不同肾小球滤过率估算方程在15~18岁慢性肾脏病儿童中应用比较

doi:10.12372/jcp.2022.21e1353

Abstract

Abstract:

Objective To compare the accuracy and applicability of eight estimation formulas for glomerular filtration rate (GFR) in children aged 15-18 years with chronic kidney disease (CKD). Methods Children with CKD hospitalized from January 2015 to March 2021 wereenrolled. Eight eGFR formulas (update Schwartz formula, CAPA formula, Counahan-Barratt formula, Filler formula, CKD-EPI-Scr2009, CKD-EPI-CysC2012, LMR18, FAS formula) were applied to estimate GFR. The Gates method of 99mTc-DTPA renal dynamic imaging was used as the gold standard GFR (sGFR) determination. The bias, precision and accuracy of each formula were compared, and the diagnostic efficacy of each formula for renal insufficiency was analyzed. Results A total of 88 children were enrolled, including 56 boys and 32 girls, and the median age was 17.0 (16.0-18.0) years. There were 56 cases of CKD stage 1, 18 cases of CKD stage 2, 11 cases of CKD stage 3, 2 cases of CKD stage 4, and 1 case of CKD stage 5. The eGFR in all formulas was positively correlated with sGFR (all P<0.001). The CKD-EPI-Scr2009 formula had the best correlation with sGFR (r=0.73), and the Filler formula had the worst correlation with sGFR (r=0.39). The CAPA, CKD-EPI-Scr2009 and FAS formulas overestimated the GFR on the overall level, while the other formulas underestimated GFR. When sGFR was used as the gold standard, the FAS formula had the smallest bias and the CAPA formula had the largest bias. In terms of precision, the LMR18 formula showed the best precision, followed by the update Schwartz formula, and the CAPA formula showed the worst precision. In terms of accuracy, the LMR18 formula showed the highest accuracy (P₃₀=73.86%). ROC curve analysis showed that the area under the curve (AUC) of the CKD-EPI-Scr2009 formula was the largest (0.907), the sensitivity of CAPA, Filler, and CKD-EPI-CysC2012 formulas were the highest (95.90%), and the specificity of LMR18 and FAS formulas were the highest (85.71%). Conclusions Among the eight eGFR formulas, the accuracy of CysC-based formulas (CAPA, Filler and CKD-EPI-CysC2012 formula) is not as good as Scr-based formulas (update Schwartz, Counahan-Barratt, CKD-EPI-Scr2009, LMR18 and FAS formula), and LMR18 formula has the highest precision and accuracy.

Key words: chronic kidney disease, glomerular filtration rate, formula, child

KUANG Qianhuining, GAO Chunlin, ZHU Hong, YANG Xiao, PENG Yingchao, XIA Zhengkun. Comparison of different estimation formulas of glomerular filtration rate in children aged 15-18 years with chronic kidney disease[J].Journal of Clinical Pediatrics, 2022, 40(12): 905-911.

Figures/Tables 6

References 29

[1]	Al-Aly Z, Bowe B. Biomarkers of CKD in children[J]. J Am Soc Nephrol, 2020, 31(5): 894-896. doi: 10.1681/ASN.2020020212 pmid: 32234830
[2]	Furth SL, Pierce C, Hui WF, et al. Estimating time to ESRD in children with CKD[J]. Am J Kidney Dis, 2018, 71(6): 783-792. doi: S0272-6386(18)30101-X pmid: 29653769
[3]	王学晶. 儿童肾小球滤过率的评估方法[J]. 中华儿科杂志, 2016, 54(7): 539-542.
[4]	Mian AN, Schwartz GJ. Measurement and estimation of glomerular filtration rate in children[J]. Adv Chronic Kidney Dis, 2017, 24(6): 348-356. doi: 10.1053/j.ackd.2017.09.011
[5]	吕潇阳, 钟良宝, 王善志, 等. 肾小球滤过率评估方程在中国糖尿病合并慢性肾脏病患者中的适用性评价[J]. 临床肾脏病杂志, 2019, 19(10): 719-726.
[6]	妇幼健康研究会, 妇女儿童肥胖控制专业委员会, 中国儿童代谢健康型肥胖定义与管理专家委员会. 中国儿童代谢健康型肥胖定义与筛查专家共识[J]. 中国妇幼健康研究, 2019, 30(12): 1487-1490.
[7]	孟群, 吴冬雪, 刘小荣, 等. 儿童慢性肾脏病营养状况及其影响因素分析[J]. 中国实用儿科杂志, 2015, 30(1): 51-54.
[8]	Haycock GB, Schwartz GJ, Wisotsky DH. Geometric method for measuring body surface area: a height-weight formula validated in infants, children, and adults[J]. J Pediatr, 1978, 93(1): 62-66.
[9]	Schwartz GJ, Muñoz A, Schneider MF, et al. New equations to estimate GFR in children with CKD[J]. J Am Soc Nephrol, 2009, 20(3): 629-637. doi: 10.1681/ASN.2008030287 pmid: 19158356
[10]	Grubb A, Horio M, Hansson LO, et al. Generation of a new cystatin C-based estimating equation for glomerular filtration rate by use of 7 assays standardized to the international calibrator[J]. Clin Chem, 2014, 60(7): 974-986. doi: 10.1373/clinchem.2013.220707 pmid: 24829272
[11]	Padgett D, Ostrenga A, Lepard L. Comparison of methods of estimating creatinine clearance in pediatric patients[J]. Am J Health Syst Pharm, 2017, 74(11): 826-830. doi: 10.2146/ajhp151004
[12]	Filler G, Lepage N. Should the Schwartz formula for estimation of GFR be replaced by cystatin C formula?[J]. Pediatr Nephrol, 2003, 18(10): 981-985. pmid: 12920638
[13]	Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate[J]. Ann Intern Med, 2009, 150(9): 604-612. doi: 10.7326/0003-4819-150-9-200905050-00006 pmid: 19414839
[14]	Terpos E, Christoulas D, Kastritis E, et al. The Chronic Kidney Disease Epidemiology Collaboration cystatin C (CKD-EPI-CysC) equation has an independent prognostic value for overall survival in newly diagnosed patients with symptomatic multiple myeloma; is it time to change from MDRD to CKD-EPI-CysC equations?[J]. Eur J Haematol, 2013, 91(4): 347-355. doi: 10.1111/ejh.12164 pmid: 23829647
[15]	Björk J, Nyman U, Delanaye P, et al. A novel method for creatinine adjustment makes the revised Lund-Malmö GFR estimating equation applicable in children[J]. Scand J Clin Lab Invest, 2020, 80(6): 456-463. doi: 10.1080/00365513.2020.1774641
[16]	Pottel H, Hoste L, Dubourg L, et al. An estimated glomerular filtration rate equation for the full age spectrum[J]. Nephrol Dial Transplant, 2016, 31(5): 798-806. doi: 10.1093/ndt/gfv454
[17]	National Kidney Foundation. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease [S]. Kidney International Supplements, 2013, 3: 1-150.
[18]	石鑫淼, 刘贝妮, 钟旭辉, 等. 儿童慢性肾脏病流行病学研究进展[J]. 中华儿科杂志, 2019, 57(9): 721-724.
[19]	Weingart C, Wirnsberger GH. Clinical implications of the estimated glomerular filtration rate[J]. Z Gerontol Geriatr, 2021, 54(3): 205-210. doi: 10.1007/s00391-021-01839-1
[20]	Selistre L, De Souza V, Cochat P, et al. GFR estimation in adolescents and young adults[J]. J Am Soc Nephrol, 2012, 23(6): 989-996. doi: 10.1681/ASN.2011070705 pmid: 22499586
[21]	Selistre L, Rabilloud M, Cochat P, et al. Comparison of the Schwartz and CKD-EPI equations for estimating glomerular filtration rate in children, adolescents, and adults: a retrospective cross-sectional study[J]. PloS Med, 2016, 13(3): e1001979. doi: 10.1371/journal.pmed.1001979
[22]	Webster-Clark M, Jaeger B, Zhong Y, et al. Low agreement between modified-Schwartz and CKD-EPI eGFR in young adults: a retrospective longitudinal cohort study[J]. BMC Nephrol, 2018, 19(1): 194. doi: 10.1186/s12882-018-0995-1 pmid: 30081844
[23]	Björk J, Grubb A, Sterner G, et al. Revised equations for estimating glomerular filtration rate based on the Lund-Malmö Study cohort[J]. Scan J Clin Lab Invest, 2011, 71(3): 232-239. doi: 10.3109/00365513.2011.557086
[24]	Nyman U, Berg U, Grubb A, et al. GFR estimation in children-age-adjusted creatinine makes the adult Lund-Malmö equation applicable in children and facilitates automatic GFR reporting from the clinical laboratory[J]. Lakartidningen, 2021, 118: 20134.
[25]	Gowrishankar M, VanderPluym C, Robert C, et al. Value of serum cystatin C in estimating renal function in children with non-renal solid organ transplantation[J]. Pediatr Transplant, 2015, 19(1): 27-34. doi: 10.1111/petr.12381 pmid: 25377124
[26]	Podracka L, Feber J, Lepage N, et al. Intra-individual variation of cystatin C and creatinine in pediatric solid organ transplant recipients[J]. Pediatr Transplant, 2010, 9(1): 28-32. doi: 10.1111/j.1399-3046.2005.00235.x
[27]	Huidobro E JP, Guzmán AM, Tagle R. Use of cystatin C to estimate glomerular filtration rate[J]. Rev Med Chil, 2021, 149(1): 98-102. doi: 10.4067/S0034-98872021000100098
[28]	Zheng K, Gong M, Qin Y, et al. Validation of glomerular filtration rate-estimating equations in Chinese children[J]. PloS One, 2017, 12(7): e0180565.
[29]	Feldman HI, Briggs JP. Race and the estimation of GFR: getting it right[J]. J Am Soc Nephrol, 2021, 32(6): 1269-1270. doi: 10.1681/ASN.2021020206 pmid: 33837121

估算公式	表达式/mL·(min·1.73 m²)^-1
改良Schwartz	0.413×身高/cm·Scr(mg·dL ^-1)^-1
CAPA	130×CysC^-1.069×年龄^0.117-7
Counahan-Barratt	0.43×身高cm·Scr(mg·dL^-1)^-1
Filler	91.62×CysC^-1.123/mg·L ^-1
CKD-EPI-Scr 2009 男性 Scr≤0.9/mg·dL^-1 Scr >0.9/mg·dL ^-1 女性 Scr≤0.7/mg·dL^-1 Scr >0.7/mg·dL^-1	141×(Scr/0.9)^-0.411×0.993^年龄 141×(Scr/0.9)^-1.209×0.993^年龄 141×(Scr/0.7)^-0.329×0.993^年龄 141×(Scr/0.7)^-1.209×0.993^年龄
CKD-EPI-CysC 2012 CysC≤0.8/mg·dL^-1 CysC >0.8/mg·dL^-1	133×(CysC/0.8)^-0.499×0.996^年龄×0.932^女性 133×(CysC/0.8)^-1.328×0.996^年龄×0.932^女性
LMR18	LMR18=e^{X-0.0158×max（年龄；18）+0.438×ln[max（年龄；18）]}
男性 ln（$(\widehat{C r})$）=ln（Cr）+0.259×(18-年龄)-0.543× ln(18/年龄)-0.00763×(18²-年龄²)+0.0000790×(18³-年龄³)
$(\widehat{C r})$<180 /μmol·L^-1 $(\widehat{C r})$≥180 /μmol·L^-1	X=2.56+0.00968×(180-$(\widehat{C r})$) X=2.56-0.926×ln($(\widehat{C r})$/180)
女性 ln（$(\widehat{C r})$）=ln（Cr）+0.177×(18-年龄)-0.223× ln(18/年龄)-0.00596×(18²-年龄²)+0.0000686×(18³-年龄³)
$(\widehat{C r})$<150μmol·L^-1 $(\widehat{C r})$≥150 /μmol·L^-1	X=2.50+0.0121×(150-$(\widehat{C r})$) X=2.50-0.926×ln（$(\widehat{C r})$/150）
FAS	FAS-eGFR=107.3·(Scr/Q^#)^-1

性别	例数	年龄/岁	Scr/μmol·L^-1	CysC/mg·L^-1	身高/cm	体重/kg
男性	56	17.0(16.0~17.0)	78.2(65.0~91.9)	1.1(0.9~1.3)	172.9±5.7	68.6±15.7
女性	32	16.0(16.0~18.0)	62.0(51.8~88.5)	1.1(0.8~1.9)	165.2±5.6	56.5±8.5
统计量		Z=0.35	Z=0.55	Z=1.32	t=6.15	t=4.01
P		0.730	0.582	0.191	<0.001	<0.001

估算公式	eGFR	Pearson相关
估算公式	eGFR	r值	P
改良Schwartz	83.4±31.0	0.664	<0.001
CAPA	160.2±72.2	0.396	<0.001
Counahan-Barratt	84.9±37.6	0.664	<0.001
Filler	86.8±32.3	0.394	<0.001
CKD-EPI-Scr2009	110.7±37.1	0.732	<0.001
CKD-EPI-CysC2012	80.6±36.4	0.443	<0.001
LMR18	82.8±28.2	0.708	<0.001
FAS	95.1±34.0	0.678	<0.001

估算公式	偏倚	精确性/%	准确性/%
改良Schwartz	-10.05	25.61	63.64
CAPA	66.75	65.83	30.68
Counahan-Barratt	-6.62	26.16	62.50
Filler	-8.54	38.43	45.45
CKD-EPI-Scr2009	17.29	25.73	53.41
CKD-EPI-CysC2012	-12.87	36.14	45.45
LMR18	-10.63	22.94	73.86
FAS	1.69	26.41	61.36

估算公式	最佳截断值	AUC	95%CI	约登指数	灵敏度/%	特异度/%
改良Schwartz	57.91	0.89	0.77~1.00	0.72	93.20	78.57
CAPA	76.90	0.82	0.67~0.97	0.60	95.90	64.29
Counahan-Barratt	60.30	0.89	0.77~1.00	0.72	93.20	78.57
Filler	41.30	0.82	0.67~0.97	0.60	95.90	64.29
CKD-EPI-Scr2009	87.06	0.91	0.82~1.00	0.71	91.90	78.57
CKD-EPI-CysC2012	36.23	0.82	0.67~0.97	0.60	95.90	64.29
LMR18	76.71	0.89	0.78~1.00	0.68	82.40	85.71
FAS	81.77	0.89	0.77~1.00	0.71	85.10	85.71

Comparison of different estimation formulas of glomerular filtration rate in children aged 15-18 years with chronic kidney disease

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 6

References 29

Related Articles 15

Metrics

Comments

Recommended 0

[1]	LIN Jinfeng, CHEN Yi, DENG Yan, FENG Ai, HUANG Juan, CHEN Lizhu, XIE Jingqi, NIE Xiaojing. A comparative study on the detection of anti-Nephrin antibodies in children's nephrotic syndrome by chemiluminescence method and cell-based assay [J]. Journal of Clinical Pediatrics, 2026, 44(8): 682-689.
[2]	ZHENG Fangyuan, WANG Miao, DING Mingming, LU Aidong, JIA Yueping, ZENG Huimin, ZHANG Leping. Next-generation sequencing identified gene variants and their prognostic impact in pediatric Philadelphia chromosome positive acute lymphoblastic leukemia [J]. Journal of Clinical Pediatrics, 2026, 44(8): 690-697.
[3]	ZHANG Xiao, FANG Hongjun, KUANG Xiaojun, WANG Lijuan, WU Zhao, JIANG Sha, LI Pei, WU Liwen. Analysis of the clinical and electrophysiological characteristics of atonic seizures in children [J]. Journal of Clinical Pediatrics, 2026, 44(8): 698-704.
[4]	WANG Mengqian, YANG Hui. Case series analysis of 13 intestinal Behcet’s syndrome in children [J]. Journal of Clinical Pediatrics, 2026, 44(8): 705-711.
[5]	WU Xirong, GAO Qi, GUO Siyuan, YIN Qingqin, QIN Qiang, YIN Ju, JIAO Anxia, CHEN Chenghao, WU Di, WANG Bei, DUAN Xiaomin, PENG Yun, XU Baoping, GAO Liwei. Clinical characteristics and prognosis of pulmonary mucormycosis in children with diabetes mellitus [J]. Journal of Clinical Pediatrics, 2026, 44(8): 712-720.
[6]	HAN Yanan, GE Lanlan, CUI Jieyuan. A case report of branchio-oto-renal syndrome caused by EYA1 gene variant with a 6-year follow-up [J]. Journal of Clinical Pediatrics, 2026, 44(8): 721-726.
[7]	SHI Jiayi, GAO Chunlin, JIA Lili, LU Yunyun, SUN Tao, ZHU Xiaodong, XIA Zhengkun, ZHANG Pei. Phenotypic characteristics and prognostic analysis of a pedigree with childhood isolated nephrotic syndrome caused by compound heterozygous mutations in the COQ2 gene [J]. Journal of Clinical Pediatrics, 2026, 44(8): 727-732.
[8]	Rachel Rosen, Osvaldo Borrelli, Christophe Faure, Katja Karrento, Usha Krishnan, Samuel Nurko, Nathalie Rommel, Alan Silverman, Michiel van Wijk, Marc Benninga (Author), Chinese Medical Association Parenteral and Enteral Nutrition Branch Pediatrics Group, The Subspecialty Group of Gastroenterology, The Society of Pediatric, Chinese Medical Association, Gastroenterology Group, Pediatrician Branch, Chinese Medical Doctor Association (Translator). Core interpretation and explanation of Rome Ⅴ diagnostic criteria: upper gastrointestinal disorders of gut-brain interaction in children and adolescents [J]. Journal of Clinical Pediatrics, 2026, 44(7): 595-608.
[9]	Carlo Di Lorenzo, Miguel Saps, Bruno P. Chumpitazi, Shaman Rajindrajith, Annamaria Staiano, Nikhil Thapar, Miranda van Tilburg, Carlos Velasco-Benítez, Arine Vlieger (Author), Chinese Medical Association Parenteral and Enteral Nutrition Branch Pediatrics Group, The Subspecialty Group of Gastroenterology, The Society of Pediatric, Chinese Medical Association, Gastroenterology Group, Pediatrician Branch, Chinese Medical Doctor Association (Translator). Core interpretation and explanation of Rome Ⅴ diagnostic criteria: lower and biliary disorders of gut-brain interaction in children and adolescents [J]. Journal of Clinical Pediatrics, 2026, 44(7): 609-621.
[10]	LI Xufeng, TANG Haoxun, LI Xingjun, ZHANG Lize, GAO Chenqing, ZHAO Shunying, LIU Jianhua. Clinical characteristics, chest CT imaging phenotypes, and their correlation with prognosis in 76 children with Chlamydia pneumoniae pneumonia [J]. Journal of Clinical Pediatrics, 2026, 44(7): 622-627.
[11]	WANG Zhen, SHAO Jingbo, ZHANG Na, XIA Min, ZHU Jiashi, DU Chengkan, LI Hong. Factors influencing long-term recurrence in pediatric acute lymphoblastic leukemia patients with low-risk disease at initial diagnosis: a five-year follow-up analysis of 254 cases from a single center [J]. Journal of Clinical Pediatrics, 2026, 44(7): 628-635.
[12]	GUO Xuemei, XUE Yao, WANG Yongren, RONG Liucheng, FANG Yongjun, LIN Rufeng. Clinical features and prognosis of childhood acute myeloid leukemia with CBFA2T3::GLIS2 fusion [J]. Journal of Clinical Pediatrics, 2026, 44(7): 636-643.
[13]	YANG Lijun, FU Dongxia, CUI Yan, YANG Junmei, ZHANG Liming. Clinical manifestation and genetic analysis of CHARGE syndrome caused by CHD7 gene variation [J]. Journal of Clinical Pediatrics, 2026, 44(7): 644-650.
[14]	HU Yan, YANG Fan, LIANG Aimin, MAO Meng. Identification and management of faltering growth in children: insights from the 13th International Conference on Nutrition and Growth [J]. Journal of Clinical Pediatrics, 2026, 44(6): 485-488.
[15]	LIU Ziyao, WANG Congying, WANG Hongmao, ZHANG Mingming, XU Yingjie, LAI Jianming, NIU Wenquan, LI Xiaohui. Early differentiation of Kawasaki disease with joint symptoms and systemic juvenile idiopathic arthritis with Kawasaki disease-like symptoms: a single-center retrospective study [J]. Journal of Clinical Pediatrics, 2026, 44(6): 489-498.