Table 3.

Diagnostic value of 8 estimating equations compared with rGFR

	R	p value	ROCAUC	Sensitivity	Specificity
B2M GFR	0.626	<0.001	0.829	73.7	74.1
CKD-EPIscr	0.774	<0.001	0.870	76.2	82.6
CKD-EPIcys	0.722	<0.001	0.837	76.0	74.1
CKD-EPIscr-cys	0.778	<0.001	0.867	76.0	81.2
C-CKD-EPIscr	0.774	<0.001	0.870	83.3	71.5
C-CKD-EPIcys	0.722	<0.001	0.837	82.7	64.1
C-CKD-EPIscr-cys	0.778	<0.001	0.867	82.9	71.2
Xiangya GFR	0.774	<0.001	0.869	71.2	89.5

R, coefficient of relationship between eGFR and rGFR by Pearson correlation analysis; ROC^AUC, area under the receiver operating characteristic curve; B2M GFR, beta-2 microglobulin-based equation; CKD-EPIscr, serum creatinine-based CKD-EPI equation which was developed in 2009; CKD-EPIcys, cystatin C-based CKD-EPI equation which was developed in 2012; CKD-EPIscr-cys, serum creatinine and cystatin C-based CKD-EPI equation which was developed in 2012; C-CKD-EPIscr, CKD-EPIscr equation modified for China which was newly developed in 2019; C-CKD-EPIcys, CKD-EPIcys equation modified for China which was newly developed in 2019; C-CKD-EPIscr-cys, CKD-EPIscr-cys equation modified for China which was newly developed in 2019; Xiangya GFR, serum creatinine-based equation which was newly developed in the Third Xiangya Hospital in China in 2019. Correlation coefficients of estimating equation were compared with rGFR.