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Letters to the Editor |
1 Clinical Decision-Making Research Unit, Vorarlberg Institute of Vascular Investigation and Treatment, and2
Department of Internal Medicine, Academic Teaching Hospital, Feldkirch, Austria
3 Department of Laboratory Medicine, Kantonsspital, Aarau, Switzerland
aAddress correspondence to this author at: Department of Laboratory Medicine, Kantonsspital, 5001 Aarau, Switzerland. Fax 41-62-838-53-99; e-mail andreas.huber{at}ksa.ch.
To the Editor:
Glomerular filtration rate (GFR) represents the best overall index of kidney function (1), and the National Kidney Foundation has recommended that clinical laboratories routinely report an estimate of GFR(1)(2). Several cystatin C–based equations for calculation of GFR have been reported(3)(4). The most recent equations have been published by Larsson et al. (GFRLarsson = 99.43 x cystatin C–1.5837)(4) and Grubb et al. [GFRGrubb = 84.69 x cystatin C–1.680 (x 0.948 if female)](5).
Both groups report on GFR estimates obtained from particle-enhanced turbidimetric immunoassay measurements of cystatin C (DakoCytomation). After correcting the Larsson estimate for body surface according to the Du Bois and Du Bois formula (6), we compared both equations, using data from 29 adult renal transplant patients who also had undergone 125I-iothalamate clearance determination as a reference measurement of GFR(7)(8). For cystatin C measurements, we used a particle-enhanced turbidimetric immunoassay (Dako) run on a Cobas Mira instrument (Roche Diagnostics), as described earlier(7)(8).
The correlation of the Larsson and Grubb cystatin C-based GFR estimates was highly significant (r = 0.98; P <0.001); however, evaluation of these methods by linear regression showed a slope substantially different from 1, indicating 23% higher GFR values obtained with the Larsson estimate (Fig. 1
). The Larsson estimates were substantially higher than the Grubb estimates even when adjustment for body surface area was not performed (data not shown).
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In comparison with the 125I-iothalamate clearance, the linear regression line for the Grubb estimate was (numbers in parentheses are the SD):
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When we compared the slopes and intercepts of these 2 linear regression lines by the method described by Zar (9), a method equivalent to analysis of covariance, the 2 regression lines showed significantly different intercepts (P <0.001), whereas we found no significant difference between the slopes (P = 0.23; GraphPad Prism 4 Software). These data are consistent with 2 distinct but parallel regression lines.
The reasons for these differences remain unclear. A possible explanation may be a reformulation of the cystatin C assay (10). Other reasons might include the different procedures to evaluate the equations and the fact that our patients are different from the patient populations in which the equations were evaluated. Standardization of cystatin C assays will lead to better comparability of cystatin C–based GFR estimates. Efforts to establish an IFCC working group focused on standardization of cystatin C measurements have already been initiated. However, standardization of measurements should also evoke consensus recommendations for the use of cystatin C–based prediction equations for GFR. In the meantime, clinical laboratories will need to carefully evaluate cystatin C– and creatinine-based equations for the estimation of GFR before introducing them into routine clinical use.
References
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