Abstract

With the development of highly active antiretroviral therapy, chronic kidney disease has become a prominent cause of morbidity in individuals infected by HIV. Because serum creatinine has significant limitations in this specific population, cystatin C is emerging as a promising biomarker for both the evaluation of glomerular filtration rate (GFR) and the detection of drug-induced kidney injury. Along with renal function, serum cystatin C concentration is associated with several biological parameters such as C-reactive protein, HIV viral load and CD4+ cells count. All these determinants of cystatin C are, however, more or less independent of GFR. Studies evaluating the accuracy of cystatin C for estimating GFR in the setting of HIV infection are scarce and methodology is often questionable (lack of reference method or inadequate statistical analyses). Thus far, data are insufficient to encourage the use of cystatin C or cystatin C-based equations to estimate GFR in the HIV-infected population. Further research is needed to explore the clinical utility of cystatin C in this setting. Beyond the use of cystatin C as a GFR marker, future studies will have to evaluate its role as a predictor of patient outcome, particularly in regard to cardiovascular morbi-mortality.

Introduction

The United Nations Programme on HIV/AIDS estimated that 33.3 million people were living with a HIV infection in 2009 [ 1 ]. The development of highly active antiretroviral therapy (HAART) has resulted in improved survival among HIV-seropositive individuals. With advancing age and HAART-related metabolic effects (diabetes [ 2 ], hypertension [ 3 ], and dyslipidaemia [ 4 ]), chronic kidney disease (CKD) has become one of the major comorbidities in HIV-seropositive individuals [ 5 ]. The real prevalence of CKD in HIV patients is still, however, questioned. In a retrospective chart review, Fernando et al. [ 6 ] found evidence of CKD in 24% of the patients and CKD Stage 3 [estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m 2 ] or higher in 10% of the patients. Overton et al. [ 7 ] found a prevalence of Stage 3 CKD of 7.4% in HIV-infected subjects versus 2.1% in controls. Crum-Cianflone et al. [ 8 ] found a lower prevalence of CKD Stage 3 (3%). Importantly, in the latter study, patients were relatively young, had no comorbidities and no specific evaluation for proteinuria. Campbell et al. [ 9 ] found similar results with a prevalence of 2.4% for Stage 3 CKD.

Risk factors for CKD in HIV-infected patients vary according to the studies but include female sex, black race [ 10 ], AIDS, low CD4+ lymphocyte count, older age, hepatitis C virus (HCV) co-infection, hypertension, diabetes mellitus [ 6 , 7 ] and injecting drug use [ 11 ]. Exposure to HAART is also associated with an increased risk for CKD, tenofovir, didanosine, atazanavir, lopinavir and indinavir being the most frequently incriminated anti-retroviral drugs [ 12 , 13 ].

Moreover, similar to the general population, CKD is associated with an increased risk of both mortality [ 14 , 15 ] and cardiovascular events (CVE) [ 16 ] in HIV-seropositive individuals. In HIV-infected women, Szczech et al. [ 17 ] observed that proteinuria was associated with an increased risk of AIDS-defining illness {hazard ratio (HR) = 1.37 [95% confidence interval (95% CI) 1.01–1.81]}. Proteinuria and elevated creatinine level were also associated with an increased risk of mortality with a HR of 1.35 (95% CI 1.01–1.81) and 1.72 (95% CI 1.09–2.70), respectively. These associations were curiously stronger than the association of low CD4+ lymphocyte count with AIDS-defining illness and death in this cohort [ 17 ]. In multivariate analysis, the odds ratio for CVE was 1.2 (95% CI 1.1–1.4) for every 10 mL/min/1.73 m 2 decrease in eGFR. These results can, however, be criticized because it has been shown in the general population that the association between glomerular filtration rate (GFR) and CVE is a graded, but not a linear one [ 18 ]. Because of the growing prevalence and burden of CKD in HIV-infected patients, screening, prevention and management of CKD have become a key challenge in this population. In 2005, the Infectious Diseases Society of America published guidelines for CKD screening in HIV-infected patients. According to these recommendations, kidney function should be assessed at initial diagnosis by measuring proteinuria and estimating GFR. In cases where CKD risk factors are present, kidney function should be assessed every 6 months. Utilization of creatinine-based estimates, and particularly the Modification Diet in Renal Disease (MDRD) study equation, is recommended [ 19 , 20 ]. This latest recommendation has, however, to be challenged by the various limitations inherent to the use of serum creatinine as a marker of GFR. Variations in generation, secretion and extra-renal elimination of creatinine have been extensively described in different populations [ 21 ]. This holds particularly true for HIV-infected patients for whom many specific factors are likely to impact the relation between serum creatinine and GFR. As a result, serum cystatin C is being touted as an alternative to serum creatinine with the potential to more accurately account for different degrees of renal impairment [ 22 , 23 ]. Cystatin C level has also been shown in the general population to be more closely associated than creatinine (and creatinine-based equations) with CVE, all-cause mortality and incident end-stage renal disease [ 24–26 ]. The mechanism of this association between cystatin C and outcomes—CVE and mortality—is not fully understood. It might, at least in part, have to do with the non-GFR determinants of cystatin C level, but this is still subject to debate. Whatever the mechanisms underlying this association, cystatin C can also be seen as a potential biomarker that may better predict outcomes in the high-risk HIV patient [ 27 ].

Serum creatinine: an imperfect marker of renal function in HIV-infected individuals

Creatinine is freely filtered by the glomerulus and secreted by the proximal tubular cells. Creatinine level can be affected at three levels: creatinine generation, tubular secretion and extra-renal elimination. Creatinine is the catabolic end product of creatine. Ninety-eight percent of creatinine is generated from muscle. Serum creatinine concentration is thus highly dependent on muscle mass [ 28 , 29 ]. In HIV-infected patients, creatinine generation is expected to decrease for numerous reasons (see Table 1 ). HIV infection induces modifications of the body composition. For example, HIV-infected men have a lower fat-free mass compared to matched healthy controls [ 30 , 31 ]. HIV infection can also lead to wasting syndromes responsible for severe depletion in lean and fat tissue [ 32 ]. Similarly, HIV-infected subjects are more often malnourished than is the general population [ 33 ]. By further modifying body composition, lipodystrophy induced by HAART may alter the association between serum creatinine and GFR.

Table 1.

Principal factors influencing serum creatinine level in HIV-infected subjects

 Effects on creatinine HIV 
Lean mass Increase in creatinine production Decrease in lean mass: AIDS wasting syndrome, mitochondrial toxicity of HAART 
Dietary intake Increase in creatinine production Strong prevalence of malnutrition in HIV-infected subjects 
Liver disease Decrease in creatine production Prevalence of HCV infection in HIV-infected subjects around 30% 
African American ethnicity Increase in creatinine production  
Reduction of the tubular excretion of creatinine 
Trimethoprim Reduction of the tubular excretion of creatinine Pneumocystis jiroveci infections prophylaxis  
 Effects on creatinine HIV 
Lean mass Increase in creatinine production Decrease in lean mass: AIDS wasting syndrome, mitochondrial toxicity of HAART 
Dietary intake Increase in creatinine production Strong prevalence of malnutrition in HIV-infected subjects 
Liver disease Decrease in creatine production Prevalence of HCV infection in HIV-infected subjects around 30% 
African American ethnicity Increase in creatinine production  
Reduction of the tubular excretion of creatinine 
Trimethoprim Reduction of the tubular excretion of creatinine Pneumocystis jiroveci infections prophylaxis  

Additionally, creatinine production in patients with liver disease is decreased [ 34 ]. Co-infection with viral hepatitis is frequent (roughly one-third of patients are co-infected with HCV or hepatitis B virus in Western countries) [ 35 , 36 ]. In HIV-infected individuals, HCV co-infection is associated with a decrease in serum creatinine level [ 37 , 38 ]. In addition, liver cirrhosis is associated with malnutrition and protein depletion [ 39 ]. Given that HCV is another risk for CKD, early diagnosis remains critical in these patients. Besides the problem of creatinine generation, change in creatinine metabolism might also explain the difficulty to rely on serum creatinine for estimating GFR in HIV patients. For instance, the use of trimethoprim/sulfamethoxazole (TMP/SMX) is recommended in primary and secondary prophylaxis of infections due to Toxoplasma gondii and Pneumocystis jiroveci [ 40 , 41 ]. Specifically, TMP inhibits creatinine secretion by the tubules, inducing an increase in serum creatinine independent of any decrease in GFR [ 42 ]. Serum creatinine increase after trimethoprim intake varies from 15 to 30% [ 43 , 44 ].

Given the numerous factors specific to HIV infection that may influence creatinine level, two recent US cohort studies have compared serum creatinine in HIV and control non-HIV individuals. In the Fat Redistribution And Metabolic change (FRAM) study, 519 HIV-positive patients were compared with 290 healthy controls from the Coronary Artery Risk Development in Young Adults (CARDIA) study [ 45 ]. There was no significant difference in creatinine level between the two groups. However, the two groups were different for several characteristics—notably a higher prevalence of HCV infection, hypertension, diabetes and proteinuria in the HIV-infected populations—which might have masked a lower creatinine level. In the second study, 250 HIV-infected subjects from the Nutrition for Healthy Living (NFHL) cohort were compared with 2628 persons matched for age, race and sex from the National Health and Nutrition Examination Survey (NHANES) [ 38 ]. Serum creatinine level was found to be significantly lower in the NFHL cohort. In the same line, Mauss et al. [ 46 ] compared kidney function between 261 HIV-seropositive patients naïve to anti-retroviral therapy with 193 healthy controls. While they found no significant difference between the two groups for serum creatinine, they did observe a trend towards an association between lower serum creatinine and HIV seropositivity after adjustment for sex, age and body mass index [ 46 ]. In a retrospective study, Overton et al. [ 7 ] compared prevalence of kidney function between 845 HIV-infected subjects with 845 HIV-negative subjects from the NHANES cohort. The prevalence of chronic renal failure (eGFR <60 mL/min/1.73 m 2 ) and serum creatinine level were significantly greater in HIV-infected subjects than in controls (7.4 versus 2.1%, 1.13 versus 0.95 mg/dL, respectively). HIV-infected subjects had more risk factors for CKD, such as hypertension and hepatitis infection and more often had a history of injecting drug use (IDU). These studies yielded different results and drawing definitive conclusion are thus difficult. Obviously, the principal limitation of these studies is the absence of GFR measurement by a gold standard method. Moreover, due to the great prevalence of viral hepatitis and IDU in the HIV-infected population, matching controls with HIV-infected subjects, remains difficult.

Serum cystatin C in HIV-positive subjects: the ideal GFR marker?

Cystatin C is a low-molecular weight protein produced by all nucleated cells, freely filtered in the glomerulus and catabolyzed by tubular cells [ 47 ]. Only small amounts are found in urine in the physiological state. Limitations of serum creatinine due to creatinine extra-renal excretion or tubular secretion are thus not present with cystatin C. However, it remains important to study muscular mass and other factors, which could influence cystatin C levels independently of GFR. Two important studies in HIV-negative subjects have examined the factors that affect serum levels of cystatin C, independently of GFR. They both identified age, gender, and C-reactive protein (CRP) level in serum [ 48 , 49 ] (see Table 2 ). In one, current smoking was also associated with an increase in serum cystatin C level. In another study, MacDonald et al. [ 51 ] demonstrated by measuring GFR by inulin clearance and evaluating body composition by dual X-ray absorptiometry that cystatin C is also affected by lean mass. However, the magnitude of the associations with height and weight is greater for serum creatinine than for serum cystatin C [ 49 ]. Cystatin C is thus clearly far less dependent on muscular mass than creatinine. Moreover, in a population-based study (Multi-Ethnic Study of Atherosclerosis, MESA Study), Kramer et al. showed no significant difference in mean cystatin C levels between African Americans and Caucasians [ 52 ] although serum creatinine strongly varies according to ethnicity (also probably reflecting difference in muscular mass according to ethnicity) [ 53 ]. The influence of these factors can be, once again, critical in HIV-infected subjects.

Table 2.

Factors influencing serum cystatin C level identified in HIV-negative subjects a

 Study population GFR evaluation method Mean GFR Factors associated with cystatin C (after adjustment with GFR or 24-h creatinine clearance) Effects on cystatin C level 
Knight et al. 2004 [ 48 ]  8058 subjects from Groningen, the Netherlands 95% Caucasian Age from 28 to 75 years 4% of patients with diabetes 24-h urine creatinine clearance 102 ± 27 mL/min Age Male gender, weight, height Current cigarette smoking CRP level Increase IncreaseIncreaseIncrease 
   
   
   
Stevens et al. 2009 [ 49 ]   MDRD study ( N = 1085)  Iothalamate urinary clearance  48 mL/min/1.73 m 2 (15–95)  Age Decrease 
AASK ( N = 1205)  Female gender Decrease 
CSG ( N = 266)  Height, weight, BMI Increase 
NephroTest ( N = 438)  EDTA urinary clearance Urine protein Increase 
All patients with CKD Stages 2–5 53.5% blacks 13.9% patients with diabetes Diabetes Increase 
CRP level White blood cell count Serum albumin Increase Increase Decrease 
   
   
Mathisen et al. [ 50 ]   Tromsø population survey ( N = 1627)  Iohexol clearance  90 mL/min/1.73 m 2 Decrease in physical activity Increase 
Current smoking Increase 
BMI Increase 
LDL-cholesterol Decrease 
HDL-cholesterol Increase 
Triglycerides Increase 
 Study population GFR evaluation method Mean GFR Factors associated with cystatin C (after adjustment with GFR or 24-h creatinine clearance) Effects on cystatin C level 
Knight et al. 2004 [ 48 ]  8058 subjects from Groningen, the Netherlands 95% Caucasian Age from 28 to 75 years 4% of patients with diabetes 24-h urine creatinine clearance 102 ± 27 mL/min Age Male gender, weight, height Current cigarette smoking CRP level Increase IncreaseIncreaseIncrease 
   
   
   
Stevens et al. 2009 [ 49 ]   MDRD study ( N = 1085)  Iothalamate urinary clearance  48 mL/min/1.73 m 2 (15–95)  Age Decrease 
AASK ( N = 1205)  Female gender Decrease 
CSG ( N = 266)  Height, weight, BMI Increase 
NephroTest ( N = 438)  EDTA urinary clearance Urine protein Increase 
All patients with CKD Stages 2–5 53.5% blacks 13.9% patients with diabetes Diabetes Increase 
CRP level White blood cell count Serum albumin Increase Increase Decrease 
   
   
Mathisen et al. [ 50 ]   Tromsø population survey ( N = 1627)  Iohexol clearance  90 mL/min/1.73 m 2 Decrease in physical activity Increase 
Current smoking Increase 
BMI Increase 
LDL-cholesterol Decrease 
HDL-cholesterol Increase 
Triglycerides Increase 
a

NephroTest, the NephroTest initiative is a prospective hospital-based ongoing cohort that began in 2000, enrolling patients with all diagnoses of CKD Stages 2–5 referred for extensive work-up by two nephrology departments. Data included in this study were collected between 2000 and 2004; AASK, African American Study of Kidney Diseases and Hypertension; BMI, body mass index; CSG, Collaborative Study Group: Captopril in Diabetic Nephropathy Study; HDL, high-density lipoprotein; LDL, low-density lipoprotein.

The association of cystatin C to CRP is potentially problematic in HIV patients. Markers of inflammation are indeed chronically elevated in HIV-positive adults. High-sensitivity (hs) CRP was found to be 55% higher in HIV-positive patients from the Strategies for Management of Anti Retroviral Therapy (SMART) study as compared to controls from the MESA and CARDIA studies [ 54 ]. Likewise, cystatin C was found to be 27.2% higher in the SMART study group. The association between hs-CRP and cystatin C level is, however, inconsistent. In the Jaroszewicz study [ 55 ], while CRP and cystatin C levels were significantly greater in HIV-positive subjects, no significant correlation between CRP and cystatin C was found. Moreover, Estrella et al. [ 56 ] published a cross-sectional study with 783 HIV-infected patients from the Multicenter AIDS Cohort Study (MACS) and 150 HIV-negative subjects. eGFR based on cystatin C was lower in the HIV+ group than in the controls, while eGFR based on creatinine was not different. eGFR based on creatinine and cystatin C were both influenced by age, AIDS condition and proteinuria. In the adjusted model, eGFR based on cystatin C was not influenced by CRP level. The precise role played by other confounders (like renal insufficiency or smoking status) in the relation between serum cystatin C and CRP requires further evaluation because CKD status, per se , is associated with ‘microinflammation’.

Non-GFR factors potentially influencing cystatin C levels have also been studied in the specific population of HIV patients. HIV replication may affect serum cystatin C level. In 922 patients from the FRAM study cohort, Choi et al. [ 27 ] observed that HIV-1 viral load was higher in the group of patients with an eGFR based on cystatin C (eGFRcys) level <60 mL/min/1.73 m 2 than in the group of patients with a greater eGFRcys. This association was not observed in another study with subjects from the same cohort or in the SMART trial study cohort [ 45 , 54 ]. The SMART trial was designed to compare two strategies of anti-retroviral treatment [ 57 ]. In the first arm (drug conservation), treatment was guided by immunological response and HAART was stopped when CD4+ lymphocyte count was >350/mm 3 . In the second arm (viral suppression), HAART was maintained [ 58 ]. The interruption of HAART in the SMART study was associated with an increase in HIV-1 viral load and cystatin C [ 59 ]. A higher viral load at baseline and an increase in HIV-1 viral load during follow-up were associated with an increase in cystatin C level in the FRAM study [ 60 ]. In the MACS cohort, a decrease in eGFRcys is associated with an increase in HIV viral load [ 56 ]. In a study of validation of estimated renal function by cystatin C-based equations, higher HIV-1 viral load was associated with higher cystatin C level independently of measured GFR. This analysis was performed in only 15 patients in whom GFR was measured by 51 Cr-ethylenediaminetetraacetic acid ( 51 Cr-EDTA) clearance [ 61 ]. Because viral load is also a strong predictor of GFR and because GFR was only estimated, not measured, in most of these studies, it cannot be concluded from these studies that the potential effect of viral load on cystatin C level is really independent of GFR variation.

Other possible factors related to HIV infection might affect cystatin C level: HIV-infected macrophages producing less cystatin C than uninfected ones [ 62 ] and CD4+ lymphocyte count (most studies showing an association between a lower count of CD4+ cells and a higher cystatin C level [ 27 , 38 , 45 , 63 ]). Here again, some discrepancies exist across studies. In the SMART trial, cystatin C at baseline was not correlated to CD4+ cells, but an increase in cystatin C during follow-up was associated with a lower CD4+ count [ 59 ]. Two others studies did not show a significant correlation between CD4+ cells and cystatin C level [ 55 , 64 ]. Once again, advanced HIV disease (high viral load and low lymphocyte CD4+ count) is associated with kidney impairment [ 17 , 65 ]. Given the imprecision of actual GFR measurement both in HIV and non-HIV studies, even adjusting to GFR and finding a residual association of risk factor with cystatin C do not automatically make it a non-GFR determinant. Although more studies are needed to evaluate the impact of HIV viral load and CD4+ count on its level, cystatin C might be a good marker of GFR in advanced HIV disease and might detect subclinical kidney impairment, which occurs in this situation.

Serum creatinine versus serum cystatin C in HIV-positive subjects: and the winner is…

Assessment of GFR in HIV-infected patients, as in other patients, had two different purposes. One is to provide the most possible early diagnosis of CKD. The second one is to detect decrease in kidney function over time (the slope of GFR) [ 66 ]. The principal cohort studies comparing cystatin C and creatinine in HIV patients and control subjects are presented in Table 3 . In most of them, serum creatinine level was not different or lower in the study group than in the control groups, whereas serum cystatin C was most often higher in the study group. Using eGFR based on cystatin C, the prevalence of GFR <60 mL/min/1.73 m 2 is greater than using the MDRD equation, varying from 5 to 15.2% versus from 1 to 2.4% [ 38 , 46 , 56 ], respectively. However, all these studies have an important limitation: the absence of GFR measurement by a gold standard method that can serve as a reference (the so-called ‘true GFR’). Because of this fundamental limitation, they do not ultimately permit conclusions on the superiority of cystatin C over serum creatinine for estimating GFR.

Table 3.

Major cohort studies of cystatin C in HIV-infected subjects

 Cohort of HIV-infected subjects Control cohort Differences between HIV-positive cohort and controls Results Risk factors for higher serum cystatin C level in HIV-participants 
Odden et al. 2007 [ 45 ]   The FRAM study ( n = 519)   CARDIA study ( n = 290)  Controls were older, more women in control cohort, BMI higher in control cohort, smoking status, hypertension, dyslipidemia, proteinuria, HCV infection higher in FRAM study cohort Serum cystatin C higher in the FRAM study cohort The prevalence of cystatin C >1 mg/L was 31% in the HIV-infected participants and only 4% in controls Lower HDL-c level, higher uric acid level, proteinuria, hypertension, higher CRP 
Between the ages of 33 and 45 years Current smoking CD4 lymphopenia Co-infection HCV, current heroin use, longer duration of efavirenz and indinavir use 
No difference in serum creatinine level between HIV-infected partcipants and controls 
Mauss et al. 2008 [ 46 ]   Treatment naïve, Caucasian patients ( n = 261)   Healthy volunteers ( n = 193)  More males in the study group Mean eGFRcreat by MDRD higher in the study group Positive correlation between cystatin C level and HIV viral load 
Older age, higher BMI in control group  Mean eGFRcys a lower in the study group  
CRP level, HCV co-infection, smoking status were not reported in the patient characteristics Prevalence of CKD (Stages 2 and more) in the study group with MDRD = 23%, with eGFRcys = 41% 
Jones et al. 2008 [ 38 ]   The NFHL cohort ( n = 250)   The NHANES ( n = 2628)  More African American subjects in NFHL, greater prevalence of hypertension, diabetes, liver disease in NFHL, higher CRP level in NFHL, lower albumin level in NFHL Serum creatinine level lower in NFHL, serum cystatin C level higher in NFHL cohort HCV infection, liver disease, lower CD4+ lymphocyte count, HIV viral load, current injecting drug use, lower serum albumin level 
Prevalence of eGFRcys b <60 mL/min/1.73 m 2 = 15.2%  
Prevalence of eGFRcreat <60 mL/min/1.73 m 2 using MDRD = 2.4%  
Neuhaus et al. 2010 [ 54 ]   SMART ( n = 494)   MESA study ( n = 5386)  Older age, more women in control cohort, more black subjects in SMART, lower BMI in SMART study, prevalence of dyslipidemia, current smoking, diabetes, hypertension greater in SMART Cystatin C was 27.2% higher in SMART study participants  
Estrella et al. 2011 [ 56 ]   MACS ( n = 783)   Healthy volunteers ( n = 150)  Hepatitis C infection status, liver enzyme level, CRP and urine protein to creatinine ratio greater in the HIV+ group, BMI, serum albumin level greater in controls, trimethoprim use in HIV+ group eGFRcys C was reduced in HIV+ groups, no differences for eGFRcreat, discordance between eGFRcys C and eGFRcreat varies with the level of kidney function HCV infection, alkaline phosphatase level, HIV viral load 
Overton et al. 2011 [ 63 ]   SUN c ( n = 670)  None   Prevalence of CKD (eGFR MDRD <60 mL/min/1.73 m 2 ) 3.3%, prevalence of cystatin C >1 mg/L 18%  Older age, HCV infection, smoking tobacco, tenofovir use, microalbuminuria, lower cystatin C was associated with undetectable viral load and HAART duration 
 Cohort of HIV-infected subjects Control cohort Differences between HIV-positive cohort and controls Results Risk factors for higher serum cystatin C level in HIV-participants 
Odden et al. 2007 [ 45 ]   The FRAM study ( n = 519)   CARDIA study ( n = 290)  Controls were older, more women in control cohort, BMI higher in control cohort, smoking status, hypertension, dyslipidemia, proteinuria, HCV infection higher in FRAM study cohort Serum cystatin C higher in the FRAM study cohort The prevalence of cystatin C >1 mg/L was 31% in the HIV-infected participants and only 4% in controls Lower HDL-c level, higher uric acid level, proteinuria, hypertension, higher CRP 
Between the ages of 33 and 45 years Current smoking CD4 lymphopenia Co-infection HCV, current heroin use, longer duration of efavirenz and indinavir use 
No difference in serum creatinine level between HIV-infected partcipants and controls 
Mauss et al. 2008 [ 46 ]   Treatment naïve, Caucasian patients ( n = 261)   Healthy volunteers ( n = 193)  More males in the study group Mean eGFRcreat by MDRD higher in the study group Positive correlation between cystatin C level and HIV viral load 
Older age, higher BMI in control group  Mean eGFRcys a lower in the study group  
CRP level, HCV co-infection, smoking status were not reported in the patient characteristics Prevalence of CKD (Stages 2 and more) in the study group with MDRD = 23%, with eGFRcys = 41% 
Jones et al. 2008 [ 38 ]   The NFHL cohort ( n = 250)   The NHANES ( n = 2628)  More African American subjects in NFHL, greater prevalence of hypertension, diabetes, liver disease in NFHL, higher CRP level in NFHL, lower albumin level in NFHL Serum creatinine level lower in NFHL, serum cystatin C level higher in NFHL cohort HCV infection, liver disease, lower CD4+ lymphocyte count, HIV viral load, current injecting drug use, lower serum albumin level 
Prevalence of eGFRcys b <60 mL/min/1.73 m 2 = 15.2%  
Prevalence of eGFRcreat <60 mL/min/1.73 m 2 using MDRD = 2.4%  
Neuhaus et al. 2010 [ 54 ]   SMART ( n = 494)   MESA study ( n = 5386)  Older age, more women in control cohort, more black subjects in SMART, lower BMI in SMART study, prevalence of dyslipidemia, current smoking, diabetes, hypertension greater in SMART Cystatin C was 27.2% higher in SMART study participants  
Estrella et al. 2011 [ 56 ]   MACS ( n = 783)   Healthy volunteers ( n = 150)  Hepatitis C infection status, liver enzyme level, CRP and urine protein to creatinine ratio greater in the HIV+ group, BMI, serum albumin level greater in controls, trimethoprim use in HIV+ group eGFRcys C was reduced in HIV+ groups, no differences for eGFRcreat, discordance between eGFRcys C and eGFRcreat varies with the level of kidney function HCV infection, alkaline phosphatase level, HIV viral load 
Overton et al. 2011 [ 63 ]   SUN c ( n = 670)  None   Prevalence of CKD (eGFR MDRD <60 mL/min/1.73 m 2 ) 3.3%, prevalence of cystatin C >1 mg/L 18%  Older age, HCV infection, smoking tobacco, tenofovir use, microalbuminuria, lower cystatin C was associated with undetectable viral load and HAART duration 
a

eGFRcys (mL/min) = 74 835/[cystatin C (mg/L) 1.333 ].

b

eGFRcys(mL/min/1.73 m 2 ) = 767 (cystatin C −1.18 ) [ 22 ].

c

Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy.

The interest of cystatin C to follow the GFR slopes (longitudinal follow-up) and to detect a decrease in GFR is not well known in the HIV population. In other specific populations of patients, cystatin C outperformed creatinine to detect a decrease in GFR as in a cohort of diabetics [ 67 ].

Another challenge is the diagnosis of a subclinical HAART-related kidney injury. Some commonly prescribed antiretroviral therapies (e.g. tenofovir) can induce proximal tubular injury leading to Fanconi syndrome. In this situation, filtered cystatin C, which is not reabsorbed by the tubule, is excreted in the urine. For this reason, urinary cystatin C is thought to be a valuable biomarker for detecting anti-retroviral tubular toxicity [ 68 ].

Up to now, only four studies on cystatin C in HIV-infected subjects evaluated agreement between estimates of GFR based on cystatin C and measured GFR. They are summarized in Table 4 .

Table 4.

Comparison of the four studies about the predictive performance of cystatin C in estimation of GFR in HIV-infected subjects a

 N patients  GFR measurement eGFRcys C equation eGFRcreat Results 
Barraclough et al. 2009 [ 69 ]  27 99 Tc-DTPA clearance   eGFR = 86.7/cysC − 4.2 b MDRD, CG eGFRcys less accurate than eGFRcreat 
Beringer et al. 2010 [ 70 ]  22 Clearance of iothalamate  eGFR = 127.7 × cysC −1.17 × age −0.13 × (0.91 if female) × (1.06 if African American)  MDRD, CG No statistically significant differences 
eGFRcys C,creat = 177.6 × Creat −0.65 × cysC −0.57 × age −0.20 × 0.82 if female and/or 1.11 if African American c 
Bonjoch et al. 2010 [ 61 ]  15 51 Cr-EDTA clearance  CysC alone, no equation MDRD, CG, CKD-EPI CysC well correlated with isotopic GFR 
van Deventer et al. 2011 [ 71 ]  20 51 Cr-EDTA clearance   eGFR = 10 2.35 × 10 (CysC × −0.33) × 10 (−0.003 × age) MDRD, CKD-EPI eGFRcys C more accurate than eGFRcreat 
 N patients  GFR measurement eGFRcys C equation eGFRcreat Results 
Barraclough et al. 2009 [ 69 ]  27 99 Tc-DTPA clearance   eGFR = 86.7/cysC − 4.2 b MDRD, CG eGFRcys less accurate than eGFRcreat 
Beringer et al. 2010 [ 70 ]  22 Clearance of iothalamate  eGFR = 127.7 × cysC −1.17 × age −0.13 × (0.91 if female) × (1.06 if African American)  MDRD, CG No statistically significant differences 
eGFRcys C,creat = 177.6 × Creat −0.65 × cysC −0.57 × age −0.20 × 0.82 if female and/or 1.11 if African American c 
Bonjoch et al. 2010 [ 61 ]  15 51 Cr-EDTA clearance  CysC alone, no equation MDRD, CG, CKD-EPI CysC well correlated with isotopic GFR 
van Deventer et al. 2011 [ 71 ]  20 51 Cr-EDTA clearance   eGFR = 10 2.35 × 10 (CysC × −0.33) × 10 (−0.003 × age) MDRD, CKD-EPI eGFRcys C more accurate than eGFRcreat 
a

DTPA, Diethylene Triamine Pentaacetic Acid.

b

Macisaac RJ et al. [ 72 ].

c

Stevens LA et al. [ 22 ].

In a cohort of 27 patients receiving HAART, Barraclough et al. showed that the predictive performance of cystatin C or cystatin C-based equations to estimate GFR was inferior to the most used creatinine-based methods (the MDRD study equation and the Cockcroft–Gault formula). This result must, however, be questioned since cystatin C was measured in this study by a quantitative sandwich enzyme immunoassay which is clearly not recommended for measuring cystatin C [ 69 ]. Choice of the analytical method to measure cystatin C has indeed a major impact on the accuracy of the cystatin C-based equations [ 73 ].

In a cohort of 22 HIV patients, Beringer et al. [ 70 ] tested four different equations combining cystatin C and creatinine and found that they all provided a more accurate estimate as compared to the Cockcroft–Gault formula and an equation using cystatin C alone. All these equations underestimated GFR measured by iothalamate. The degree of underestimation of GFR with cystatin C was greater in patients with detectable HIV viral load than in patients with HIV viral load <400 copies/mL (−28.8 versus −14.3%). This difference was, however, not statistically significant.

Bonjoch et al. [ 61 ] reported that cystatin C shows the strongest correlation with measured GFR by an isotopic method ( 51 Cr-EDTA) compared to the Cockcroft–Gault, the Chronic Kidney Disease Epidemiology group (CKD-EPI), the MDRD study equations and the 24-h urine creatinine clearance. GFR was measured in 15 patients, all received HAART and 80% had no detectable viral load for an average of 90 months.

In a South African cohort, van Deventer et al. [ 71 ] developed a new prediction equation based on cystatin C for estimating GFR and compared performances of these new equations to existing creatinine-based equations (MDRD, CKD-EPI equations). One hundred black Africans patients were included, 50 in the development dataset and 50 in the validation dataset. In this cohort, GFR was measured by plasma clearance of 51 Cr-EDTA. Twenty patients from the cohort were HIV positive, overall this cystatin C-based equation was more precise than the creatinine-based equations, particularly in patients with GFR >60 mL/min/1.73 m 2 . In the subgroup of HIV-positive patients, this cystatin C-based equation proved to give the most accurate estimate as well. Although they all used ‘true GFR’ as a reference, these studies have in common one major limitation. They all included a very limited number of patients and should thus be seen as studies suggesting—not proving—the better performance of cystatin C. Furthermore, most of the patients included in these studies are Caucasian (except for the South African study), HAART-treated, and had an undetectable viral load and a CD4+ lymphocyte count >200/mm 3 . The performance of cystatin C may vary with the stage of HIV infection. With a predictive performance of 78% for MDRD, and the hypothesis of a predictive performance of 90% for cystatin C, >250 HIV-infected patients should be included in studies comparing MDRD and equations based on cystatin C.

Of note, equations used to estimate GFR vary from one study to another. Some authors used equations exclusively based on cystatin C, while others used equations combining cystatin C and creatinine or equation including other variables as age, gender and ethnicity. Up to now, data are clearly insufficient to determine which equation must be favoured in HIV patients, even if, in the general population, interesting results have been published with the equations combining serum creatinine and cystatin C [ 22 ]. The relative inaccuracy of estimates of GFR can be due to the imprecision of a single GFR measurement [ 74 , 75 ]. In these four studies, the assay for measuring cystatin C concentration was not the same and, as for serum creatinine, differences in assays and in cystatin C calibration can severely impact the accuracy of the equations. Further studies are needed with greater sample size and patients with AIDS or HAART-treated patients with low HIV viral load and high CD4+ cells count. Subjects of different ethnicities should also be more deeply studied.

Cystatin C in HIV-infected patients: a step towards outcome prediction?

In the general population, serum cystatin C is a predictor of CVE and of mortality [ 76 , 77 ]. Cystatin C is more strongly and more linearly associated than serum creatinine and creatinine-estimated GFR with all-cause mortality. In addition, cystatin C in combination with urine albumin-to-creatinine ratio and serum creatinine is an accurate predictor of mortality and CVE [ 25 ]. In patients with CKD, there is a trend for a stronger association between cystatin C and mortality than between measured GFR and mortality [ 26 ], thereby suggesting that cystatin C could predict cardiovascular outcomes, at least in part, independently of its association with GFR. In the SMART trial, hs-CRP, interleukin-6 and D-dimers were associated with all-cause mortality [ 78 ] and risk of opportunistic diseases [ 79 ]. Serum cystatin C was higher in the drug conservation arm [ 59 ] and the risk of cardiovascular disease was also higher in these patients [ 57 ]. HIV-infected subjects with high cardiovascular risk assessed by Framingham score had a higher serum cystatin C level [ 80 ]. GFR was found to be associated with all-cause mortality in HIV-infected subjects only when GFR was estimated from cystatin C and not from creatinine [ 27 ]. In the FRAM study, five-year mortality was better predicted by cystatin C-based estimates with an increase in absolute risk of roughly 10% for patients having an eGFR <60 mL/min/1.73 m 2 [ 27 ]. Taken together, these data suggest that cystatin C might be a valuable biomarker of cardiovascular risk assessment in HIV-seropositive patients. The interest in cystatin C to predict outcomes in HIV-infected subjects could justify by itself the use of cystatin C in the follow-up of these patients. However, several issues regarding the interest in cystatin C in HIV patients need to be addressed first. These are summarized in Table 5 .

Table 5.

Critical questions about the use of cystatin C in HIV-infected patients

The cost in comparison with the dosage of serum creatinine  
Could an early diagnosis of CKD-infected patients affect the outcome of the HIV infection?  
No eGFRcys equations are up to now validated in this population  
Should cystatin be used in combination with creatinine?  
Are the associations between non-HIV-related factors such as CRP level and smoking status only dependent on GFR?  
Do HIV viral load and lymphocytes CD4+ count affect cystatin C level only in association with kidney function?  
Do physicians need a novel GFR estimate or a predictor of clinical outcomes?  
Should physicians use the same GFR estimates for all HIV-infected patients?  
Is it feasible to monitor kidney function with such an assay in developing countries where the majority of HIV-infected people live?  
The cost in comparison with the dosage of serum creatinine  
Could an early diagnosis of CKD-infected patients affect the outcome of the HIV infection?  
No eGFRcys equations are up to now validated in this population  
Should cystatin be used in combination with creatinine?  
Are the associations between non-HIV-related factors such as CRP level and smoking status only dependent on GFR?  
Do HIV viral load and lymphocytes CD4+ count affect cystatin C level only in association with kidney function?  
Do physicians need a novel GFR estimate or a predictor of clinical outcomes?  
Should physicians use the same GFR estimates for all HIV-infected patients?  
Is it feasible to monitor kidney function with such an assay in developing countries where the majority of HIV-infected people live?  

Conclusions

Serum creatinine is far from being the ideal estimate of GFR in HIV-infected subjects. Cystatin C appears to be an alternative biomarker for GFR estimation. However, studies relying on a robust methodology and comparing estimates of GFR based on cystatin C with a reference GFR measurement are currently missing. These studies should calculate bias, precision and accuracy of the cystatin C-based equations and should determine which of the various equations available must be preferred. They should also include a sufficient number of patients, take into account the standardization of cystatin C measurement, and use appropriate statistical analysis (Bland and Altman analysis). In addition, cystatin C might serve as a predictor of all-cause mortality in HIV-infected patients. Whether this ability to predict patient outcome will extend to cardiovascular morbi-mortality and CKD progression still has to be evaluated. Given that HIV-infected patients are at increased risk of CVE, cystatin C might be particularly valuable in this population. Whatever the role played by cystatin C in the future for the care of HIV-infected patients, financial issues will have to be addressed. Standardized measurement of cystatin C will be very soon easily available but will remain expensive in comparison to the measurement of serum creatinine. The added value of cystatin C will have to be both clinically significant and economically acceptable for its widespread diffusion, particularly in developing countries.

Conflict of interest statement . None declared

References

1.
UNAIDS. Report on the Global AIDS Epidemic,
 , 
2010
 
2.
Koster
JC
Remedi
MS
Qiu
H
, et al.  . 
HIV protease inhibitors acutely impair glucose-stimulated insulin release
Diabetes
 , 
2003
, vol. 
52
 (pg. 
1695
-
1700
)
3.
Seaberg
EC
Muñoz
A
Lu
M
, et al.  . 
Association between highly active antiretroviral therapy and hypertension in a large cohort of men followed from 1984 to 2003
AIDS
 , 
2005
, vol. 
19
 (pg. 
953
-
960
)
4.
Riddler
SA
Li
X
Chu
H
, et al.  . 
Longitudinal changes in serum lipids among HIV-infected men on highly active antiretroviral therapy
HIV Med
 , 
2007
, vol. 
8
 (pg. 
280
-
287
)
5.
Schwartz
EJ
Szczech
LA
Ross
MJ
, et al.  . 
Highly active antiretroviral therapy and the epidemic of HIV+ end-stage renal disease
J Am Soc Nephrol
 , 
2005
, vol. 
16
 (pg. 
2412
-
2420
)
6.
Fernando
SK
Finkelstein
FO
Moore
BA
, et al.  . 
Prevalence of chronic kidney disease in an urban HIV infected population
Am J Med Sci
 , 
2008
, vol. 
335
 (pg. 
89
-
94
)
7.
Overton
ET
Nurutdinova
D
Freeman
J
, et al.  . 
Factors associated with renal dysfunction within an urban HIV-infected cohort in the era of highly active antiretroviral therapy
HIV Med
 , 
2009
, vol. 
10
 (pg. 
343
-
350
)
8.
Crum-Cianflone
N
Ganesan
A
Teneza-Mora
N
, et al.  . 
Prevalence and factors associated with renal dysfunction among HIV-infected patients
AIDS Patient Care STDS
 , 
2010
, vol. 
24
 (pg. 
353
-
360
)
9.
Campbell
LJ
Ibrahim
F
Fisher
M
, et al.  . 
Spectrum of chronic kidney disease in HIV-infected patients
HIV Med
 , 
2009
, vol. 
10
 (pg. 
329
-
336
)
10.
Lucas
GM
Lau
B
Atta
MG
, et al.  . 
Chronic kidney disease incidence, and progression to end-stage renal disease, in HIV-infected individuals: a tale of two races
J Infect Dis
 , 
2008
, vol. 
197
 (pg. 
1548
-
1557
)
11.
Vupputuri
S
Batuman
V
Muntner
P
, et al.  . 
The risk for mild kidney function decline associated with illicit drug use among hypertensive men
Am J Kidney Dis
 , 
2004
, vol. 
43
 (pg. 
629
-
635
)
12.
Mocroft
A
Kirk
O
Reiss
P
, et al.  . 
Estimated glomerular filtration rate, chronic kidney disease and antiretroviral drug use in HIV-positive patients
AIDS
 , 
2010
, vol. 
24
 (pg. 
1667
-
1678
)
13.
Tordato
F
Cozzi Lepri
A
Cicconi
P
, et al.  . 
Evaluation of glomerular filtration rate in HIV-1-infected patients before and after combined antiretroviral therapy exposure
HIV Med
 , 
2011
, vol. 
12
 (pg. 
4
-
13
)
14.
Estrella
MM
Parekh
RS
Abraham
A
, et al.  . 
The impact of kidney function at highly active antiretroviral therapy initiation on mortality in HIV-infected women
J Acquir Immune Defic Syndr
 , 
2010
, vol. 
55
 (pg. 
217
-
220
)
15.
Mayor
AM
Dworkin
M
Quesada
L
, et al.  . 
The morbidity and mortality associated with kidney disease in an HIV-infected cohort in Puerto Rico
Ethn Dis
 , 
2010
, vol. 
20
 (pg. 
S1-163
-
S1-167
)
16.
George
E
Lucas
GM
Nadkarni
GN
, et al.  . 
Kidney function and the risk of cardiovascular events in HIV-1-infected patients
AIDS
 , 
2010
, vol. 
24
 (pg. 
387
-
394
)
17.
Szczech
LA
Hoover
DR
Feldman
JG
, et al.  . 
Association between renal disease and outcomes among HIV-infected women receiving or not receiving antiretroviral therapy
Clin Infect Dis
 , 
2004
, vol. 
39
 (pg. 
1199
-
1206
)
18.
Go
AS
Chertow
GM
Fan
D
, et al.  . 
Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization
N Engl J Med
 , 
2004
, vol. 
351
 (pg. 
1296
-
1305
)
19.
Gupta
SK
Eustace
JA
Winston
JA
, et al.  . 
Guidelines for the management of chronic kidney disease in HIV-infected patients: recommendations of the HIV Medicine Association of the Infectious Diseases Society of America
Clin Infect Dis
 , 
2005
, vol. 
40
 (pg. 
1559
-
1585
)
20.
Estrella
MM
Fine
DM
Screening for chronic kidney disease in HIV-infected patients
Adv Chronic Kidney Dis
 , 
2010
, vol. 
17
 (pg. 
26
-
35
)
21.
Stevens
LA
Coresh
J
Greene
T
, et al.  . 
Assessing kidney function—measured and estimated glomerular filtration rate
N Engl J Med
 , 
2006
, vol. 
354
 (pg. 
2473
-
2483
)
22.
Stevens
LA
Coresh
J
Schmid
CH
, et al.  . 
Estimating GFR using serum cystatin C alone and in combination with serum creatinine: a pooled analysis of 3,418 individuals with CKD
Am J Kidney Dis
 , 
2008
, vol. 
51
 (pg. 
395
-
406
)
23.
Séronie-Vivien
S
Delanaye
P
Piéroni
L
, et al.  . 
Cystatin C: current position and future prospects
Clin Chem Lab Med
 , 
2008
, vol. 
46
 (pg. 
1664
-
1686
)
24.
Koenig
W
Twardella
D
Brenner
H
, et al.  . 
Plasma concentrations of cystatin C in patients with coronary heart disease and risk for secondary cardiovascular events: more than simply a marker of glomerular filtration rate
Clin Chem
 , 
2005
, vol. 
51
 (pg. 
321
-
327
)
25.
Peralta
CA
Shlipak
MG
Judd
S
, et al.  . 
Detection of chronic kidney disease with creatinine, cystatin C, and urine albumin-to-creatinine ratio and association with progression to end-stage renal disease and mortality
JAMA
 , 
2011
, vol. 
305
 (pg. 
1545
-
1552
)
26.
Menon
V
Shlipak
MG
Wang
X
, et al.  . 
Cystatin C as a risk factor for outcomes in chronic kidney disease
Ann Intern Med
 , 
2007
, vol. 
147
 (pg. 
19
-
27
)
27.
Choi
A
Scherzer
R
Bacchetti
P
, et al.  . 
Cystatin C, albuminuria, and 5-year all-cause mortality in HIV-infected persons
Am J Kidney Dis
 , 
2010
, vol. 
56
 (pg. 
872
-
882
)
28.
Perrone
RD
Madias
NE
Levey
AS
Serum creatinine as an index of renal function: new insights into old concepts
Clin Chem
 , 
1992
, vol. 
38
 (pg. 
1933
-
1953
)
29.
Delanaye
P
Cavalier
E
Maillard
N
, et al.  . 
La créatinine: d'hier à aujourd'hui [Creatinine: past and present]
Ann Biol Clin (Paris)
 , 
2010
, vol. 
68
 (pg. 
531
-
543
)
30.
Visnegarwala
F
Shlay
JC
Barry
V
, et al.  . 
Effects of HIV infection on body composition changes among men of different racial/ethnic origins
HIV Clin Trials
 , 
2007
, vol. 
8
 (pg. 
145
-
154
)
31.
Delpierre
C
Bonnet
E
Marion-Latard
F
, et al.  . 
Impact of HIV infection on total body composition in treatment-naive men evaluated by dual-energy X-ray absorptiometry comparison of 90 untreated HIV-infected men to 241 controls
J Clin Densitom
 , 
2007
, vol. 
10
 (pg. 
376
-
380
)
32.
McDermott
AY
Terrin
N
Wanke
C
, et al.  . 
CD4+ cell count, viral load, and highly active antiretroviral therapy use are independent predictors of body composition alterations in HIV-infected adults: a longitudinal study
Clin Infect Dis
 , 
2005
, vol. 
41
 (pg. 
1662
-
1670
)
33.
Nahlen
BL
Chu
SY
Nwanyanwu
OC
, et al.  . 
HIV wasting syndrome in the United States
AIDS
 , 
1993
, vol. 
7
 (pg. 
183
-
188
)
34.
Cocchetto
DM
Tschanz
C
Bjornsson
TD
Decreased rate of creatinine production in patients with hepatic disease: implications for estimation of creatinine clearance
Ther Drug Monit
 , 
1983
, vol. 
5
 (pg. 
161
-
168
)
35.
Thomas
DL
The challenge of hepatitis C in the HIV-infected person
Annu Rev Med
 , 
2008
, vol. 
59
 (pg. 
473
-
485
)
36.
Chun
HM
Fieberg
AM
Hullsiek
KH
, et al.  . 
Epidemiology of hepatitis B virus infection in a US cohort of HIV-infected individuals during the past 20 years
Clin Infect Dis
 , 
2010
, vol. 
50
 (pg. 
426
-
436
)
37.
Fischer
MJ
Wyatt
CM
Gordon
K
, et al.  . 
Hepatitis C and the risk of kidney disease and mortality in veterans with HIV
J Acquir Immune Defic Syndr
 , 
2010
, vol. 
53
 (pg. 
222
-
226
)
38.
Jones
CY
Jones
CA
Wilson
IB
, et al.  . 
Cystatin C and creatinine in an HIV cohort: the nutrition for healthy living study
Am J Kidney Dis
 , 
2008
, vol. 
51
 (pg. 
914
-
924
)
39.
Peng
S
Plank
LD
McCall
JL
, et al.  . 
Body composition, muscle function, and energy expenditure in patients with liver cirrhosis: a comprehensive study
Am J Clin Nutr
 , 
2007
, vol. 
85
 (pg. 
1257
-
1266
)
40.
Mofenson
LM
Brady
MT
Danner
SP
, et al.  . 
Guidelines for the Prevention and Treatment of Opportunistic Infections among HIV-exposed and HIV-infected children: recommendations from CDC, the National Institutes of Health, the HIV Medicine Association of the Infectious Diseases Society of America, the Pediatric Infectious Diseases Society, and the American Academy of Pediatrics
MMWR Recomm Rep
 , 
2009
, vol. 
58
 (pg. 
1
-
166
)
41.
Delanaye
P
Mariat
C
Cavalier
E
, et al.  . 
Trimethoprim, creatinine and creatinine based equations
Nephron Clin Pract
 , 
2011
, vol. 
119
 (pg. 
187
-
193
)
42.
Berglund
F
Killander
J
Pompeius
R
Effect of trimethoprim-sulfamethoxazole on the renal excretion of creatinine in man
J Urol
 , 
1975
, vol. 
114
 (pg. 
802
-
808
)
43.
Myre
SA
McCann
J
First
MR
, et al.  . 
Effect of trimethoprim on serum creatinine in healthy and chronic renal failure volunteers
Ther Drug Monit
 , 
1987
, vol. 
9
 (pg. 
161
-
165
)
44.
Maki
DG
Fox
BC
Kuntz
J
, et al.  . 
A prospective, randomized, double-blind study of trimethoprim-sulfamethoxazole for prophylaxis of infection in renal transplantation. Side effects of trimethoprim-sulfamethoxazole, interaction with cyclosporine
J Lab Clin Med
 , 
1992
, vol. 
119
 (pg. 
11
-
24
)
45.
Odden
MC
Scherzer
R
Bacchetti
P
, et al.  . 
Cystatin c level as a marker of kidney function in human immunodeficiency virus infection: the FRAM study
Arch Intern Med
 , 
2007
, vol. 
167
 (pg. 
2213
-
2219
)
46.
Mauss
S
Berger
F
Kuschak
D
, et al.  . 
Cystatin C as a marker of renal function is affected by HIV replication leading to an underestimation of kidney function in HIV patients
Antivir Ther
 , 
2008
, vol. 
13
 (pg. 
1091
-
1095
)
47.
Tenstad
O
Roald
AB
Grubb
A
, et al.  . 
Renal handling of radiolabelled human cystatin C in the rat
Scand J Clin Lab Invest
 , 
1996
, vol. 
56
 (pg. 
409
-
414
)
48.
Knight
EL
Verhave
JC
Spiegelman
D
, et al.  . 
Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement
Kidney Int
 , 
2004
, vol. 
65
 (pg. 
1416
-
1421
)
49.
Stevens
LA
Schmid
CH
Greene
T
, et al.  . 
Factors other than glomerular filtration rate affect serum cystatin C levels
Kidney Int
 , 
2009
, vol. 
75
 (pg. 
652
-
660
)
50.
Mathisen
UD
Melsom
T
Ingebretsen
OC
, et al.  . 
Estimated GFR associates with cardiovascular risk factors independently of measured GFR
J Am Soc Nephrol
 , 
2011
, vol. 
22
 (pg. 
927
-
937
)
51.
Macdonald
J
Marcora
S
Jibani
M
, et al.  . 
GFR estimation using cystatin C is not independent of body composition
Am J Kidney Dis
 , 
2006
, vol. 
48
 (pg. 
712
-
719
)
52.
Kramer
H
Palmas
W
Kestenbaum
B
, et al.  . 
Chronic kidney disease prevalence estimates among racial/ethnic groups: the Multi-Ethnic Study of Atherosclerosis
Clin J Am Soc Nephrol
 , 
2008
, vol. 
3
 (pg. 
1391
-
1397
)
53.
Delanaye
P
Mariat
C
Maillard
N
, et al.  . 
Are the creatinine-based equations accurate to estimate glomerular filtration rate in African American populations?
Clin J Am Soc Nephrol
 , 
2011
, vol. 
6
 (pg. 
906
-
912
)
54.
Neuhaus
J
Jacobs
DR
Baker
JV
, et al.  . 
Markers of inflammation, coagulation, and renal function are elevated in adults with HIV infection
J Infect Dis
 , 
2010
, vol. 
201
 (pg. 
1788
-
1795
)
55.
Jaroszewicz
J
Wiercinska-Drapalo
A
Lapinski
TW
, et al.  . 
Does HAART improve renal function? An association between serum cystatin C concentration, HIV viral load and HAART duration
Antivir Ther
 , 
2006
, vol. 
11
 (pg. 
641
-
645
)
56.
Estrella
MM
Parekh
RS
Astor
BC
, et al.  . 
Chronic kidney disease and estimates of kidney function in HIV infection: a cross-sectional study in the multicenter AIDS cohort study
J Acquir Immune Defic Syndr
 , 
2011
, vol. 
57
 (pg. 
380
-
386
)
57.
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
, vol. 
13
 (pg. 
177
-
187
)
58.
El-Sadr
WM
Lundgren
JD
Neaton
JD
, et al.  . 
CD4+ count-guided interruption of antiretroviral treatment
N Engl J Med
 , 
2006
, vol. 
30
 (pg. 
2283
-
2296
)
59.
Mocroft
A
Wyatt
C
Szczech
L
, et al.  . 
Interruption of antiretroviral therapy is associated with increased plasma cystatin C
AIDS
 , 
2009
, vol. 
23
 (pg. 
71
-
82
)
60.
Longenecker
CT
Scherzer
R
Bacchetti
P
, et al.  . 
HIV viremia and changes in kidney function
AIDS
 , 
2009
, vol. 
23
 (pg. 
1089
-
1096
)
61.
Bonjoch
A
Bayés
B
Riba
J
, et al.  . 
Validation of estimated renal function measurements compared with the isotopic glomerular filtration rate in an HIV-infected cohort
Antiviral Res
 , 
2010
, vol. 
88
 (pg. 
347
-
354
)
62.
Ciborowski
P
Kadiu
I
Rozek
W
, et al.  . 
Investigating the human immunodeficiency virus type 1-infected monocyte-derived macrophage secretome
Virology
 , 
2007
, vol. 
20
 (pg. 
198
-
209
)
63.
Overton
ET
Patel
P
Mondy
K
, et al.  . 
Cystatin C and baseline renal function among HIV-infected persons in the SUN study
AIDS Res Hum Retroviruses
 , 
2012
, vol. 
28
 (pg. 
148
-
155
)
64.
Esezobor
CI
Iroha
E
Oladipo
O
, et al.  . 
Kidney function of HIV-infected children in Lagos, Nigeria: using Filler’s serum cystatin C-based formula
J Int AIDS Soc
 , 
2010
, vol. 
13
 pg. 
17
 
65.
Gardner
LI
Holmberg
SD
Williamson
JM
, et al.  . 
Development of proteinuria or elevated serum creatinine and mortality in HIV-infected women
J Acquir Immune Defic Syndr
 , 
2003
, vol. 
32
 (pg. 
203
-
209
)
66.
Hsu
C-Y
Chertow
GM
Curhan
GC
Methodological issues in studying the epidemiology of mild to moderate chronic renal insufficiency
Kidney Int
 , 
2002
, vol. 
61
 (pg. 
1567
-
1576
)
67.
Perkins
BA
Nelson
RG
Ostrander
BEP
, et al.  . 
Detection of renal function decline in patients with diabetes and normal or elevated GFR by serial measurements of serum cystatin C concentration: results of a 4-year follow-up study
J Am Soc Nephrol
 , 
2005
, vol. 
16
 (pg. 
1404
-
1412
)
68.
Jaafar
A
Séronie-Vivien
S
Malard
L
, et al.  . 
Urinary cystatin C can improve the renal safety follow-up of tenofovir-treated patients
AIDS
 , 
2009
, vol. 
23
 (pg. 
257
-
259
)
69.
Barraclough
K
Er
L
Ng
F
, et al.  . 
A comparison of the predictive performance of different methods of kidney function estimation in a well-characterized HIV-infected population
Nephron Clin Pract
 , 
2009
, vol. 
111
 (pg. 
c39
-
c48
)
70.
Beringer
PM
Owens
H
Nguyen
A
, et al.  . 
Estimation of glomerular filtration rate by using serum cystatin C and serum creatinine concentrations in patients with human immunodeficiency virus
Pharmacotherapy
 , 
2010
, vol. 
30
 (pg. 
1004
-
1010
)
71.
van Deventer
HE
Paiker
JE
Katz
IJ
, et al.  . 
A comparison of cystatin C- and creatinine-based prediction equations for the estimation of glomerular filtration rate in black South Africans
Nephrol Dial Transplant
 , 
2011
, vol. 
26
 (pg. 
1553
-
1558
)
72.
Macisaac
RJ
Tsalamandris
C
Thomas
MC
, et al.  . 
Estimating glomerular filtration rate in diabetes: a comparison of cystatin-C- and creatinine-based methods
Diabetologia
 , 
2006
, vol. 
49
 (pg. 
1686
-
1689
)
73.
Delanaye
P
Cavalier
E
Krzesinski
J-M
, et al.  . 
Cystatin C-based equations: don’t repeat the same errors with analytical considerations
Nephrol Dial Transplant
 , 
2008
, vol. 
23
 pg. 
1065
 
74.
Rule
AD
Lieske
JC
Cystatin C is more than GFR, and this may be a good thing
J Am Soc Nephrol
 , 
2011
, vol. 
22
 (pg. 
795
-
797
)
75.
Kwong
Y-TD
Stevens
LA
Selvin
E
, et al.  . 
Imprecision of urinary iothalamate clearance as a gold-standard measure of GFR decreases the diagnostic accuracy of kidney function estimating equations
Am J Kidney Dis
 , 
2010
, vol. 
56
 (pg. 
39
-
49
)
76.
Shlipak
MG
Sarnak
MJ
Katz
R
, et al.  . 
Cystatin C and the risk of death and cardiovascular events among elderly persons
N Engl J Med
 , 
2005
, vol. 
352
 (pg. 
2049
-
2060
)
77.
Shlipak
MG
Katz
R
Sarnak
MJ
, et al.  . 
Cystatin C and prognosis for cardiovascular and kidney outcomes in elderly persons without chronic kidney disease
Ann Intern Med
 , 
2006
, vol. 
145
 (pg. 
237
-
246
)
78.
Kuller
LH
Tracy
R
Belloso
W
, et al.  . 
Inflammatory and coagulation biomarkers and mortality in patients with HIV infection
PLoS Med
 , 
2008
, vol. 
5
 pg. 
e203
 
79.
Rodger
AJ
Fox
Z
Lundgren
JD
, et al.  . 
Activation and coagulation biomarkers are independent predictors of the development of opportunistic disease in patients with HIV infection
J Infect Dis
 , 
2009
, vol. 
200
 (pg. 
973
-
983
)
80.
Falasca
K
Ucciferri
C
Mancino
P
, et al.  . 
Cystatin C, adipokines and cardiovascular risk in HIV infected patients
Curr HIV Res
 , 
2010
, vol. 
8
 (pg. 
405
-
410
)

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