May 9, 2012

LA BioMed’s Dr. Kalantar-Zadeh: Risk Prediction Equation For Death/End-Stage Renal Disease

Equation may provide more accurate risk prediction of death, end-stage renal disease for patients with impaired kidney function

Kamyar Kalantar-Zadeh, M.D., M.P.H., Ph.D., principal investigator at the Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center (LA BioMed), is the author of an invited editorial in JAMA. The editorial accompanied a study that included data from more than 1 million adults, and indicated the use of a newer risk prediction equation that classified fewer individuals as having chronic kidney disease and more accurately categorized the risk for death and end-stage renal disease.

Glomerular filtration rate (GFR) is used in the diagnosis of chronic kidney disease (CKD) and is an independent predictor of all-cause and cardiovascular mortality and kidney failure in a wide range of populations, according to background information in the article. Clinical guidelines recommend reporting estimated GFR when serum creatinine level is measured. "The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates GFR than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables [age, sex, race, and serum creatinine level], especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking," the authors write.

Kunihiro Matsushita, M.D., Ph.D., of Johns Hopkins University, Baltimore, and colleagues conducted a study to evaluate whether estimated GFR calculated by the CKD-EPI equation predicts risk for adverse outcomes more accurately than the MDRD Study equation in a broad range of populations. The study consisted of a meta-analysis of data from 1.1 million adults (18 years of age and older) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. The participants were from 40 countries or regions of Asia,

Europe, North America and South America, the Middle East, and Oceania. Data transfer and analyses were conducted between March 2011 and March 2012. The primary adverse outcomes analyzed were all-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7,644 events from 21 cohorts).

The prevalence of CKD stages 3 to 5 (<60 mL/min/1.73 m2) was lower by the CKD-EPI equation than by the MDRD Study equation in the general population cohorts (6.3 percent vs. 8.7 percent, respectively) and in the high-risk cohorts (14.6 percent vs. 17.7 percent).

"Overall, the CKD-EPI creatinine-based equation more accurately classified individuals with respect to risk of mortality and ESRD compared with the MDRD Study equation. Given more accurate GFR estimation, lower CKD prevalence estimates, and better risk categorization by the CKD-EPI equation without additional laboratory costs, its implementation for estimated GFR reporting could contribute to more efficient and targeted prevention and management of CKD-related outcomes."

In an accompanying editorial, Dr. Kalantar-Zadeh and his co-author wrote that "even though CKD staging using the more conservative CKD-EPI equation seems valid because it produces more meaningful risk profiles, it is premature to conclude that the ultimate tool for estimated GFR accuracy has been found."

"An even more conservative and accurate equation may be developed eventually, perhaps by these same investigators who first developed and advocated the MDRD equation (that is still in use in many estimated GFR laboratory reports) and who have now advanced the CKD-EPI equation to replace its MDRD predecessor. Some inherent limitations of the MDRD equation remain essentially unchanged in the CKD-EPI equation, in particular the reliance on creatinine as a single suboptimal filtration marker that not only is a close correlate of skeletal muscle mass but also probably varies with the magnitude of ingested meat and nutritional status. To date no single circulating biomarker meets the desired criteria of the ideal renal filtration marker. It is possible that a panel of several filtration markers, including cystatin C, for instance, combined with some surrogate markers of nutritional status and body composition, will provide a more accurate and clinically meaningful estimate of GFR."


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