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Notable steps in obtaining improved estimates for glomerular filtration rate.

Knowledge of the glomerular filtration rate (GFR) is of crucial importance in the management of patients. In addition to a general evaluation of kidney function, a more precise assessment is valuable on many occasions, e.g., to detect early impairment of renal function, to allow correct dosage of drugs cleared by the kidneys, to monitor renal transplants, and to evaluate patients before use of potentially nephrotoxic radiographic contrast media. Determination of GFR with high accuracy requires the use of invasive techniques based on measuring the plasma clearance rate of injected substances that are excreted exclusively via glomerular filtration, e.g., inulin, [sup.125]I -iothalamate, iohexol, and [sup.51]Cr-EDTA. Such procedures are labor-intensive and not free of risk for the patient.

The plasma or serum concentrations of endogenous substances, particularly creatinine, have been used as indicators of GFR for more than a century (1). The creatinine concentration, however, is far from ideal as a GFR marker because it is strongly influenced not only by GFR, but also by factors such as muscle mass, sex, age, diet, race, and tubular secretion (2, 3). To compensate for the shortcomings, several investigators have made successful attempts at constructing GFR prediction equations that include creatinine and additional variables. The most widely used GFR prediction equations for adults are those proposed by Cockcroft and Gault (4), which produces absolute GFR values in mL/min, and the Modification of Diet in Renal Disease (MDRD) equation, which produces relative GFR values in mL x [min.sup.-1] x [(1.73 [m.sup.2]).sup.-1] (3, 5). Although both prediction equations are used frequently, their general implementation in healthcare remains far from realized, mainly because of limitations related to the use of different creatinine measurement procedures among laboratories. For this reason, a prediction equation associated with a specific method and a specific set of calibrators will not have the same diagnostic performance when used in conjunction with other methods and calibrators.

To harmonize the Jaffe procedures, merely introducing a negative offset value is not sufficient, although this reduces the positive bias in the low measuring range; it also is often necessary to compensate for the concomitant negative bias found in the measuring range above the high calibration point (6). The only way to achieve general implementation of creatinine-based prediction equations, with the associated clinical benefits for patients, is therefore to suggest steps that will produce worldwide harmonization of methods to determine creatinine. Although this may seem easy in principle, implementation of a plan to harmonize methods can be complicated because the suggested steps must be recognized as sound by all those involved in measuring creatinine. The special report entitled "Recommendations for Improving Serum Creatinine Measurement" by Myers et al., published last month in Clinical Chemistry (7), represents a document of such quality that the steps recommended should be recognized as worthwhile to undertake. The document not only presents an up-to-date and thorough report on advantages and disadvantages associated with all known methods for creatinine determination, it also suggests clearly feasible ways for the engaged parties to achieve worldwide harmonization and metrologic traceability for the reported creatinine values.

Implementation of the steps suggested by Myers et al. (7) for harmonization of creatinine measurement may also allow further progress in the development of new GFR prediction equations with improved diagnostic performance. It is already known that use of different prediction equations might be necessary for optimal prediction of GFR in different patient cohorts (8, 9), but easy and reliable evaluation of the diagnostic performances of different prediction equations in different patient cohorts requires harmonization of creatinine measurements. In addition, comparison of different mathematic-statistical models for derivation of prediction equations could also be greatly facilitated by harmonization of creatinine measurement.

The recommendations for harmonization of creatinine measurement presented by Myers et al. (7) are also to a great extent pertinent for the harmonization of measurements of GFR markers other than creatinine, e.g., cystatin C (10,11).

Several Internet-based tools are available to facilitate the use of GFR prediction equations (12,13), but the clinical usefulness of these tools is hampered by the lack of harmonization of creatinine and cystatin C measurements. The steps toward harmonization suggested by Myers et al. (7) may very well increase the clinical benefits of using these tools.

DOI: 10.1373/clinchem.2005.062737


(1.) Jaffe M. Uber den Niederschlag welchen Pikrinsaure in normalem Harn erzeugt and uber eine neue Reaction des Kreatinins. Z Physiol Chem 1886;10:391-400.

(2.) Perrone RD, Madias NE, Levey AS. Serum creatinine as an index of renal function: new insights into old concepts. Clin Chem 1992;38:1933-53.

(3.) 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;130:461-70.

(4.) Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976;16:31-41.

(5.) Levey AS, Greene T, Kusek JW, Beck GJ. A simplified equation to predict glomerular fltration rate from serum creatinine [Abstract]. J Am Soc Nephrol 2000;11:A0828.

(6.) Martensson A, Rustad P, Lund H, Ossowicki H. Creatininium reference intervals for corrected methods. Scand J Clin Lab Invest 2004;64:439-41.

(7.) Myers GL, Miller WG, Coresh J, Fleming J, Greenberg N, Greene T, et 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.

(8.) 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 2002;141:929-37.

(9.) Stevens LA, Levey AS. Clinical implications of estimating equations for glomerular filtration rate. Ann Intern Med 2004;141:959-61.

(10.) Grubb A, Nyman U, Bjbrk J, Lindstrbm V, Rippe B, Sterner G, et al. Simple cystatin C-based prediction equations forglomerularfltration 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;51:1420-31.

(11.) Grubb A, Bjbrk J, Lindstrbm V, Sterner G, Bondesson P, Nyman U. A cystatin C-based formula without anthropometric variables estimates glomerular filtration rate better than creatinine clearance using the Cockcroft-Gault formula. Scand J Clin Lab Invest 2005;65:153-62.

(12.) NKDEP. Health Professionals. GFR MDRD calculator for adults. www. calculators/mdrd.htm (accessed November 2005).

(13.) Lund University. Tool for calculating absolute GFR (mL/min) using relative GFR (mL/min/1.73m2), weight (kg) and height (cm). GFReng.htm (accessed November 2005).

Anders Grubb [1] * Gunnar Nordin [2]

[1] Department of Clinical Chemistry University Hospital Lund, Sweden

[2] External Quality Assurance in Laboratory Medicine in Sweden (EQUALIS) Uppsala, Sweden

* Address correspondence to this author at: Department of Clinical Chemistry, University Hospital, 5-22185 Lund, Sweden. E-mail
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Title Annotation:Editorial
Author:Grubb, Anders; Nordin, Gunnar
Publication:Clinical Chemistry
Date:Feb 1, 2006
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