Skip to main content
SpringerLink
Log in

Performance of the creatinine and cystatin C-based equations for estimation of GFR in Chinese patients with chronic kidney disease

  • Original Article
  • Published:
Clinical and Experimental Nephrology Aims and scope Submit manuscript

Abstract

Background

Currently, creatinine- or cystatin C-based glomerular filtration rate (GFR) estimation equation has been recommended to assess GFR in CKD patients. However, it is still obscure whether those equations performed consistently outstandingly in Chinese population.

Methods

The equations were validated in a population totaling 632 participants (mean age 61.6 ± 12.3 years). The estimated GFR (eGFR) calculated separately by six equations (C-MDRD, Ccys, Cscr–cys, CKD-EPIscr, CKD-EPIcys, and CKD-EPIscr–cys equations) was compared with the reference GFR (rGFR) measured by the 99mTc-DTPA renal dynamic imaging method. Participants were divided into age and rGFR specific subgroups.

Results

CKD-EPIscr–cys equation had a larger area under receiver operating characteristic curve (ROCAUC) and relative higher sensitivity (79.8 %) and specificity (93 %) to diagnose CKD. CKD-EPIscr–cys and CKD-EPIcys equations appeared to be more accurate with higher proportion of eGFR within 30 % of rGFR (P 30) value. Those two equations performed as well in older people as in the younger population. The CKD-EPIscr–cys equation acquired the highest P 30 (80.9 %) in subgroups with rGFR ≥60 mL/min/1.73 m2, while the CKD-EPIcys equation yielded the best performance in the rGFR <60 mL/min/1.73 m2 subgroup.

Conclusion

CKD-EPIscr–cys formula had better capability to accurately evaluate GFR in the participants CKD stages 1–2 in Chinese ethnic. The application of the cystatin C-based equations may be the optimal one for patients of moderately to severely injured GFR. Considering the accuracy in the entire range of participants less ideally, the additional of the Chinese racial factor is assumed to be essential.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2095–128.

    Article  PubMed  Google Scholar 

  2. Zhang L, Wang F, Wang L, Wang W, Liu B, Liu J, et al. Prevalence of chronic kidney disease in China: a cross-sectional survey. Lancet. 2012;379(9818):815–22.

    Article  PubMed  Google Scholar 

  3. Ferguson MA, Waikar SS. Established and emerging markers of kidney function. Clin Chem. 2012;58(4):680–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Florkowski CM, Chew-Harris JS. Methods of estimating GFR—different equations including CKD-EPI. Clin Biochem Rev. 2011;32(2):75–9.

    PubMed  PubMed Central  Google Scholar 

  5. Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney function—measured and estimated glomerular filtration rate. N Engl J Med. 2006;354(23):2473–83.

    Article  CAS  PubMed  Google Scholar 

  6. Tangri N, Stevens LA, Schmid CH, Zhang YL, Beck GJ, Greene T, et al. Changes in dietary protein intake has no effect on serum cystatin C levels independent of the glomerular filtration rate. Kidney Int. 2011;79(4):471–7.

    Article  CAS  PubMed  Google Scholar 

  7. Hojs R, Bevc S, Ekart R, Gorenjak M, Puklavec L. Serum cystatin C-based formulas for prediction of glomerular filtration rate in patients with chronic kidney disease. Nephron Clin Pract. 2010;114(2):c118–26.

    Article  CAS  PubMed  Google Scholar 

  8. Macdonald J, Marcora S, Jibani M, Roberts G, Kumwenda M, Glover R, et al. GFR estimation using cystatin C is not independent of body composition. Am J Kidney Dis. 2006;48(5):712–9.

    Article  CAS  PubMed  Google Scholar 

  9. Grubb A, Nyman U, Bjork J. Improved estimation of glomerular filtration rate (GFR) by comparison of eGFR cystatin C and eGFR creatinine. Scand J Clin Lab Invest. 2012;72(1):73–7.

    Article  CAS  PubMed  Google Scholar 

  10. Grubb A. Non-invasive estimation of glomerular filtration rate (GFR). The Lund model: simultaneous use of cystatin C- and creatinine-based GFR-prediction equations, clinical data and an internal quality check. Scand J Clin Lab Invest. 2010;70(2):65–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Matsuo S, Imai E, Horio M, Yasuda Y, Tomita K, Nitta K, et al. Revised equations for estimated GFR from serum creatinine in Japan. Am J Kidney Dis. 2009;53(6):982–92.

    Article  CAS  PubMed  Google Scholar 

  12. Teo BW, Xu H, Wang D, Li J, Sinha AK, Shuter B, et al. GFR estimating equations in a multiethnic Asian population. Am J Kidney Dis. 2011;58(1):56–63.

    Article  PubMed  Google Scholar 

  13. Horio M, Imai E, Yasuda Y, Watanabe T, Matsuo S. Modification of the CKD epidemiology collaboration (CKD-EPI) equation for Japanese: accuracy and use for population estimates. Am J Kidney Dis. 2010;56(1):32–8.

    Article  PubMed  Google Scholar 

  14. Ma YC, Zuo L, Chen JH, Luo Q, Yu XQ, Li Y, et al. Improved GFR estimation by combined creatinine and cystatin C measurements. Kidney Int. 2007;72(12):1535–42.

    Article  CAS  PubMed  Google Scholar 

  15. Ma YC, Zuo L, Chen JH, Luo Q, Yu XQ, Li Y, et al. Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J Am Soc Nephrol. 2006;17(10):2937–44.

    Article  PubMed  Google Scholar 

  16. Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med. 2012;367(1):20–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Du X, Liu L, Hu B, Wang F, Wan X, Jiang L, et al. Is the Chronic Kidney Disease Epidemiology Collaboration four-level race equation better than the cystatin C equation? Nephrology (Carlton). 2012;17(4):407–14.

    Article  CAS  Google Scholar 

  18. Lamb EJ, Tomson CR, Roderick PJ. Clinical Sciences Reviews Committee of the Association for Clinical B. Estimating kidney function in adults using formulae. Ann Clin Biochem. 2005;42(Pt 5):321–45.

    Article  PubMed  Google Scholar 

  19. Kilbride HS, Stevens PE, Eaglestone G, Knight S, Carter JL, Delaney MP, et al. Accuracy of the MDRD (Modification of Diet in Renal Disease) study and CKD-EPI (CKD Epidemiology Collaboration) equations for estimation of GFR in the elderly. Am J Kidney Dis. 2013;61(1):57–66.

    Article  PubMed  Google Scholar 

  20. Zhu Y, Ye X, Zhu B, Pei X, Wei L, Wu J, et al. Comparisons between the 2012 new CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equations and other four approved equations. PLoS One. 2014;9(1):e84688.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Earley A, Miskulin D, Lamb EJ, Levey AS, Uhlig K. Estimating equations for glomerular filtration rate in the era of creatinine standardization: a systematic review. Ann Intern Med. 2012;156(11):785–95.

    Article  PubMed  Google Scholar 

  22. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604–12.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Lane BR, Demirjian S, Weight CJ, Larson BT, Poggio ED, Campbell SC. Performance of the chronic kidney disease-epidemiology study equations for estimating glomerular filtration rate before and after nephrectomy. J Urol. 2010;183(3):896–901.

    Article  PubMed  Google Scholar 

  24. Cirillo M, Lombardi C, Luciano MG, Bilancio G, Anastasio P, De Santo NG. Estimation of GFR: a comparison of new and established equations. Am J Kidney Dis. 2010;56(4):802–4.

    Article  PubMed  Google Scholar 

  25. Eriksen BO, Mathisen UD, Melsom T, Ingebretsen OC, Jenssen TG, Njolstad I, et al. Cystatin C is not a better estimator of GFR than plasma creatinine in the general population. Kidney Int. 2010;78(12):1305–11.

    Article  CAS  PubMed  Google Scholar 

  26. Salgado JV, Neves FA, Bastos MG, Franca AK, Brito DJ, Santos EM, et al. Monitoring renal function: measured and estimated glomerular filtration rates—a review. Braz J Med Biol Res. 2010;43(6):528–36.

    Article  CAS  PubMed  Google Scholar 

  27. Yap M, Lamarche J, Peguero A, Courville C. Serum cystatin C versus serum creatinine in the estimation of glomerular filtration rate in rhabdomyolysis. J Ren Care. 2011;37(3):155–7.

    Article  PubMed  Google Scholar 

  28. Cai X, Long Z, Lin L, Feng Y, Zhou N, Mai Q. Serum cystatin C is an early biomarker for assessment of renal function in burn patients. Clin Chem Lab Med. 2012;50(4):667–71.

    Article  CAS  PubMed  Google Scholar 

  29. Dharnidharka VR, Kwon C, Stevens G. Serum cystatin C is superior to serum creatinine as a marker of kidney function: a meta-analysis. Am J Kidney Dis. 2002;40(2):221–6.

    Article  CAS  PubMed  Google Scholar 

  30. Roos JF, Doust J, Tett SE, Kirkpatrick CM. Diagnostic accuracy of cystatin C compared to serum creatinine for the estimation of renal dysfunction in adults and children–a meta-analysis. Clin Biochem. 2007;40(5–6):383–91.

    Article  CAS  PubMed  Google Scholar 

  31. Kumaresan R, Giri P. A comparison of serum cystatin C and creatinine with glomerular filtration rate in Indian patients with chronic kidney disease. Oman Med J. 2011;26(6):421–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Horio M, Imai E, Yasuda Y, Watanabe T, Matsuo S. Collaborators developing the Japanese equation for estimated GFR. GFR estimation using standardized serum cystatin C in Japan. Am J Kidney Dis. 2013;61(2):197–203.

    Article  CAS  PubMed  Google Scholar 

  33. Ye X, Wei L, Pei X, Zhu B, Wu J, Zhao W. Application of creatinine- and/or cystatin C-based glomerular filtration rate estimation equations in elderly Chinese. Clin Interv Aging. 2014;9:1539–49.

    PubMed  PubMed Central  Google Scholar 

  34. Schaeffner ES, Ebert N, Delanaye P, Frei U, Gaedeke J, Jakob O, et al. Two novel equations to estimate kidney function in persons aged 70 years or older. Ann Intern Med. 2012;157(7):471–81.

    Article  PubMed  Google Scholar 

  35. Alshaer IM, Kilbride HS, Stevens PE, Eaglestone G, Knight S, Carter JL, et al. External validation of the Berlin equations for estimation of GFR in the elderly. Am J Kidney Dis. 2014;63(5):862–5.

    Article  PubMed  Google Scholar 

  36. Liu X, Ma H, Huang H, Wang C, Tang H, Li M, et al. Is the Chronic Kidney Disease Epidemiology Collaboration creatinine–cystatin C equation useful for glomerular filtration rate estimation in the elderly? Clin Interv Aging. 2013;8:1387–91.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Shlipak MG, Mattes MD, Peralta CA. Update on cystatin C: incorporation into clinical practice. Am J Kidney Dis. 2013;62(3):595–603.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Kidney Disease Improving Global Outcomes. Clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int. 2013;3(Suppl):1–150.

    Google Scholar 

  39. Li Q, Zhang CL, Fu ZL, Wang RF, Ma YC, Zuo L. Development of formulae for accurate measurement of the glomerular filtration rate by renal dynamic imaging. Nucl Med Commun. 2007;28(5):407–13.

    Article  PubMed  Google Scholar 

  40. Blaufox MD, Aurell M, Bubeck B, Fommei E, Piepsz A, Russell C, et al. Report of the Radionuclides in Nephrourology Committee on renal clearance. J Nucl Med. 1996;37(11):1883–90.

    CAS  PubMed  Google Scholar 

  41. Soveri I, Berg UB, Bjork J, Elinder CG, Grubb A, Mejare I, et al. Measuring GFR: a systematic review. Am J Kidney Dis. 2014;64(3):411–24.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by grants from Chinese Society of Nephrology (14050430580), Natural Science Foundation of Shanghai (124119a7802), Shanghai Minhang Committee of Science and Technology (2013MHZ015).

Author information

Authors and Affiliations

  1. Division of Nephrology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China

    Min Yang, Guang Xu, Lilu Ling, Jianying Niu & Yong Gu

  2. Division of Nuclear Medicine, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China

    Tong Lu

  3. Division of Nephrology, Nanjing First Hospital, Nanjing Medical University, Chang Le Road 68, Nanjing, 210006, China

    Xin Du

  4. Division of Nephrology, Huashan Hospital, Shanghai Fifth People’s Hospital, Fudan University, 801 Heqing Road, Minhang District, Shanghai, 200240, China

    Yong Gu

Authors
  1. Min Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guang Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lilu Ling
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jianying Niu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tong Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xin Du
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yong Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Xin Du or Yong Gu.

Ethics declarations

Conflict of interest

The authors of this manuscript declare no competing interests.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, M., Xu, G., Ling, L. et al. Performance of the creatinine and cystatin C-based equations for estimation of GFR in Chinese patients with chronic kidney disease. Clin Exp Nephrol 21, 236–246 (2017). https://doi.org/10.1007/s10157-016-1273-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10157-016-1273-9

Keywords

Search

Navigation