Abstract
Objectives
A trueness-based EQA/PT program for high density lipoprotein cholesterol (HDL-C) was initiated. We analyzed the 4 year EQA/PT program to overview the measurement standardization for HDL-C in China.
Methods
Two levels of freshly frozen, commutable serum external quality assessment/proficiency testing (EQA/PT) materials were prepared and determined by reference measurement procedure each year. The samples were delivered to clinical laboratories and measured 15 times in 3 days. The precision [coefficient of variation (CV)], trueness (bias), and accuracy [total error (TE)] were calculated and used to evaluate measurement performance. The pass rates of individual laboratories and peer groups were analyzed using the acceptable performance from the National Cholesterol Education Program (NCEP) and biological variation as the evaluation criteria.
Results
More than 60% of laboratories use heterogeneous systems, and there was a decrease in the percentage from 2016 to 2019. About 95, 78, and 33% of laboratories met the minimum, desirable and optimum TE criteria derived from biological variation. The pass rates were 87.0% (84.7–88.8%), 58.7% (55.3–62.4%), and 97.3% (95.6–98.3%) that met the acceptable performance of TE, bias, and CV of NCEP. The homogeneous systems had higher pass rates of TE, bias, and CV than the heterogeneous groups in 2016, but they did not show apparent advantages in 2017–2019.
Conclusions
The trueness-based EQA/PT program can be used to evaluate the accuracy, reproducibility, and trueness of results. For some IVD manufacturers and individual laboratories, accuracy, especially trueness, are still problems. Efforts should be made to improve the situation and achieve better HDL-C measurement standardization.
Funding source: Beijing Natural Science Found
Award Identifier / Grant number: 7212087
Funding source: CAMS Innovation Fund for Medical Sciences
Award Identifier / Grant number: 2021-I2M-1-050
Funding source: Beijing’s Golden Bridge Seed Fund Project
-
Research funding: This work was supported by the Beijing Natural Science Found (N0. 7212087), CAMS Innovation Fund for Medical Sciences (No. 2018-I2M-1-002), and Excellent training project of Beijing Dongcheng district.
-
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Competing interests: Authors state no conflict of interest.
-
Informed consent: Informed consent was obtained from all individuals included in this study.
-
Ethical approval: The local Institutional Review Board deemed the study exempt from review.
References
1. van Deventer, HE, Miller, WG, Myers, GL, Sakurabayashi, I, Bachmann, LM, Caudill, SP, et al.. Non-HDL cholesterol shows improved accuracy for cardiovascular risk score classification compared to direct or calculated LDL cholesterol in a dyslipidemic population. Clin Chem 2011;57:490–501. https://doi.org/10.1373/clinchem.2010.154773.Search in Google Scholar
2. Rader, DJ, Hovingh, GK. HDL and cardiovascular disease. Lancet 2014;384:618–25. https://doi.org/10.1016/s0140-6736(14)61217-4.Search in Google Scholar
3. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III). JAMA 2001;285:2486–97. https://doi.org/10.1001/jama.285.19.2486.Search in Google Scholar PubMed
4. Waldman, B, Jenkins, AJ, Davis, TM, Taskinen, MR, Scott, R, O’Connell, RL, et al.. HDL-C and HDL-C/ApoA-I predict long-term progression of glycemia in established type 2 diabetes. Diabetes Care 2014;37:2351–8. https://doi.org/10.2337/dc13-2738.Search in Google Scholar PubMed
5. Borai, A, Ichihara, K, Al Masaud, A, Tamimi, W, Bahijri, S, Armbuster, D, et al.. Establishment of reference intervals of clinical chemistry analytes for the adult population in Saudi Arabia: a study conducted as a part of the IFCC global study on reference values. Clin Chem Lab Med 2016;54:843–55. https://doi.org/10.1515/cclm-2015-0490.Search in Google Scholar PubMed
6. Zhang, J, Luo, W, Zeng, J, Zhang, T, Zhou, W, Zhao, H, et al.. Standardization of measurement procedures for serum uric acid: 8-year experience from category 1 EQA program results in China. Clin Chem Lab Med 2019;57:476–82. https://doi.org/10.1515/cclm-2018-0274.Search in Google Scholar PubMed
7. Wang, J, Wang, Y, Zhang, T, Zeng, J, Zhao, H, Guo, Q, et al.. Evaluation of serum alkaline phosphatase measurement through the 4-year trueness verification program in China. Clin Chem Lab Med 2018;56:2072–8. https://doi.org/10.1515/cclm-2018-0399.Search in Google Scholar PubMed
8. ISO 15189:2012(E). Medical laboratories — requirements for quality and competence. Geneva, Switzerland: International Organization for Standardization; 2012.Search in Google Scholar
9. Plebani, M. External quality assessment programs: past, present and future. Jugosl Med Biohemija 2005;24:201–6. https://doi.org/10.2298/jmh0503201p.Search in Google Scholar
10. ISO/IEC 17043:2010(E). Conformity assessment — general requirements for proficiency testing. Geneva, Switzerland: International Organization for Standardization; 2010.Search in Google Scholar
11. WHO. Laboratory quality management system: handbook. World Health Organization; 2011. Available from: https://www.who.int/ihr/publications/lqms/en/.Search in Google Scholar
12. Miller, WG, Jones, GR, Horowitz, GL, Weykamp, C. Proficiency testing/external quality assessment: current challenges and future directions. Clin Chem 2011;57:1670–80. https://doi.org/10.1373/clinchem.2011.168641.Search in Google Scholar PubMed
13. Jones, GRD, Albarede, S, Kesseler, D, MacKenzie, F, Mammen, J, Pedersen, M, et al.. Analytical performance specifications for external quality assessment – definitions and descriptions. Clin Chem Lab Med 2017;55:949–55. https://doi.org/10.1515/cclm-2017-0151.Search in Google Scholar PubMed
14. Westgard, JO, Carey, RN, Wold, S. Criteria for judging precision and accuracy in method development and evaluation. Clin Chem 1974;20:825–33. https://doi.org/10.1093/clinchem/20.7.825.Search in Google Scholar
15. Ceriotti, F, Fernandez-Calle, P, Klee, GG, Nordin, G, Sandberg, S, Streichert, T, et al.. Criteria for assigning laboratory measurands to models for analytical performance specifications defined in the 1st EFLM strategic conference. Clin Chem Lab Med 2017;55:189–94. https://doi.org/10.1515/cclm-2016-0091.Search in Google Scholar PubMed
16. Sandberg, S, Fraser, CG, Horvath, AR, Jansen, R, Jones, G, Oosterhuis, W, et al.. Defining analytical performance specifications: consensus statement from the 1st strategic conference of the European federation of clinical chemistry and laboratory medicine. Clin Chem Lab Med 2015;53:833–5. https://doi.org/10.1515/cclm-2015-0067.Search in Google Scholar PubMed
17. ISO 13528:2015(E). Statistical methods for use in proficiency testing by interlaboratory comparison. Geneva, Switzerland: International Organization for Standardization; 2015.Search in Google Scholar
18. Clinical and Laboratory Standards Institute (CLSI). Evaluation of commutability of processed samples. Approved guideline, EP 14-A3. Wayne, PA: Clinical and Laboratory Standards Institute; 2014.Search in Google Scholar
19. Zhang, LJ, Zeng, J, Wang, SM, Zhou, WY, Wang, M, Yang, RY, et al.. Matrix effects of the processed materials in high-density lipoprotein cholesterol measurement. Chin J Lab Med 2015;38:737–41.Search in Google Scholar
20. Dong, J, Guo, H, Yang, R, Li, H, Wang, S, Zhang, J, et al.. Serum LDL- and HDL-cholesterol determined by ultracentrifugation and HPLC. J Lipid Res 2011;52:383–8. https://doi.org/10.1194/jlr.d008979.Search in Google Scholar PubMed PubMed Central
21. Zhou, W, Li, H, Dong, J, Wang, S, Yang, R, Zhang, C, et al.. Serum cholesterol measured by isotope dilution liquid chromatography tandem mass spectrometry. Clin Chem Lab Med 2011;49:669–76. https://doi.org/10.1515/cclm.2011.093.Search in Google Scholar PubMed
22. The Joint Committee for Traceability in Laboratory Medicine (JCTLM). Database of higher-order reference materials, measurement methods/procedures and services. Available from: https://www.bipm.org/jctlm/home.do [Accessed 01 Apr 2020].Search in Google Scholar
23. Ellison, SL, Rosslein, M, Williams, A, editors. EURACHEM/CITAC guide CG 4: quantifying uncertainty in analytical measurement, 2nd ed. Czech Republic: EURACHEM; 2000.Search in Google Scholar
24. ISO/IEC Guide 98-3:2008. Uncertainty of measurement – part 3: guide to the expression of uncertainty in measurement (GUM:1995). Geneva: ISO; 2008.Search in Google Scholar
25. Centers for Disease Control. Acceptable performance criteria in LSP. Available from: https://www.cdc.gov/labstandards/lsp.html [Accessed 30 Jun 2022].Search in Google Scholar
26. European Federation of Clinical Chemistry and Laboratory Medicine (EFLM). The EFLM biological variation database. Available from: https://biologicalvariation.eu/search?q=HDL [Accessed 23 May 2022].Search in Google Scholar
27. Wang, J, Wang, Y, Zhang, T, Zeng, J, Zhao, H, Guo, Q, et al.. Evaluation of serum alkaline phosphatase measurement through the 4-year trueness verification program in China. Clin Chem Lab Med 2018;56:2072–8.10.1515/cclm-2018-0399Search in Google Scholar PubMed
28. Yan, Y, Pu, Y, Zeng, J, Zhang, T, Zhou, W, Zhang, J, et al.. Evaluation of serum electrolytes measurement through the 6-year trueness verification program in China. Clin Chem Lab Med 2020;59:107–16. https://doi.org/10.1515/cclm-2020-0355.Search in Google Scholar PubMed
29. Miller, WG, Myers, GL, Sakurabayashi, I, Bachmann, LM, Caudill, SP, Dziekonski, A, et al.. Seven direct methods for measuring HDL and LDL cholesterol compared with ultracentrifugation reference measurement procedures. Clin Chem 2010;56:977–86. https://doi.org/10.1373/clinchem.2009.142810.Search in Google Scholar PubMed PubMed Central
30. Oosterhuis, WP, Theodorsson, E. Total error vs. Measurement uncertainty: revolution or evolution? Clin Chem Lab Med 2016;54:235–9. https://doi.org/10.1515/cclm-2015-0997.Search in Google Scholar PubMed
Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2020-0658).
© 2022 Walter de Gruyter GmbH, Berlin/Boston
