Recommendations for improving serum creatinine measurement: a report from the Laboratory Working Group of the National Kidney Disease Education Program

Abstract

Background: Reliable serum creatinine measurements in glomerular filtration rate (GFR) estimation are critical to ongoing global public health efforts to increase the diagnosis and treatment of chronic kidney disease (CKD). We present an overview of the commonly used methods for the determination of serum creatinine, method limitations, and method performance in conjunction with the development of analytical performance criteria. Available resources for standardization of serum creatinine measurement are discussed, and recommendations for measurement improvement are given.

Methods: The National Kidney Disease Education Program (NKDEP) Laboratory Working Group reviewed problems related to serum creatinine measurement for estimating GFR and prepared recommendations to standardize and improve creatinine measurement.

Results: The NKDEP Laboratory Working Group, in collaboration with international professional organizations, has developed a plan that enables standardization and improved accuracy (trueness) of serum creatinine measurements in clinical laboratories worldwide that includes the use of the estimating equation for GFR based on serum creatinine concentration that was developed from the Modification of Diet in Renal Disease (MDRD) study.

Conclusions: The current variability in serum creatinine measurements renders all estimating equations for GFR, including the MDRD Study equation, less accurate in the normal and slightly increased range of serum creatinine concentrations [<133 micromol/L (1.5 mg/dL)], which is the relevant range for detecting CKD [<60 mL.min(-1).(1.73 m2)(-1)]. Many automated routine methods for serum creatinine measurement meet or exceed the required precision; therefore, reduction of analytical bias in creatinine assays is needed. Standardization of calibration does not correct for analytical interferences (nonspecificity bias). The bias and nonspecificity problems associated with some of the routine methods must be addressed.