Equation May Accurately Predict Risk of Certain Outcomes for Patients with Impaired Kidney Function

Newswise — In a study that included data from more than 1 million adults, use of a newer risk prediction equation classified fewer individuals as having chronic kidney disease and more accurately categorized the risk for death and end-stage renal disease, according to a study in the May 9 issue of JAMA.

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).

Estimated GFR was classified into 6 categories (90 or greater, 60-89, 45-59, 30-44, 15-29, and <15 mL/min/1.73 m2) by both equations. The researchers found that approximately one-fourth of participants were reclassified to a higher estimated GFR category by the CKD-EPI equation compared with the MDRD Study equation (24.4 percent in the general population cohorts, 15.4 percent in the high-risk cohorts, and 6.6 percent in the CKD cohorts), lowering the prevalence of CKD in all cohorts except for the elderly. Approximately 0.6 percent of participants were reclassified to a lower estimated GFR category. Participants who were reclassified upward had lower risks of mortality and ESRD compared with those not reclassified even after adjusting for various factors. Individuals who were reclassified downward (0.7 percent) had higher risk than those who were not reclassified.

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).

"Net reclassification improvement based on estimated GFR categories was significantly positive for all outcomes. Net reclassification improvement was similarly positive in most subgroups defined by age (<65 years and 65 years and older), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts," the authors write.

"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."

(JAMA. 2012;307[18]:1941-1951. Available pre-embargo to the media at www.jamamedia.org)

Editor's Note: Please see the article for additional information, including other authors, author contributions and affiliations, financial disclosures, funding and support, etc.

Editorial: Toward More Accurate Detection and Risk Stratification of Chronic Kidney Disease

In an accompanying editorial, Kamyar Kalantar-Zadeh, M.D., M.P.H., Ph.D., of the Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, Calif., and Alpesh N. Amin, M.D., M.B.A., of the University of California-Irvine Medical Center, write 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."

(JAMA. 2012;307[18]:1976-1977. Available pre-embargo to the media at www.jamamedia.org)

Editor's Note: This work was supported by research grants from the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health and a philanthropic grant from Harold C. Simmons. Please see the article for additional information, including author affiliations, financial disclosures, etc.

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