GFR Estimation Using a Panel of Filtration Markers in Shanghai and Beijing

利用一组滤过标志物在上海和北京进行肾小球滤过率(GFR)估算

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Abstract

RATIONALE & OBJECTIVES: Estimated glomerular filtration rate (eGFR) using creatinine and cystatin C (eGFR(cr-cys)) may be less accurate compared to measured GFR (mGFR) in China than in North America, Europe, and Australia due to variation across regions in their non-GFR determinants. The non-GFR determinants of β(2)-microglobulin (B2M) and β-trace protein (BTP) differ from those of creatinine and cystatin C. Thus, the average eGFR using all 4 markers (eGFR(avg)) could be more accurate than eGFR(cr-cys) in China. STUDY DESIGN: Diagnostic test study. SETTING & PARTICIPANTS: 1,066 participants in Shanghai and Beijing with creatinine and cystatin C and 666 participants with all 4 filtration markers. TESTS COMPARED: Index tests were previously developed equations for eGFR using creatinine, cystatin C, B2M, and BTP and combinations. The reference test was mGFR using plasma clearance of iohexol. We compared the performance of eGFR(avg) to eGFR(cr-cys) using the proportion of participants with errors in eGFR >30% of mGFR (1 - P(30)) and root mean square error (RMSE) of the regression of eGFR on mGFR on the logarithmic scale. We also compared classification and reclassification of mGFR categories using eGFR(avg) compared to eGFR(cr-cys). OUTCOMES: Accuracy was significantly better for eGFR(avg) (1 - P(30) of 10.4% and RMSE of 0.214) compared to eGFR(cr-cys) (1 - P(30) of 13.8% and RMSE of 0.232; P = 0.004 and P = 0.006, respectively). However, improvements in accuracy did not generally translate into significant improvement in classification or reclassification of mGFR categories. LIMITATIONS: Study population may not be generalizable to clinical settings other than large urban medical centers in China. CONCLUSIONS: A panel of endogenous filtration markers including B2M and BTP in addition to creatinine and cystatin C may improve GFR estimation in China. Further study is necessary to determine whether GFR estimation using B2M and BTP can be improved and whether these improvements lead to useful clinical applications.

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