. J Int Assoc Physicians AIDS Care (Chic Ill) 2004,3(3):92–8. 10.1177/154510970400300304View ArticleGoogle Scholar
  46. Segerer S, Bogner JR, Walli R, Loch O, Goebel FD: Hyperlipidemia under treatment with proteinase inhibitors. Infection 1999,27(2):77–81. 10.1007/BF02560501PubMedView ArticleGoogle Scholar
  47. Dragsted UB, Gerstoft J, Pedersen C, et al.: Randomized trial to evaluate indinavir/ritonavir versus saquinavir/ritonavir in human immunodeficiency virus type 1-infected patients: the MaxCmin1 Trial. J Infect Dis 2003,188(5):635–42. 10.1086/377288PubMedView ArticleGoogle Scholar
  48. Dragsted UB, Gerstoft J, Youle M, et al.: A randomized trial to evaluate lopinavir/ritonavir versus saquinavir/ritonavir in HIV-1-infected patients: the MaxCmin2 trial. Antivir Ther 2005,10(6):735–43.PubMedGoogle Scholar
  49. Manfredi R, Chiodo F: Disorders of lipid metabolism in patients with HIV disease treated with antiretroviral agents: frequency, relationship with administered drugs, and role of hypolipidaemic therapy with bezafibrate. J Infect 2001,42(3):181–8. 10.1053/jinf.2001.0829PubMedView ArticleGoogle Scholar
  50. Eron J, Yeni P, Gathe J, et al.: The KLEAN study of fosamprenavir-ritonavir versus lopinavir-ritonavir, each in combination with abacavir-lamivudine, for initial treatment of HIV infection over 48 weeks: a randomized non-inferiority trial. Lancet 2006,368(9534):476–82. 10.1016/S0140-6736(06)69155-1PubMedView ArticleGoogle Scholar
  51. Gathe JC, 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(11):1529–37. 10.1097/01.aids.0000131332.30548.92PubMedView ArticleGoogle Scholar
  52. Smith KY, Weinberg WG, Dejesus E, et al.: Fosamprenavir or atazanavir once daily boosted with ritonavir 100 mg, plus tenofovir/emtricitabine, for the initial treatment of HIV infection: 48-week results of ALERT. AIDS Res Ther 2008, 5: 5. 10.1186/1742-6405-5-5PubMed CentralPubMedView ArticleGoogle Scholar
  53. European Society of Cardiology HeartScore Programme 2009. Last access on February 27, 2010 [http://www.heartscore.org/Pages/welcome.aspx]
  54. De Backer G, Ambrosioni E, Borch-Johnsen K, et al.: European guidelines on cardiovascular disease prevention in clinical practice. Third Joint Task Force of European and Other Societies on Cardiovascular Disease Prevention in Clinical Practice. European Heart Journal 2003,24(17):1601–10. 10.1016/S0195-668X(03)00347-6PubMedView ArticleGoogle Scholar
  55. Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C: Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation 2004,109(3):433–8. 10.1161/01.CIR.0000111245.75752.C6PubMedView ArticleGoogle Scholar
  56. Alberti KG, Zimmet P, Shaw J: The metabolic syndrome- -a new worldwide definition. Lancet 2005,366(9491):1059–62. 10.1016/S0140-6736(05)67402-8PubMedView ArticleGoogle Scholar
  57. Johnson M, Grinsztejn B, Rodriguez C, et al.: Atazanavir plus ritonavir or saquinavir, and lopinavir/ritonavir in patients experiencing multiple virological failures. AIDS 2005,19(7):685–94. 10.1097/01.aids.0000166091.39317.99PubMedView ArticleGoogle Scholar
  58. Johnson M, Grinsztejn B, Rodriguez C, et al.: 96-week comparison of once-daily atazanavir/ritonavir and twice daily lopinavir/ritonavir in patients with multiple virologic failures. AIDS 2006,20(5):711–8. 10.1097/01.aids.0000216371.76689.63PubMedView ArticleGoogle Scholar
  59. Mallolas J, Podzamczer D, Milinkovic A, et al.: Efficacy and safety of switching from boosted lopinavir to boosted atazanavir in patients with virological suppression receiving a LPV/r-containing HAART the ATAZIP study. J Acquir Immune Defic Syndr 2009,51(1):29–36. 10.1097/QAI.0b013e31819a226fPubMedView ArticleGoogle Scholar
  60. Wood R, Phanuphak P, Cahn P, et al.: Long-term efficacy and safety of atazanavir with stavudine and lamivudine in patients previously treated with nelfinavir or atazanavir. J Acquir Immune Defic Syndr 2004,36(2):684–92. 10.1097/00126334-200406010-00005PubMedView ArticleGoogle Scholar
  61. Rodriguez-French A, Boghossian J, Gray GE, et al.: The NEAT study: a 48-week open-label study to compare the antiviral efficacy and safety of GW433908 versus nelfinavir in antiretroviral therapy-naive HIV-1-infected patients. J Acquir Immune Defic Syndr 2004,35(1):22–32. 10.1097/00126334-200401010-00003PubMedView ArticleGoogle Scholar
  62. Robert Koch-Institut: HIV/AIDS in Deutschland -Eckdaten, Epidemiologische Kurzinformation des Robert Koch-Instituts, Stand: Ende. 2008. [http://www.rki.de/cln_100/nn_195960/DE/Content/InfAZ/H/HIVAIDS/Epidemiologie/Daten_und_Berichte/EckdatenDeutschland,templateId=raw,property=publicationFile.pdf/EckdatenDeutschland.pdf]Google Scholar
  63. Institute for Pharmacogenomics and Individualized Therapy Homepage of the Institute for Pharmacogenomics and Individualized Therapy 2007. Last access on December 10, 2009 [http://www.ipit.unc.edu/]
  64. Hauner H, Buchholz G, Hamann B, Koletzko B: Prävention und Therapie der Adipositas - Evidenzbasierte Leitlinie Version 2007. 2007.Google Scholar
  65. Gesundheitsberichtserstattung des Bundes. Cholesterinmesswerte im Bundes-Gesundheitssurvey 1998 in Deutschland [http://www.gbe-bund.de/gbe10/abrechnung.prc_abr_test_logon?p_uid=gastg&p_aid=&p_knoten=FID&p_sprache=D&p_suchstring=4228::Cholesterin]
  66. Gesundheitsberichtserstattung des Bundes Body Mass Index (BMI) der erwachsenen Bevölkerung 1998. Last access on August 30, 2009 [http://www.gbe-bund.de/gbe10/abrechnung.prc_abr_test_logon?p_uid=gastg&p_aid=&p_knoten=FID&p_sprache=D&p_suchstring=8397::Body-Mass-Index]
  67. Gesundheitsberichtserstattung des Bundes Bluthoch- druck - Gesundheit in Deutschland 2006. Last access on August 30, 2009 [http://www.gbe-bund.de/gbe10/abrechnung.prc_abr_test_logon?p_uid=gastg&p_aid=&p_knoten=FID&p_sprache=D&p_suchstring=10700::Hypertonie]
  68. Diabetes Deutschland. Diabetes: Themen und Fakten - Die aktuelle Situation Diabetes: Themen und Fakten 2007. Last access on August 30, 2009 [http://www.diabetes-deutschland.de/aktuellesituation.html]

Copyright

© I. Holzapfel Publishers 2011

Advertisement