Comparison between the Beta-2 Microglobulin-Based Equation and the CKD-EPI Equation for Estimating GFR in CKD Patients in China: ES-CKD Study

Lili Yue; Binbin Pan; Xiumin Shi; Xin Du

doi:10.1159/000505850

Comparison between the Beta-2 Microglobulin-Based Equation and the CKD-EPI Equation for Estimating GFR in CKD Patients in China: ES-CKD Study

Kidney Dis (Basel). 2020 May;6(3):204-214. doi: 10.1159/000505850. Epub 2020 Feb 25.

Authors

Lili Yue¹, Binbin Pan¹, Xiumin Shi², Xin Du¹

Affiliations

¹ Department of Nephrology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
² Department of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.

Abstract

Background: Beta-2 microglobulin (B2M) and cystatin C are novel glomerular filtration markers that have a stronger association with adverse outcomes than creatinine. The B2M-based glomerular filtration rate (GFR) estimating equation was built in 2016. Several new creatinine and cystatin C equations were developed in 2019 in China. However, external validation of these new equations remains to be seen.

Methods: This is a prospective cohort study. The equations were validated in a population totaling 830 participants (median age 62 years). These equations include the B2M-based equation (built in 2016), three CKD-EPI equations (built in 2009 and 2012), three Yang-Du equations (C-CKD-EPIscr, C-CKD-EPIcys, and C-CKD-EPIscr-cys equations, all of which were Chinese-modified CKD-EPI equations developed by Yang et al. in 2019), and a Xiangya equation (a creatinine-based equation built in the Third Xiangya Hospital in 2019). The estimated GFR (eGFR) calculated separately by 8 equations (B2M GFR, CKD-EPIscr, CKD-EPIcys, CKD-EPIscr-cys, C-CKD-EPIscr, C-CKD-EPIcys, C-CKD-EPIscr-cys, and Xiangya equations) was compared with the reference GFR (rGFR) measured by the ^99mTc-DTPA renal dynamic imaging method. Participants were divided into CKD stage 1-5 specific subgroups. The primary outcomes of this study were bias, precision (interquartile range of difference, IQR), and accuracy (the proportion of eGFR within 30% of rGFR [P30] and root mean square error [RMSE]) of eGFR versus rGFR.

Results: The B2M-based equation was worse than CKD-EPI equations and Yang-Du equations in most outcomes. CKD-EPIscr and C-CKD-EPIscr equations had a larger area under the receiver operating characteristic curve (ROC^AUC). The CKD-EPIscr equation had the highest sensitivity (83.3%) and the Xiangya equation the highest specificity (89.5%) to diagnose CKD. The bias was the lowest in CKD-EPIcys and C-CKD-EPIscr-cys equations by median and mean difference (1.23 and -1.42, respectively). The Xiangya equation yielded the highest bias by both median and mean difference (8.29 and 6.52, respectively). The C-CKD-EPIscr equation was the most accurate with the highest P30 value (68.1%) and most precise with the lowest IQR (19). The Xiangya equation had the best RMSE (lowest RMSE, 0.56), and gave the best performance in the CKD stage 2 subgroup. The C-CKD-EPIscr-cys equation achieved the lowest bias in CKD stage 3-5 (p = 0.663, 0.104, and 0.130, respectively, compared with rGFR).

Conclusion: The B2M-based equation was worse than CKD-EPI and Yang-Du equations on the whole. CKD-EPIcys and C-CKD-EPIscr-cys equations had the lowest bias, whereas the Xiangya equation yielded the highest bias. The Xiangya equation gave the best performance in the CKD stage 2 subgroup, while the C-CKD-EPIscr-cys equation achieved the lowest bias in CKD stage 3-5. Further work to improve the performance of the GFR estimating equation is needed.

Keywords: Beta-2 microglobulin; Chinese population; Creatinine; Cystatin C; Equation; Glomerular filtration rate.