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      The impact of different GFR estimating equations on the prevalence of CKD and risk groups in a Southeast Asian cohort using the new KDIGO guidelines


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          Recently, the Kidney Disease: Improving Global Outcomes (KDIGO) group recommended that patients with CKD should be assigned to stages and composite relative risk groups according to GFR (G) and proteinuria (A) criteria. Asians have among the highest rates of ESRD in the world, but establishing the prevalence and prognosis CKD is a problem for Asian populations since there is no consensus on the best GFR estimating (eGFR) equation. We studied the effects of the choice of new Asian and Caucasian eGFR equations on CKD prevalence, stage distribution, and risk categorization using the new KDIGO classification.


          The prevalence of CKD and composite relative risk groups defined by eGFR from with Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI); standard (S) or Chinese(C) MDRD; Japanese CKD-EPI (J-EPI), Thai GFR (T-GFR) equations were compared in a Thai cohort (n = 5526)


          There was a 7 fold difference in CKD 3-5 prevalence between J-EPI and the other Asian eGFR formulae. CKD 3-5 prevalence with S-MDRD and CKD-EPI were 2 - 3 folds higher than T-GFR or C-MDRD. The concordance with CKD-EPI to diagnose CKD 3-5 was over 90% for T-GFR or C-MDRD, but they only assigned the same CKD stage in 50% of the time. The choice of equation also caused large variations in each composite risk groups especially those with mildly increased risks. Different equations can lead to a reversal of male: female ratios. The variability of different equations is most apparent in older subjects. Stage G3aA1 increased with age and accounted for a large proportion of the differences in CKD 3-5 between CKD-EPI, S-MDRD and C-MDRD.


          CKD prevalence, sex ratios, and KDIGO composite risk groupings varied widely depending on the equation used. More studies are needed to define the best equation for Asian populations.

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

          G. Myers (2006)
          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. 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. 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. 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.
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            Evaluation of the Chronic Kidney Disease Epidemiology Collaboration equation for estimating the glomerular filtration rate in multiple ethnicities.

            An equation from the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) provides more accurate estimates of the glomerular filtration rate (eGFR) than that from the modification of diet in renal disease (MDRD) Study, although both include a two-level variable for race (Black and White and other). Since creatinine generation differs among ethnic groups, it is possible that a multilevel ethnic variable would allow more accurate estimates across all groups. To evaluate this, we developed an equation to calculate eGFR that includes a four-level race variable (Black, Asian, Native American and Hispanic, and White and other) using a database of 8254 patients pooled from 10 studies. This equation was then validated in 4014 patients using 17 additional studies from the United States and Europe (validation database), and in 1022 patients from China (675), Japan (248), and South Africa (99). Coefficients for the Black, Asian, and Native American and Hispanic groups resulted in 15, 5, and 1% higher levels of eGFR, respectively, compared with the White and other group. In the validation database, the two-level race equation had minimal bias in Black, Native American and Hispanic, and White and other cohorts. The four-level ethnicity equation significantly improved bias in Asians of the validation data set and in Chinese. Both equations had a large bias in Japanese and South African patients. Thus, heterogeneity in performance among the ethnic and geographic groups precludes use of the four-level race equation. The CKD-EPI two-level race equation can be used in the United States and Europe across a wide range of ethnicity.
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              A risk score for predicting incident diabetes in the Thai population.

              The objective of this study was to develop and evaluate a risk score to predict people at high risk of diabetes in Thailand. A Thai cohort of 2,677 individuals, aged 35-55 years, without diabetes at baseline, was resurveyed after 12 years. Logistic regression models were used to identify baseline risk factors that predicted the incidence of diabetes; a simple model that included only those risk factors as significant (P < 0.05) when adjusted for each other was developed. The coefficients from this model were transformed into components of a diabetes score. This score was tested in a Thai validation cohort of a different 2,420 individuals. A total of 361 individuals developed type 2 diabetes in the exploratory cohort during the follow-up period. The significant predictive variables in the simple model were age, BMI, waist circumference, hypertension, and history of diabetes in parents or siblings A cutoff score of 6 of 17 produced the optimal sum of sensitivity (77%) and specificity (60%). The area under the receiver-operating characteristic curve (AUC) was 0.74. Adding impaired fasting glucose or impaired glucose tolerance status to the model slightly increased the AUC to 0.78; adding low HDL cholesterol and/or high triglycerides barely improved the model. The validation cohort demonstrated similar results. A simple diabetes risk score, based on a set of variables not requiring laboratory tests, can be used for early intervention to delay or prevent the disease in Thailand. Adding impaired fasting glucose or impaired glucose tolerance or triglyceride and HDL cholesterol status to this model only modestly improves the predictive ability.

                Author and article information

                BMC Nephrol
                BMC Nephrology
                BioMed Central
                6 January 2012
                : 13
                : 1
                [1 ]Department of Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok10110, Thailand
                [2 ]Division of Clinical Chemistry, Department of Pathology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok 10110, Thailand
                [3 ]Medical and Health Office, Electricity Generating Authority of Thailand, Bangkruay, Nonthaburi 11130, Thailand
                Copyright ©2012 Kitiyakara et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                : 26 April 2011
                : 6 January 2012
                Research Article

                renal failure,glomerular filtration rate,thai,egat,epidemiology, classification,kidney
                renal failure, glomerular filtration rate, thai, egat, epidemiology, classification, kidney


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