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Licensed Unlicensed Requires Authentication Published by De Gruyter March 6, 2023

Imprecision remains to be improved in the measurement of serum cystatin C with heterogeneous systems

  • Jie Zeng , Li Zhang , Jiangtao Zhang , Weiyan Zhou ORCID logo , Tianjiao Zhang , Jing Wang , Haijian Zhao and Chuanbao Zhang ORCID logo EMAIL logo

Abstract

Objectives

Except for the large bias of some measurement systems for serum cystatin C (CysC) measurements, unacceptable imprecision has been observed for the heterogenous system. This study analyzed the external quality assessment (EQA) results in 2018–2021 to provide an insight into the imprecision of CysC assays.

Methods

Five EQA samples were sent to participating laboratories every year. Participants were divided into reagent/calibrator-based peer groups, for which the robust mean of each sample and robust coefficient of variation (CV) were calculated by Algorithm A from ISO 13528. Peers with more than 12 participants per year were selected for further analysis. The limit of CV was determined to be 4.85% based on clinical application requirements. The concentration-related effect on CVs was investigated using logarithmic curve fitting; the difference in medians and robust CVs between instrument-based subgroups was also evaluated.

Results

The total number of participating laboratories increased from 845 to 1,695 in four years and heterogeneous systems remained the mainstream (≥85%). Of 18 peers with ≥12 participants, those using homogeneous systems showed relatively steady and small CVs over four years, with the mean four-year CVs ranging from 3.21 to 3.68%. Some peers using heterogenous systems showed reduced CVs over four years, while 7/15 still had unacceptable CVs in 2021 (5.01–8.34%). Six peers showed larger CVs at the low or high concentrations, and some instrument-based subgroups presented greater imprecision than others.

Conclusions

More efforts should be made to improve the imprecision of heterogeneous systems for CysC measurement.


Corresponding author: Chuanbao Zhang, National Center for Clinical Laboratories, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology, Beijing Engineering Research Center of Laboratory Medicine, Institute of Geriatric Medicine, Beijing, P.R. China, Phone: +86 010-58115059, Fax: +86 010-65132968, E-mail:
Jie Zeng and Li Zhang contributed equally to this work.

Funding source: National Key Research and Development Program of China

Award Identifier / Grant number: 2022YFC3602301

  1. Research funding: National Key Research and Development Program of China: No. 2022YFC3602301.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: Not applicable.

References

1. Eckardt, KU, Coresh, J, Devuyst, O, Johnson, RJ, Köttgen, A, Levey, AS, et al.. Evolving importance of kidney disease: from subspecialty to global health burden. Lancet 2013;382:158–69. https://doi.org/10.1016/s0140-6736(13)60439-0.Search in Google Scholar

2. Vijay, P, Lal, BB, Sood, V, Khanna, R, Alam, S. cystatin C: best biomarker for acute kidney injury and estimation of glomerular filtration rate in childhood cirrhosis. Eur J Pediatr 2021;180:3287–95. https://doi.org/10.1007/s00431-021-04076-1.Search in Google Scholar PubMed

3. Lees, JS, Welsh, CE, Celis-Morales, CA, Mackay, D, Lewsey, J, Gray, SR, et al.. Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease. Nat Med 2019;25:1753–60. https://doi.org/10.1038/s41591-019-0627-8.Search in Google Scholar PubMed PubMed Central

4. Casal, MA, Nolin, TD, Beumer, JH. Estimation of kidney function in oncology: implications for anticancer drug selection and dosing. Clin J Am Soc Nephrol 2019;14:587–95. https://doi.org/10.2215/cjn.11721018.Search in Google Scholar PubMed PubMed Central

5. Lameire, NH, Levin, A, Kellum, JA, Cheung, M, Jadoul, M, Winkelmayer, WC, et al.. Harmonizing acute and chronic kidney disease definition and classification: report of a kidney disease: improving global Outcomes (KDIGO) consensus conference. Kidney Int 2021;100:516–26. https://doi.org/10.1016/j.kint.2021.06.028.Search in Google Scholar PubMed

6. Levey, AS, Coresh, J, Tighiouart, H, Greene, T, Inker, LA. Measured and estimated glomerular filtration rate: current status and future directions. Nat Rev Nephrol 2020;16:51–64. https://doi.org/10.1038/s41581-019-0191-y.Search in Google Scholar PubMed

7. Levey, AS, Titan, SM, Powe, NR, Coresh, J, Inker, LA. Kidney disease, race, and GFR estimation. Clin J Am Soc Nephrol 2020;15:1203–12. https://doi.org/10.2215/cjn.12791019.Search in Google Scholar

8. Shlipak, MG, Tummalapalli, SL, Boulware, LE, Grams, ME, Ix, JH, Jha, V, et al.. The case for early identification and intervention of chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int 2021;99:34–47. https://doi.org/10.1016/j.kint.2020.10.012.Search in Google Scholar PubMed

9. Kashani, K, Rosner, MH, Ostermann, M. Creatinine: from physiology to clinical application. Eur J Intern Med 2020;72:9–14. https://doi.org/10.1016/j.ejim.2019.10.025.Search in Google Scholar PubMed

10. Kimura, K, Morita, H, Daimon, M, Horio, M, Kawata, T, Nakao, T, et al.. Utility of cystatin C for estimating glomerular filtration rate in patients with muscular dystrophy. Int Heart J 2016;57:386–8. https://doi.org/10.1536/ihj.15-461.Search in Google Scholar PubMed

11. Li, DY, Yin, WJ, Zhou, LY, Ma, RR, Liu, K, Hu, C, et al.. Utility of cystatin C-based equations in patients undergoing dialysis. Clin Chim Acta 2018;485:282–7. https://doi.org/10.1016/j.cca.2018.07.010.Search in Google Scholar PubMed

12. Delgado, C, Baweja, M, Crews, DC, Eneanya, ND, Gadegbeku, CA, Inker, LA, et al.. A unifying approach for GFR estimation: recommendations of the NKF-ASN task force on reassessing the inclusion of race in diagnosing kidney disease. J Am Soc Nephrol 2021;32:2994–3015. https://doi.org/10.1681/asn.2021070988.Search in Google Scholar

13. Eckfeldt, JH, Karger, AB, Miller, WG, Rynders, GP, Inker, LA. Performance in measurement of serum cystatin C by laboratories participating in the College of American Pathologists 2014 CYS survey. Arch Pathol Lab Med 2015;139:888–93. https://doi.org/10.5858/arpa.2014-0427-cp.Search in Google Scholar

14. Grubb, A, Horio, M, Hansson, LO, Björk, J, Nyman, U, Flodin, M, 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. Clin Chem 2014;60:974–86. https://doi.org/10.1373/clinchem.2013.220707.Search in Google Scholar PubMed

15. Bargnoux, AS, Kuster, N, Delatour, V, Delanaye, P, González-Antuña, A, Cristol, JP, et al.. Reference method and reference material are necessary tools to reveal the variability of cystatin C assays. Arch Pathol Lab Med 2016;140:117–8. https://doi.org/10.5858/arpa.2015-0198-le.Search in Google Scholar

16. Karger, AB, Long, T, Inker, LA, Eckfeldt, JH. Improved performance in measurement of serum cystatin C by laboratories participating in the College of American Pathologists’ 2019 CYS survey. Arch Pathol Lab Med 2022;146:1218–23. https://doi.org/10.5858/arpa.2021-0306-cp.Search in Google Scholar PubMed

17. Bargnoux, AS, Piéroni, L, Cristol, JP, Kuster, N, Delanaye, P, Carlier, MC, et al.. Multicenter evaluation of cystatin C measurement after assay standardization. Clin Chem 2017;63:833–41. https://doi.org/10.1373/clinchem.2016.264325.Search in Google Scholar PubMed

18. China National Accreditation Service for Conformity Assessment. CNAS-GL003: Guidance on evaluating the homogeneity and stability of samples used for proficiency testing. Beijing, China: CNAS; 2018.Search in Google Scholar

19. International Organization for Standardization. ISO 13528: statistical methods for use in proficiency testing by interlaboratory comparison. Geneva, Switzerland: ISO; 2022.Search in Google Scholar

20. Aarsand, AK, Fernandez-Calle, P, Webster, C, Coskun, A, Gonzales-Lao, E, Diaz-Garzon, J, et al.. The EFLM biological variation database. Available from: https://biologicalvariation.eu/ [Accessed Nov 2022].Search in Google Scholar

21. Miller, WG, Myers, GL. Commutability still matters. Clin Chem 2013;59:1291–3. https://doi.org/10.1373/clinchem.2013.208785.Search in Google Scholar PubMed

22. Miller, WG, Myers, GL, Rej, R. Why commutability matters. Clin Chem 2006;52:553–4. https://doi.org/10.1373/clinchem.2005.063511.Search in Google Scholar PubMed

23. Xiao, YL, Zhang, CB, Zhao, HJ, Kang, FF, Wang, W, Zhong, K, et al.. Application of ISO 13528 robust statistical method for external quality assessment of blood glucose measurements in China. Accred Qual Assur 2014;19:397–401. https://doi.org/10.1007/s00769-014-1078-z.Search in Google Scholar

24. Zhang, K, Lin, G, Wang, L, Sun, Y, Zhang, R, Xie, J, et al.. Harmonization of results has not been fully achieved for serum immunoglobulin measurements. Clin Chem Lab Med 2015;53:e309–e12. https://doi.org/10.1515/cclm-2015-0145.Search in Google Scholar PubMed

25. Stepman, HC, Tiikkainen, U, Stöckl, D, Vesper, HW, Edwards, SH, Laitinen, H, et al.. Measurements for 8 common analytes in native sera identify inadequate standardization among 6 routine laboratory assays. Clin Chem 2014;60:855–63. https://doi.org/10.1373/clinchem.2013.220376.Search in Google Scholar PubMed PubMed Central

Received: 2022-12-21
Accepted: 2023-02-03
Published Online: 2023-03-06
Published in Print: 2023-07-26

© 2023 Walter de Gruyter GmbH, Berlin/Boston

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