Clinical Chemistry Link to Randox Laboratories Web Site
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Clinical Chemistry 53: 480-488, 2007. First published January 26, 2007; 10.1373/clinchem.2006.076042
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow 076042.Supplemental Data
Right arrow All Versions of this Article:
clinchem.2006.076042v1
53/3/480    most recent
Right arrow Submit an electronic Letter to
the Editor about this paper
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (4)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Pucci, L.
Right arrow Articles by Penno, G.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Pucci, L.
Right arrow Articles by Penno, G.
Related Collections
Right arrow Endocrinology and Metabolism
(Clinical Chemistry. 2007;53:480-488.)
© 2007 American Association for Clinical Chemistry, Inc.

Endocrinology and Metabolism

Cystatin C and Estimates of Renal Function: Searching for a Better Measure of Kidney Function in Diabetic Patients

Laura Pucci1,a, Stefano Triscornia1, Daniela Lucchesi1, Carmen Fotino1, Giovanni Pellegrini2, Ennia Pardini2, Roberto Miccoli1, Stefano Del Prato1 and Giuseppe Penno1

1 Dipartimento di Endocrinologia e Metabolismo and 2 Laboratorio di Analisi Chimiche e Microbiologiche, Azienda Ospedaliero Universitaria di Pisa, Pisa, Italy.

aAddress correspondence to this author at: Dipartimento di Endocrinologia e Metabolismo, U.O. di Malattie Metaboliche e Diabetologia, Università di Pisa, 56124 Pisa, Italy. Fax 39-050-541521; e-mail plaura{at}immr.med.unipi.it.


   Abstract
Top
 Abstract
Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Background: Early identification of impairment in renal function is crucial in diabetic patients. Serum cystatin C may be the most sensitive indicator of glomerular filtration rate (GFR) in the clinical setting.

Methods: We compared cystatin C with creatinine, the Cockcroft-Gault (C-G) formula, and the Modification of Diet in Renal Disease (MDRD) study equation for the assessment of early decreased renal function in 288 diabetic patients (125 type 1, 163 type 2) with renal impairment [GFR: 4–222 mL · min–1 · (1.73 m2)–1]. Relationships of cystatin C, creatinine, and iohexol clearance were linearized by plotting their reciprocals in a simple regression model. Diagnostic efficiency was calculated from ROC curves.

Results: In this study population, cystatin C (P = 0.0013) was better correlated with GFR (r = 0.857) than were creatinine (r = 0.772), C-G (r = 0.750), and MDRD (r = 0.806), a result replicated in patients with normal renal function (P = 0.023, type 1; P = 0.011, type 2), but not in those with decreased GFR. Mean cystatin C concentrations showed step-by-step statistically significant increases as GFR decreased, allowing very early detection of reduction in renal function. At 90 mL · min–1 · (1.73 m2)–1 and 75 mL · min–1 · (1.73 m2)–1 cut-points, diagnostic efficiencies of cystatin C (89% and 92%) were better than those of the other variables (79%–82% and 85%–86%, respectively; P = 0.01).

Conclusions: All data supported the value of serum cystatin C compared with conventional estimates based on serum creatinine measurement for detecting very early reduction of renal function. Use of cystatin C to measure renal function will optimize early detection, prevention, and treatment strategies for diabetic nephropathy.


   Introduction
Top
 Abstract
 Introduction
Patients and Methods
 Results
 Discussion
 References
 
Individuals with moderate (1) or mildly (2) decreased renal function are at increased risk for chronic kidney disease and cardiovascular disease. Adverse outcomes of renal failure can be prevented or delayed through early detection and treatment (3). Therefore the routine measurement of the urine albumin-to-creatinine (A/C)1 ratio and estimation of glomerular filtration rate (GFR) are strongly recommended for patients at high risk for kidney failure and cardiovascular disease, such as diabetic patients (4).

Gold standard procedures for GFR measurement, based on the clearance of 51Cr-EDTA or iohexol, are impractical in the clinical setting and for larger research studies. Otherwise, creatinine alone is unsatisfactory to estimate GFR, and leads to delays in detecting earlier stages of kidney failure (3). Indeed, in addition to renal function, serum creatinine depends on creatinine generation, extrarenal elimination, and tubular handling (5). By accounting for physiologic factors that affect creatinine, equations estimating GFR overcome some limitations. Creatinine clearance calculated by the Cockcroft-Gault (C-G) formula overestimates GFR as renal function declines and tubular secretion increases. The Modification of Diet in Renal Disease (MDRD) study equation (7) shows low accuracy at higher GFR (7).

Cystatin C has been identified as a new, promising, and easily measurable marker for prompt detection of early kidney failure (8)(9). Cystatin C is produced at a constant rate by nucleated cells and released into the bloodstream with a half-life of ~2 h (10). Cystatin C is freely filtered and almost completely taken up and degraded, but not secreted, by proximal tubular cells. Several studies have used direct measures of GFR as the gold standard to compare cystatin C with creatinine and creatinine-derived estimates of GFR (11). Several studies have also been conducted in diabetic patients (12)(13)(14)(15)(16)(17)(18)(19)(20)(21) in whom cystatin C seems to outperform creatinine-based estimations (12)(14)(15)(16)(17)(18)(20)(21). Nevertheless the utility of cystatin C remains uncertain (22).

Using iohexol plasma clearance as the reference GFR, we compared cystatin C with serum creatinine, C-G, and MDRD for estimating GFR in a large sample of patients with type 1 and type 2 diabetes.


   Patients and Methods
Top
 Abstract
 Introduction
 Patients and Methods
Results
 Discussion
 References
 
A total of 288 white diabetic patients were recruited at the Department of Endocrinology and Metabolism between January 2003 and December 2004. Our Ethics Committee approved the study that was conducted in accordance with the Helsinki Declaration. All study participants gave written informed consent.

Among type 1 diabetic patients (n = 125), 31% had A/C ratios within the reference interval, 33% had microalbuminuria, and 36% had overt nephropathy. The respective values for type 2 diabetic patients (n = 163) were 12%, 60%, and 28%. Hypertension, defined as blood pressure >140/90 mmHg and/or ongoing treatment, occurred in 62% and 82% of patients, respectively. All patients with hypertension and/or increased albuminuria were on ACE-inhibitors and/or AT1-antagonists. In 73% of these patients, calcium channel blockers and/or diuretics or other antihypertensives were also employed.

Urinary albumin was measured by a nephelometric immunoassay on the BNTM II nephelometer (Dade/Behring) in at least 3 first-morning urine samples obtained in a 6-month period. Microalbuminuria was defined as an A/C ratio of 2.5 (3.5 in females) to 30 mg/mmol; clinical nephropathy as an A/C ratio >30 mg/mmol and/or a serum creatinine ≥133 µmol/L (1.5 mg/dL) in males or ≥115 µmol/L (1.3 mg/dL) in females.

Serum and urinary creatinine were determined by a fully automated Jaffè kinetic method on a Roche/Hitachi 747 analyzer. Because the serum creatinine assay had not been recalibrated to be traceable to an isotope dilution mass spectrometry reference method (23), the original MDRD equation was employed for estimating GFR: [GFR (mL · min–1 · (1.73 m2)–1) = 186 · (creatinine)–1154 · (age)–0.203 · (0.742 if female)]. We also estimated GFR by the C-G formula: creatinine clearance (mL/min) = (140 – age) x weight/72 x creatinine (x 0.85 in females) (3).

Serum cystatin C was measured by a particle-enhanced nephelometric immunoassay (N Latex Cystatin C, Dade Behring Diagnostics) on the BN II nephelometer.

GFR was assessed by the iohexol plasma clearance (iGFR) method as previously described (24). An intravenous bolus of 5 mL of iohexol (Omnipaque 300; Nycomed) was injected. Blood samples were drawn at 5, 15, 60, 90, 180, 240, and 300 min. If creatinine was >176 µmol/L (2 mg/dL), samples were withdrawn also at 360 and 420 min after injection; if creatinine was >440 µmol/L (5 mg/dL) a further sample was taken at the 1440th minute.

For both the cystatin C assay and iGFR procedure, details are described in the online expanded Methods section [see the Data Supplement that accompanies the online version of this article at http://www.clinchem.org/content/vol53/issue3].

statistical analysis
Results are presented as mean (SD) or median (range). To check gaussian distributions, data were evaluated by the Kolgomorov-Smirnov test, taking P <0.001 as significant. Cystatin C and creatinine were found not to have a gaussian distribution; their logarithms were employed in all statistical treatments. Differences in continuous variables were investigated by the one-way ANOVA followed by the Scheffé test and the unpaired Student t-test. Fisher exact test and {chi}2 test were employed to analyze contingency tables. The limit of significance was P <0.05. Reciprocals of cystatin C and creatinine allowed the linearization of the curvilinear relationship between iGFR and each serum marker. Correlations were investigated by the simple linear regression and by calculating the coefficient of regression.

To assess the diagnostic value of each marker, nonparametric ROC curves were generated by plotting the sensitivity vs 1-specificity. Areas under the curves (AUC), 95% confidence intervals (CI), and differences between ROC curves were calculated. In creating ROC curves, we used 3 cutoffs for iGFR: 60, 75, and 90 mL · min–1 · (1.73 m2)–1. For each value we obtained the maximum diagnostic efficiency (the proportion of patients correctly classified at each cut-point), the cutoff limits at maximum efficiency, sensitivity and specificity, positive predictive values (PPV) and negative predictive values (NPV).

To investigate variables other than renal function affecting creatinine and cystatin C, multiple regression analyses were performed.


   Results
Top
 Abstract
 Introduction
 Patients and Methods
 Results
Discussion
 References
 
diabetic patients
Patients with type 1 diabetes were younger and had longer diabetes duration than those with type 2 (Table 1 ). Body mass index (BMI) was lower and hemoglobin A1c higher in type 1 patients. Systolic pressure and rate of hypertension were higher in type 2 patients, whereas advanced complications, overt nephropathy, and proliferative retinopathy were more frequent in type 1 patients. These differences account, at least in part, for the differences in renal function between type 1 and type 2 diabetic patients. Both groups, however, share a wide and comparable range of explored renal function. Albuminuria correlated inversely with decreasing iGFR (n = 288, r = –0.439, P <0.0001). This relation was stronger (P = 0.0002) in type 1 patients (r = 0.668, P <0.0001) than in type 2 patients (r = 0.341, P <0.0001).


View this table:
[in this window]
[in a new window]

  		Table 1. General characteristics of patients with type 1 and type 2 diabetes, and comparison of renal function tests.

correlations between endogenous parameters of renal function and igfr
Cystatin C correlated more strongly (P = 0.006) with iGFR (n = 288, r = 0.857, P <0.0001) than did creatinine (r = 0.772, P <0.0001). Furthermore, cystatin C showed better correlation with iGFR (P <0.001, and P <0.05, respectively) than C-G (r = 0.750, P <0.0001) and MDRD (r = 0.806, P <0.0001). These correlations occurred in patients with type 1 and type 2 diabetes, but differences in correlation coefficients were stronger in type 1 than in type 2 patients (Table 2 ).


View this table:
[in this window]
[in a new window]

  		Table 2. Correlations between iGFR and reciprocal of serum cystatin C, reciprocal of serum creatinine, creatinine clearance calculated by the C-G formula, and GFR estimated by the abbreviated MDRD equation, respectively in type 1 and type 2 diabetic patients.

For both type 1 and type 2 diabetes, regressions were stronger for patients with reduced GFR [<90 mL · min–1 · (1.73 m2)–1] than for those with normal GFR. For patients with reduced GFR, both type 1 and type 2, all parameters had approximately the same correlation value with GFR (P <0.0001). For patients with normal GFR, cystatin C had a higher correlation value (type 1: r = 0.59; type 2: r = 0.65, P <0.001) than all the other variables (Table 3 ).


View this table:
[in this window]
[in a new window]

  		Table 3. Correlations between iGFR and reciprocal of serum cystatin C, reciprocal of serum creatinine, creatinine clearance calculated by the C-G formula, and GFR estimated by the abbreviated MDRD equation, respectively in type 1 and type 2 diabetic patients with normal and reduced renal function.

endogenous parameters of renal function by igfr
GFR values were divided into 6 categories [<45, 45–59.9, 60–74.9, 75–90, 90–120, and >120 mL · min–1 · (1.73 m2)–1], incorporating the guidelines of the US National Kidney Foundation (3). Distributions of sexes ({chi}2=5.39, P = 0.370) and types of diabetes ({chi}2=7.88, P = 0.162) were similar in the 6 categories that did not differ in age (P = 0.496) and only slightly in BMI (P = 0.006), because of a lower BMI in patients with GFR <45 mL · min–1 · (1.73 m2)–1. However, patients with iGFR >120 mL · min–1 · (1.73 m2)–1 were younger (P <0.005) and more frequently males (P = 0.027).

In the study patient population as a whole (Fig. 1 ), as well as in type 1 and type 2 diabetic patients (data not shown), decreasing iGFR was associated with increasing cystatin C, increasing creatinine, and decreasing GFR as estimated by both C-G and MDRD. Among iGFR categories, however, a step-by-step statistically significant change in the mean values was observed only for cystatin C (Fig. 1A ). Thus cystatin C not only discloses early decreases in GFR [75–90 mL · min–1 · (1.73 m2)–1] but also reflects changes within the reference interval [>90 mL · min–1 · (1.73 m2)–1]. Creatinine (Fig. 1B ) and C-G (Fig. 1C ) did not reflect early decreases in renal function (differences in C-G within the GFR reference interval disappeared when corrected for age and sex), but showed significant decreases only when iGFR was 75 mL · min–1 · (1.73 m2)–1 or lower. Use of MDRD seems to reflect changes even within the reference range (Fig. 1D ), but renal function is estimated with low precision in individuals with a higher GFR. Indeed, the bias between MDRD and iGFR tends to increase for GFR values <45 and >90 mL · min–1 · (1.73 m2)–1. In particular, MDRD underestimated GFR by 19% and 29% in patients with iGFR values of 90–120 and >120 mL · min–1 · (1.73 m2)–1, respectively (Fig. 2 ). Results were consistent irrespective of sex and type of diabetes.


Figure 1
View larger version (30K):
[in this window]
[in a new window]

  		Figure 1. Endogenous serum variables of renal function:(A) serum cystatin C; (B), serum creatinine; and estimated GFR from prediction equations (C), C-G formula; (D), MDRD equation; according to GFR assessed by iohexol plasma clearance.

For each variable, one-way ANOVA gives a P value <0.0001. Both cystatin C and creatinine were log-transformed before analysis (P values reported in the 4 panels were obtained by the Scheffé test).


Figure 2
View larger version (15K):
[in this window]
[in a new window]

  		Figure 2. Percentage difference between GFR estimated by the MDRD equation and the iohexol plasma clearance according to GFR assessed by iohexol plasma clearance.

nonparametric roc curves
ROC plots for cystatin C and creatinine (Table 4 ) demonstrated that the AUC of cystatin C was greater than that of creatinine at a cutoff level of 90 (P = 0.003) and 75 mL · min–1 · (1.73 m2)–1 (P = 0.0018), but not at a cutoff threshold of 60 mL · min–1 · (1.73 m2)–1 (P = 0.342). Likewise, AUC for cystatin C was greater than those for C-G and MDRD at the cutoff levels of 90 (P = 0.0005 and P = 0.007, respectively) and 75 mL · min–1 · (1.73 m2)–1 (P = 0.005 and P = 0.004, respectively), but not at the cutoff of 60 mL · min–1 · (1.73 m2)–1 (P = 0.192 and P = 0.461). All these results were reproduced in type 1 and type 2 diabetic patients (see Tables 1 and 2 in the online Data Supplement).


View this table:
[in this window]
[in a new window]

  		Table 4. ROC analysis for serum cystatin C, serum creatinine, creatinine clearance calculated by the C-G formula, and GFR estimated by the abbreviated MDRD equation in the whole group of diabetic patients.

At the cut-point of 90 mL · min–1 · (1.73 m2)–1, the maximum diagnostic efficiency of cystatin C (89%) was higher than those of creatinine (82%, P = 0.04), C-G (79%, P = 0.004) and MDRD (80%, P = 0.02). The cutoff limit of 0.98 mg/L for cystatin C corresponds to a PPV of 93% and a NPV of 87%. The respective features for the cutoff limit of 98 µmol/L (1.11 mg/dL) for creatinine were PPV 86% and NPV 80%. At the cutoff point of 75 mL · min–1 · (1.73 m2)–1, the maximum diagnostic efficiency was 92% for cystatin C, 85% (P = 0.02) for creatinine, 86% for C-G (P = 0.04), and 86% for MDRD (P = 0.04). The cutoff limit of 1.13 mg/L for cystatin C corresponds to a PPV of 93% and to a NPV of 91%. The respective features for the cutoff limit of 110 µmol/L (1.25 mg/dL) for creatinine are PPV 81% and NPV 87%. No differences between the parameters estimating GFR were observed when the cut-point was at 60 mL · min–1 · (1.73 m2)–1 (Table 4Up ).

extrarenal factors affecting serum concentrations of renal function variables
In patients with normal GFR [>90 mL · min–1 · (1.73 m2)–1], mean (SD) creatinine was higher (P <0.05) in males than in females [80 ( (14)) µmol/L, 0.91 (0.16) mg/dL, vs 73 (10) µmol/L, 0.83 (0.11) mg/dL, respectively], but no differences (P = 0.16) were observed for cystatin C [0.76 (0.15) vs 0.71 (0.08) mg/L]. In patients with decreased GFR, no sex differences were observed for either creatinine or cystatin C.

Age was weakly related to creatinine in type 1 (r = 0.20, P = 0.02) and type 2 diabetic patients (r = 0.21, P = 0.007) as a whole, but not in patients with normal GFR. Age was also related to cystatin C in type 1 (r = 0.32, P = 0.006) and in type 2 diabetic patients (r = 0.46, P <0.001). This correlation persisted in patients with normal GFR (r = 0.45, P <0.001), particularly in those with type 2 diabetes (r = 0.59, P <0.001).

An inverse correlation was observed between BMI and creatinine (r = –0.17, P = 0.004). This correlation was also present in those with normal GFR (r = –0.18, P = 0.02) and therefore was not driven by the lower BMI of patients with severe renal failure. A correlation between BMI and cystatin C (r = –0.19, P = 0.006) was also observed, but was lost in patients with normal GFR.

Multiple regression analysis indicated that for the whole patient group, extrarenal factors (including hypertension and smoking) affected both creatinine (sex, BMI) and cystatin C (age, hypertension) independently of renal function, but explained variations increased only very slightly, by 3%–4%. In the subgroup with normal GFR, the same extrarenal factors affected to some degree the explained variation of both creatinine (by 12%, from 12%–24%) and cystatin C (by 13%, from 36%–49%). Thus, half of the explained variation of creatinine was attributable to extrarenal factors, whereas extrarenal factors account only for approximately one-fourth of explained variation of cystatin C.


   Discussion
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
References
 
The production of cystatin C has been extensively reported to be independent of and unaffected by sex, age, height, weight, and muscle mass (10). In our study, cystatin C, unlike creatinine, was unaffected by sex and BMI, but was correlated with age independently of GFR. These effects, negligible when the entire range of renal function was considered, became significant in patients with normal GFR. Compared with creatinine, however, the proportion of variations in cystatin C attributable to extrarenal factors is considerably lower (50% vs 26%).

Two large studies (25)(26) with consistent results found that cystatin C is influenced by many variables (age, sex, body mass, smoking, hypertension, coronary heart disease, C-reactive protein) other than renal function alone, even after adjustment for kidney function. Both studies excluded patients with moderate and severe renal failure, and in both cystatin C was highly correlated with age (r ~0.40).

Creatinine tends to be increased in patients with hypothyroidism and decreased in those with hyperthyroidism. The production of cystatin C is differently influenced by thyroid hormone, so that concentrations of cystatin C are low in hypothyroidism (27), even in mild forms (28), and increased in hyperthyroidism (27). Thyroid dysfunction is increased in frequency in the diabetic population (29). In our study, thyroid status was known in all participants, and patients with no euthyroidism were excluded.

Even if nonrenal influences, including polymorphisms in the promoter and exon 1 of the cystatin C gene (30)(31), make cystatin C not completely reliable as a measure of renal function, most studies have found cystatin C to be a better marker of GFR than creatinine. In a recent metaanalysis (9), approximations of GFR performed with cystatin C compared with creatinine had higher correlation coefficients (0.816 vs 0.742; P <0.001) and ROC-AUC (0.926 vs 0.837; P <0.001).

Previous studies have compared creatinine and creatinine-derived formulas with cystatin C in patients with diabetes, employing an acknowledged gold standard as the reference method for GFR (12)(13)(14)(15)(17)(19)(20)(21), but most of them included small numbers of patients. Overall, 115 type 1 diabetic patients were included in 4 studies (13)(15)(19)(21) and 355 type 2 patients were enrolled in 7 studies (12)(13)(14)(17)(19)(20)(21). As far as the gold standard for GFR is concerned, 51Cr-EDTA (12)(13)(14)(19)(21), iohexol (15), or (99m)Tc-DTPA (20) plasma clearance techniques, or 125I-iothalamate urinary clearance (17) were employed. In all these studies, with one relevant exception (14), only a few blood samples were obtained after tracer injection, and results were analyzed with a unicompartmental model. To increase accuracy, we adopted a multiple sampling protocol to measure iGFR after iohexol injection, with longer time intervals between the injection and sampling points as creatinine increased (24).

Using 4 methods of evaluation (correlations with GFR, mean values of each variable in patients stratified by GFR values, ROC curves, and diagnostic efficiency) we showed that cystatin C is more sensitive for detecting early renal function impairment than creatinine and creatinine-derived formulas.

The correlation of cystatin C with GFR was stronger than the correlation with creatinine, C-G, or MDRD. As reported in type 2 diabetes (14), and also observed in our study in both type 1 and type 2 patients, the correlations between GFR and creatinine or cystatin C were higher in patients with decreased than in those with normal GFR. The regressions with GFR were superimposable in the subgroup with reduced GFR, whereas in patients with normal renal function the relationship between cystatin C and GFR was stronger than between GFR and the other 3 variables. This different behavior is due not only to the wider range of GFR values of patients with reduced renal function but also to the role played by different pathophysiological factors. In patients with reduced GFR, both cystatin C and creatinine are strongly and comparably influenced by renal impairment. Furthermore, cystatin C has been recently reported to have significant nonrenal clearance that, as for creatinine, has a relatively greater impact in patients with severe renal failure (32). Thus cystatin C and creatinine are strongly influenced by common factors and closely correlated in patients with reduced GFR, whereas the correlation is lower in patients with normal GFR as a consequence of the different weight of different factors that affect serum concentrations. The lower variance and the relatively greater importance of extrarenal covariates in affecting serum creatinine largely account for its insensitivity for detecting small decreases in GFR, in the so-called creatinine-blind GFR area.

Comparison of the mean values of the 4 variables in groups with different GFRs clearly revealed the performance of cystatin C when we focused on differences within the creatinine-blind GFR range, when creatinine and C-G are normal or do not change significantly despite declining renal function. With MDRD calculations it seems possible to detect changes in renal function even within the GFR reference range, but at the price of an unacceptable underestimation of GFR. Furthermore, the large sample of patients with high GFR [>120 mL · min–1 · (1.73 m2)–1] included in our study showed significantly reduced cystatin C, suggesting that low cystatin C could be a useful marker for hyperfiltration. Therefore, cystatin C might be employed in large prospective studies for exploring hyperfiltration, a condition whose prognostic role in the history of diabetic nephropathy has been debated for decades (33).

The diagnostic efficiency of cystatin C, as shown by the AUCs of the ROC curves is higher than those of the other indexes. The GFR reference threshold chosen, below which GFR is defined as impaired, influences the diagnostic efficiency of the methods under investigation. At both 90 and 75 mL · min–1 · (1.73 m2)–1 GFR, efficiency was higher for cystatin C and comparable for the other parameters. The lower the GFR limit chosen, the more the ROC curves for MDRD, C-G, creatinine, and cystatin C approach each other. Our ROC curves confirmed that cystatin C is a better diagnostic tool than creatinine, C-G, and MDRD both for identifying diabetic patients with normal (>90) or near-normal [>75 mL · min–1 · (1.73 m2)–1] GFR and for detecting patients with early (<75) or very early [<90 mL · min–1 · (1.73 m2)–1] impairment of GFR.

Previous studies on the role of cystatin C in detecting early renal failure in diabetic patients were contradictory. Some authors showed that cystatin C was more effective than creatinine in detecting initial reduction of GFR in type 2 (12)(14)(17)(20)(21) as well as in type 1 diabetes (15)(21). Two further studies, which did not employ a gold standard method for GFR, confirmed that cystatin C better differentiates GFR values among type 1 (18) and type 2 (16)(18) diabetic patients. Two studies (13)(19), on the other hand, showed that cystatin C is not more sensitive than creatinine for detecting early renal failure. Such discrepancies may be attributable at least in part to intraassay variations for creatinine and cystatin C measurements related to differences in assay techniques. We employed a nephelometric assay for cystatin C, a method claimed to perform with higher accuracy (34). Discrepancies may also rise from different and often arbitrarily chosen cut-points for the definition of abnormalities in renal function. In our study, the cut-points for GFR stratification incorporate the guidelines of the US National Kidney Foundation (3). Finally, our study includes the greatest number of type 1 and type 2 patients evaluated so far to explore the value of cystatin C.

More recently, some studies have successfully investigated the possibility of introducing cystatin C-based formulas without anthropometric variables to replace creatinine-based equations in predicting GFR (35). Furthermore, in a cross-sectional study of 251 patients, composed mainly of type 2 diabetic patients (82%), a GFR estimated from cystatin C had a predictive performance towards GFR equal to commonly used creatinine-based estimates (36). On the other hand, trends in the reciprocal of cystatin C concentrations during a 4-year follow-up correlated more closely to changes in urinary iothalamate clearance than C-G and MDRD in type 2 diabetic patients with normal or increased GFR (37).

In conclusion, although multiple factors in addition to renal function may influence cystatin C, our study provides convincing evidence that cystatin C may be more useful for detecting early renal impairment in both type 1 and type 2 diabetic patients than are creatinine and commonly employed creatinine-derived formulas. These results are remarkable in light of data suggesting that cystatin C is a useful indicator of the association of mild kidney dysfunction with increased risk for cardiovascular events (38), peripheral arterial disease, heart failure (39), and death (38). Furthermore, recent studies (37)(40) suggest that very early renal failure, instead of or in addition to microalbuminuria, may be considered the early marker of the underlying progressive kidney damage associated with diabetes.


   Footnotes
 
1 Nonstandard abbreviations: A/C, urinary albumin-to-creatinine ratio; GFR, glomerular filtration rate; C-G, Cockcroft-Gault formula; MDRD, Modification of Diet in Renal Disease study equation; iGFR, iohexol plasma clearance method; AUC, areas under the curve; CI, confidence interval; PPV, positive predictive values; NPV, negative predictive values; and BMI, body mass index.


   References
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 

  1. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351:1296-1305.[Abstract/Free Full Text]
  2. Anavekar NS, McMurray JJ, Velazquez EJ, Solomon SD, Kober L, Rouleau JL, et al. Relation between renal dysfunction and cardiovascular outcomes after myocardial infarction. N Engl J Med 2004;351:1285-1295.[Abstract/Free Full Text]
  3. Levey AS, Coresh J, Balk E, Kausz AT, Levin A, Steffes MW, . National Kidney Foundationet al. National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med 2003;139:137-147.[Abstract/Free Full Text]
  4. Sarnak MJ, Levey AS, Schoolwerth AC, Coresh J, Culleton B, Hamm LL, . American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Preventionet al. Kidney disease as a risk factor for development of cardiovascular disease: a statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention. Circulation 2003;108:2154-2169.[Free Full Text]
  5. Stevens LA, Levey AS. Measurement of kidney function. Med Clin North Am 2005;89:457-473.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  6. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999;130:461-470.[Abstract/Free Full Text]
  7. Rule AD, Larson TS, Bergstralh EJ, Slezak JM, Jacobsen SJ, Cosio FG. Using serum creatinine to estimate glomerular filtration rate: accuracy in good health and in chronic kidney disease. Ann Intern Med 2004;141:929-937.[Abstract/Free Full Text]
  8. Levin A. Cystatin C, serum creatinine, and estimates of kidney function: searching for better measures of kidney function and cardiovascular risk. Ann Intern Med 2005;142:586-588.[Free Full Text]
  9. Dharnidharka VR, Kwon C, Stevens G. Serum cystatin C is superior to serum creatinine as a marker of kidney function: a meta-analysis. Am J Kidney Dis 2002;40:221-226.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  10. Filler G, Bokenkamp A, Hofmann W, Le Bricon T, Martinez-Bru C, Grubb A. Cystatin C as a marker of GFR-history, indications, and future research. Clin Biochem 2005;38:1-8.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  11. Mussap M, Plebani M. Biochemistry and clinical role of human cystatin C. Crit Rev Clin Lab Sci 2004;41:467-550.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  12. Harmoinen AP, Kouri TT, Wirta OR, Lehtimaki TJ, Rantalaiho V, Turjanmaa VM, et al. Evaluation of plasma cystatin C as a marker for glomerular filtration rate in patients with type 2 diabetes. Clin Nephrol 1999;52:363-370.[ISI][Medline] [Order article via Infotrieve]
  13. Oddoze C, Morange S, Portugal H, Berland Y, Dussol B. Cystatin C is not more sensitive than creatinine for detecting early renal impairment in patients with diabetes. Am J Kidney Dis 2001;38:310-316.[ISI][Medline] [Order article via Infotrieve]
  14. Mussap M, Dalla Vestra M, Fioretto P, Saller A, Varagnolo M, Nosadini R, et al. Cystatin C is a more sensitive marker than creatinine for the estimation of GFR in type 2 diabetic patients. Kidney Int 2000;61:1453-1461.[CrossRef]
  15. Tan GD, Lewis AV, James TJ, Altmann P, Taylor RP, Levy JC. Clinical usefulness of cystatin C for the estimation of glomerular filtration rate in type 1 diabetes: reproducibility and accuracy compared with standard measures and iohexol clearance. Diabetes Care 2002;25:2004-2009.[Abstract/Free Full Text]
  16. Mojiminiyi OA, Abdella N. Evaluation of cystatin C and ß-2 microglobulin as markers of renal function in patients with type 2 diabetes mellitus. J Diabetes Complications 2003;17:160-168.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  17. Hoek FJ, Kemperman FA, Krediet RT. A comparison between cystatin C, plasma creatinine and the Cockcroft and Gault formula for the estimation of glomerular filtration rate. Nephrol Dial Transplant 2003;18:2024-2031.[Abstract/Free Full Text]
  18. Buysschaert M, Joudi I, Wallemacq P, Hermans MP. Comparative performance of serum cystatin-C versus serum creatinine in diabetic subjects. Diabetes Metab 2003;29:377-383.[ISI][Medline] [Order article via Infotrieve]
  19. Perlemoine C, Beauvieux MC, Rigalleau V, Baillet L, Barthes N, Derache P, et al. Interest of cystatin C in screening diabetic patients for early impairment of renal function. Metabolism 2003;52:1258-1264.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  20. Xia LH, Bing XG, An XT. Serum cystatin C assay for the detection of early renal impairment in diabetic patients. J Clin Lab Anal 2004;18:31-35.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  21. Christensson AG, Grubb AO, Nilsson JA, Norrgren K, Sterner G, Sundkvist G. Serum cystatin C advantageous compared with serum creatinine in the detection of mild but not severe diabetic nephropathy. J Intern Med 2004;256:510-518.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  22. Curhan G. Cystatin C: a marker of renal function or something more?. Clin Chem 2005;51:293-294.[Free Full Text]
  23. Myers GL, Miller WG, Coresh J, Fleming J, Greenberg N, Greene T, . National Kidney Disease Education Program Laboratory Working Groupet al. Recommendations for improving serum creatinine measurement: a report from the Laboratory Working Group of the National Kidney Disease Education Program. Clin Chem 2006;52:5-18.[Abstract/Free Full Text]
  24. Pucci L, Bandinelli S, Pilo M, Nannipieri M, Navalesi R, Penno G. Iohexol as a marker of glomerular filtration rate in patients with diabetes: comparison of multiple and simplified sampling protocols. Diabet Med 2001;18:116-120.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  25. Knight EL, Verhave JC, Spiegelman D, Hillege HL, de Zeeuw D, Curhan GC, et al. Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement. Kidney Int 2004;65:1416-1421.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  26. Wasen E, Suominen P, Isoaho R, Mattila K, Virtanen A, Kivela SL, et al. Serum cystatin C as a marker of kidney dysfunction in an elderly population. Clin Chem 2002;48:1138-1140.[Free Full Text]
  27. Manetti L, Pardini E, Genovesi M, Campomori A, Grasso L, Morselli LL, et al. Thyroid function differently affects serum cystatin C and creatinine concentrations. J Endocrinol Invest 2005;28:346-349.[ISI][Medline] [Order article via Infotrieve]
  28. Wiesli P, Schwegler B, Spinas GA, Schmid C. Serum cystatin C is sensitive to small changes in thyroid function. Clin Chim Acta 2003;338:87-90.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  29. Perros P, McCrimmon RJ, Shaw G, Frier BM. Frequency of thyroid dysfunction in diabetic patients: value of annual screening. Diabet Med 1995;12:622-627.[ISI][Medline] [Order article via Infotrieve]
  30. Eriksson P, Deguchi H, Samnegard A, Lundman P, Boquist S, Tornvall P, et al. Human evidence that the cystatin C gene is implicated in focal progression of coronary artery disease. Arterioscler Thromb Vasc Biol 2004;24:551-557.[Abstract/Free Full Text]
  31. Loew M, Hoffmann MM, Koenig W, Brenner H, Rothenbacher D. Genotype and plasma concentration of cystatin C in patients with coronary heart disease and risk for secondary cardiovascular events. Arterioscler Thromb Vasc Biol 2005;25:1470-1474.[Abstract/Free Full Text]
  32. Sjostrom P, Tidman M, Jones I. Determination of the production rate and non-renal clearance of cystatin C and estimation of the glomerular filtration rate from the serum concentration of cystatin C in humans. Scand J Clin Lab Invest 2005;65:111-124.[ISI][Medline] [Order article via Infotrieve]
  33. Premaratne E, Macisaac RJ, Tsalamandris C, Panagiotopoulos S, Smith T, Jerums G. Renal hyperfiltration in type 2 diabetes: effect of age-related decline in glomerular filtration rate. Diabetologia 2005;48:2486-2493.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  34. Priem F, Althaus H, Jung K, Sinha P. Beta-trace protein is not better than cystatin C as an indicator of reduced glomerular filtration rate. Clin Chem 2001;47:2181.[Free Full Text]
  35. Grubb A, Nyman U, Bjork J, Lindstrom V, Rippe B, Sterner G, et al. Simple cystatin C-based prediction equations for glomerular filtration rate compared with the modification of diet in renal disease prediction equation for adults and the Schwartz and the Counahan-Barratt prediction equations for children. Clin Chem 2005;51:1420-1431.[Abstract/Free Full Text]
  36. Macisaac RJ, Tsalamandris C, Thomas MC, Premaratne E, Panagiotopoulos S, Smith TJ, et al. Estimating glomerular filtration rate in diabetes: a comparison of cystatin-C and creatinine-based methods. Diabetologia 2006;49:1686-1689.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  37. Perkins BA, Nelson RG, Ostrander BE, Blouch KL, Krolewski AS, Myers BD, 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;16:1404-1412.[Abstract/Free Full Text]
  38. Shlipak MG, Sarnak MJ, Katz R, Fried LF, Seliger SL, Newman AB, et al. Cystatin C and the risk of death and cardiovascular events among elderly persons. N Engl J Med 2005;352:2049-2060.[Abstract/Free Full Text]
  39. Shlipak MG, Katz R, Fried LF, Jenny NS, Stehman-Breen CO, Newman AB, et al. Cystatin-C and mortality in elderly persons with heart failure. J Am Coll Cardiol 2005;45:268-271.[Abstract/Free Full Text]
  40. Perkins BA, Krolewski AS. Early nephropathy in type 1 diabetes: a new perspective on who will and who will not progress. Curr Diab Rep 2005;5:455-463.[Medline] [Order article via Infotrieve]



The following articles in journals at HighWire Press have cited this article:


Home page
 Clin. Chem.Home page
V. Rigalleau, M.-C. Beauvieux, C. Lasseur, P. Chauveau, C. Raffaitin, C. Perlemoine, N. Barthe, C. Combe, and H. Gin
The Combination of Cystatin C and Serum Creatinine Improves the Monitoring of Kidney Function in Patients with Diabetes and Chronic Kidney Disease
Clin. Chem., November 1, 2007; 53(11): 1988 - 1989.
[Full Text] [PDF]

Home page
 Clin. Chem.Home page
A. G.W. Norden, P. Rodriguez-Cutillas, and R. J. Unwin
Clinical Urinary Peptidomics: Learning to Walk Before We Can Run
Clin. Chem., March 1, 2007; 53(3): 375 - 376.
[Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow 076042.Supplemental Data
Right arrow All Versions of this Article:
clinchem.2006.076042v1
53/3/480    most recent
Right arrow Submit an electronic Letter to
the Editor about this paper
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (4)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Pucci, L.
Right arrow Articles by Penno, G.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Pucci, L.
Right arrow Articles by Penno, G.
Related Collections
Right arrow Endocrinology and Metabolism

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS