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Analytical performance specifications for trace elements in biological fluids derived from six countries federated external quality assessment schemes over 10 years

  • Josiane Arnaud , Cas Weykamp EMAIL logo , Ross Wenzel ORCID logo , Marina Patriarca , Montserrat González-Estecha , Liesbeth Janssen , Ma’atem Beatrice Fofou-Caillierez , Montserrat Ventura Alemany , Valeria Patriarca , Irene de Graaf , Renaud Persoons , Mariona Panadès , Bernard China , Marieke te Winkel , Hans van der Vuurst and Marc Thelen ORCID logo
Published/Copyright: July 22, 2024

Abstract

Objectives

This article defines analytical performance specifications (APS) for evaluating laboratory proficiency through an external quality assessment scheme.

Methods

Standard deviations for proficiency assessment were derived from Thompson’s characteristic function applied to robust data calculated from participants’ submissions in the Occupational and Environmental Laboratory Medicine (OELM) external quality assurance scheme for trace elements in serum, whole blood and urine. Characteristic function was based on two parameters: (1) β – the average coefficient of variation (CV) at high sample concentrations; (2) α – the average standard deviation (SD) at low sample concentrations. APSs were defined as 1.65 standard deviations calculated by Thompson’s approach. Comparison between OELM robust data and characteristic function were used to validate the model.

Results

Application of the characteristic function allowed calculated APS for 18 elements across three matrices. Some limitations were noted, particularly for elements (1) with no sample concentrations near analytical technique limit of detection; (2) exhibiting high robust CV at high concentration; (3) exhibiting high analytical variability such as whole blood Tl and urine Pb; (4) with an unbalanced number of robust SD above and under the characteristic function such as whole blood Mn and serum Al and Zn.

Conclusions

The characteristic function was a useful means of deriving APS for trace elements in biological fluids where biological variation data or outcome studies were not available. However, OELM external quality assurance scheme data suggests that the characteristic functions are not appropriate for all elements.


Corresponding author: Cas Weykamp, MCA Laboratory, Queen Beatrix Hospital, Beatrixpark 1, Winterswijk 7101 BN, The Netherlands, E-mail:
The authors are members of the Occupational and Environmental Laboratory Medicine network (OELM) and/or participate in the OELM external quality assessment scheme.

Acknowledgments

The authors would like to thank participating laboratories who submitted their results.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

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

  4. Competing interests: The authors state no conflict of interest.

  5. Research funding: None declared.

  6. Data availability: Not applicable.

References

1. 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-2017-0151.10.1515/cclm-2017-0151Search in Google Scholar PubMed

2. ISO 13528:2022. Statistical methods for use in proficiency testing by interlaboratory comparisons. https://www.iso.org/standard/78879.html [Accessed 6 Mar 2024].Search in Google Scholar

3. European Federation of Clinical Chemistry and Laboratory Medicine (EFLM). https://www.eflm.eu [Accessed 17 Feb 2024].Search in Google Scholar

4. 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-2015-0067.10.1515/cclm-2015-0067Search in Google Scholar PubMed

5. Horvath, AR, Bossuyt, PM, Sandberg, S, John, AS, Monaghan, PJ, Verhagen-Kamerbeek, WD, et al.. Setting analytical performance specifications based on outcome studies – is it possible? Clin Chem Lab Med 2015;53:841–8. https://doi.org/10.1515/cclm-2015-0214.10.1515/cclm-2015-0214Search in Google Scholar PubMed

6. Miller, WG, Jones, GR, Horowitz, GL, Weykamp, C. Proficiency testing/external quality assessment: current challenges and future directions. Clin Chem 2011;12:1670–80. https://doi.org/10.1373/clinchem.2011.168641.Search in Google Scholar PubMed

7. Panteghini, M, Ceriotti, F, Jones, G, Oosterhuis, W, Plebani, M, Sandberg, S. Task Force on performance specifications in laboratory medicine of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM). Strategies to define performance specifications in laboratory medicine: 3 years on from the Milan Strategic Conference. Clin Chem Lab Med 2017;55:1849–56. https://doi.org/10.1515/cclm-2017-0772.Search in Google Scholar PubMed

8. Ceriotti, F, Cobbaert, C. Harmonization of external quality assessment schemes and their role – clinical chemistry and beyond. Clin Chem Lab Med 2018;56:1587–90. https://doi.org/10.1515/cclm-2018-0265.Search in Google Scholar PubMed

9. Lamkarkach, F, Ougier, E, Garnier, R, Viau, C, Kolossa-Gehring, M, Lange, R, et al.. Human biomonitoring initiative (HBM4EU): human biomonitoring guidance values (HBM-GVs) derived for cadmium and its compounds. Environ Int 2021;147:106337. https://doi.org/10.1016/j.envint.2020.106337.10.1016/j.envint.2020.106337Search in Google Scholar PubMed

10. Lead poisoning. World Health Organization; 2023. https://www.who.int/news-room/fact-sheets/detail/lead-poisoning-and-health [Accessed 6 Mar 2024].Search in Google Scholar

11. Lamas, GA, Bhatnagar, A, Jones, MR, Mann, KK, Nasir, K, Tellez-Plaza, M, et al.. Contaminant metals as cardiovascular risk factors: a scientific statement from the American Heart Association. J Am Heart Assoc 2023;12:e029852. https://doi.org/10.1161/JAHA.123.029852.Search in Google Scholar PubMed PubMed Central

12. Keles, M. Evaluation of the clinical chemistry test analytical performance by using different models and specifications. Turk J Biochem 2020;45:11–8. https://doi.org/10.1515/tjb-2018-0250.Search in Google Scholar

13. Ricos, C, Fernandez-Calle, P, Perich, C, Sandberg, S. External quality control in laboratory medicine. Progresses and future. Adv Lab Med 2022;3:221–31. https://doi.org/10.1515/almed-2022-0058.Search in Google Scholar PubMed PubMed Central

14. Aarsand, AK, Fernandez-Calle, P, Webster, C, Coskun, A, Gonzales-Lao, E, Diaz-Garzon, J, et al.. The EFLM biological variation database. https://biologicalvariation.eu/ [Accessed 17 Feb 2024].Search in Google Scholar

15. Coşkun, A, Carobene, A, Aarsand, AK, Aksungar, FB, Serteser, M, Sandberg, S, et al.. European Federation of Clinical Chemistry and Laboratory Medicine Working Group on Biological Variation and Task Group for the biological variation database. Within- and between-subject biological variation data for serum zinc, copper and selenium obtained from 68 apparently healthy Turkish subjects. Clin Chem Lab Med 2022;60:533–42. https://doi.org/10.1515/cclm-2021-0886.10.1515/cclm-2021-0886Search in Google Scholar PubMed

16. Coşkun, A, Aarsand, AK, Braga, F, Carobene, A, Díaz-Garzón, J, Fernandez-Calle, P, et al.. Systematic review and meta-analysis of within-subject and between-subject biological variation estimates of serum zinc, copper and selenium. Clin Chem Lab Med 2022;60:479–82. https://doi.org/10.1515/cclm-2021-0723.10.1515/cclm-2021-0723Search in Google Scholar PubMed

17. Plebani, M, Padoan, A, Lippi, G. Biological variation: back to basics. Clin Chem Lab Med 2015;53:155–6. https://doi.org/10.1515/cclm-2014-1182.Search in Google Scholar PubMed

18. Bartlett, WA, Braga, F, Carobene, A, Coşkun, A, Prusa, R, Fernandez-Calle, P, et al.. Biological variation Working Group, European Federation of Clinical Chemistry and Laboratory Medicine (EFLM). A checklist for critical appraisal of studies of biological variation. Clin Chem Lab Med 2015;53:879–85. https://doi.org/10.1515/cclm-2014-1127.Search in Google Scholar PubMed

19. Aarsand, AK, Røraas, T, Fernandez-Calle, P, Ricos, C, Díaz-Garzón, J, Jonker, N, et al.. European Federation of Clinical Chemistry and Laboratory Medicine Working Group on Biological Variation and Task and Finish Group for the Biological Variation Database. The biological variation data critical appraisal checklist: a standard for evaluating studies on biological variation. Clin Chem 2018;64:501–14. https://doi.org/10.1373/clinchem.2017.281808.10.1373/clinchem.2017.281808Search in Google Scholar PubMed

20. Carobene, A, Aarsand, AK, Bartlett, WA, Coskun, A, Diaz-Garzon, J, Fernandez-Calle, P, et al.. The European Biological Variation Study (EuBIVAS): a summary report. Clin Chem Lab Med 2021;60:505–17. https://doi.org/10.1515/cclm-2021-0370.10.1515/cclm-2021-0370Search in Google Scholar PubMed

21. Sandberg, S, Carobene, A, Bartlett, B, Coskun, A, Fernandez-Calle, P, Jonker, N, et al.. Biological variation: recent development and future challenges. Clin Chem Lab Med 2022;61:741–50. https://doi.org/10.1515/cclm-2022-1255.10.1515/cclm-2022-1255Search in Google Scholar PubMed

22. Arnaud, J, Weber, JP, Weykamp, CW, Parsons, PJ, Angerer, J, Mairiaux, E, et al.. Quality specifications for the determination of copper, zinc, and selenium in human serum or plasma: evaluation of an approach based on biological and analytical variation. Clin Chem 2008;54:1892–9. https://doi.org/10.1373/clinchem.2008.108142.10.1373/clinchem.2008.108142Search in Google Scholar PubMed

23. Thompson, M. Uncertainty functions, a compact way of summarising or specifying the behaviour of analytical systems. TrAC, Trends Anal Chem 2011;30:1168–75. https://doi.org/10.1016/j.trac.2011.03.012.Search in Google Scholar

24. Horwitz, W, Albert, R. The Horwitz ratio (HorRat): a useful index of method performance with respect to precision. J AOAC Int 2006;89:1095–109. https://doi.org/10.1093/jaoac/89.4.1095.Search in Google Scholar

25. Panteghini, M. Redesigning the surveillance of in vitro diagnostic medical devices and of medical laboratory performance by quality control in the traceability era. Clin Chem Lab Med 2023;61:759–68. https://doi.org/10.1515/cclm-2022-1257.10.1515/cclm-2022-1257Search in Google Scholar PubMed

26. Côté, I, Robouch, P, Robouch, B, Bisson, D, Gamache, P, LeBlanc, A, et al.. Determination of the standard deviation for proficiency assessment from past participant’s performances. Accred Qual Assur 2012;17:389–93. https://doi.org/10.1007/s00769-012-0906-2.Search in Google Scholar

27. Praamsma, ML, Arnaud, J, Bisson, D, Kerr, S, Harrington, CF, Parsons, PJ. Network of Organisers of External Quality Assurance Schemes in Occupational and Environmental Laboratory Medicine. An assessment of clinical laboratory performance for the determination of manganese in blood and urine. Clin Chem Lab Med 2016;54:1921–8. https://doi.org/10.1515/cclm-2015-1267.10.1515/cclm-2015-1267Search in Google Scholar PubMed

28. OELM. Occupational and environmental laboratory medicine. http://www.trace-elements.eu/ [Accessed 29 Oct 2023].Search in Google Scholar

29. ISO 13485. Dispositifs médicaux – Systèmes de management de la qualité – Exigences à des fins réglementaires; 2016. https://www.iso.org/fr/standard/59752.html [Accessed 6 Mar 2024].Search in Google Scholar

30. Taylor, A, Angerer, J, Claeys, F, Kristiansen, J, Mazarrasa, O, Menditto, A, et al.. Comparison of procedures for evaluating laboratory performance in external quality assessment schemes for lead in blood and aluminum in serum demonstrates the need for common quality specifications. Clin Chem 2002;48:2000–7. https://doi.org/10.1093/clinchem/48.11.2000.Search in Google Scholar

31. 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-2015-0997.10.1515/cclm-2015-0997Search in Google Scholar PubMed

32. Haeckel, R, Wosniok, W, Streichert, T. Optimizing the use of the “state-of-the-art” performance criteria. Clin Chem Lab Med 2015;53:887–91. https://doi.org/10.1515/cclm-2014-1201.10.1515/cclm-2014-1201Search in Google Scholar PubMed

33. Göen, T, Schaller, KH, Drexler, H. External quality assessment of human biomonitoring in the range of environmental exposure levels. Int J Hyg Environ Health 2012;215:229–32. https://doi.org/10.1016/j.ijheh.2011.08.012.10.1016/j.ijheh.2011.08.012Search in Google Scholar PubMed

34. Taylor, A. Quality assessment of measurement. J Trace Elem Med Biol 2011;25:S17–21. https://doi.org/10.1016/j.jtemb.2010.11.001.10.1016/j.jtemb.2010.11.001Search in Google Scholar PubMed

35. Baker, MG, Simpson, CD, Sheppard, L, Stover, B, Morton, J, Cocker, J, et al.. Variance components of short-term biomarkers of manganese exposure in an inception cohort of welding trainees. J Trace Elem Med Biol 2015;29:123–9. https://doi.org/10.1016/j.jtemb.2014.05.004.10.1016/j.jtemb.2014.05.004Search in Google Scholar PubMed PubMed Central

36. Ricós, C, Alvarez, V, Cava, F, García-Lario, JV, Hernández, A, Jiménez, CV, et al.. Current databases on biological variation: pros, cons and progress. Scand J Clin Lab Invest 1999;59:491–500. https://doi.org/10.1080/00365519950185229.10.1080/00365519950185229Search in Google Scholar PubMed

37. Delves, HT, Sherlock, JC, Quinn, MJ. Temporal stability of blood lead concentrations in adults exposed only to environmental lead. Hum Toxicol 1984;3:279–88. https://doi.org/10.1177/096032718400300404.10.1177/096032718400300404Search in Google Scholar PubMed

38. 10 chemicals of public health concern. World Health Organization; 2020. https://www.who.int/news-room/photo-story/photo-story-detail/10-chemicals-of-public-health-concern [Accessed 6 Mar 2024].Search in Google Scholar

39. WHO guideline for clinical management of exposure to lead: executive summary. World Health Organization; 2021. https://www.who.int/publications/i/item/9789240036888 [Accessed 6 Mar 2024].Search in Google Scholar

40. Fourth national report on human exposure to environmental chemicals: updated tables. National Center for Environmental Health (U.S.). Division of Laboratory Sciences; 2019, Vol 1. https://stacks.cdc.gov/view/cdc/75822 [Accessed 6 Mar 2024].Search in Google Scholar

41. Becker, K, Kaus, S, Krause, C, Lepom, P, Schulz, C, Seiwert, M, et al.. German Environmental Survey 1998 (GerES III): environmental pollutants in blood of the German population. Int J Hyg Environ Health 2002;205:297–308. https://doi.org/10.1078/1438-4639-00155.10.1078/1438-4639-00155Search in Google Scholar PubMed

42. SCOEL/OPIN/336. Cadmium and its inorganic compounds. Scientific Committee on Occupational Exposure Limits; 2017. https://echa.europa.eu/documents/10162/35144386/182_cadmium_and_its_inorganic_compounds_oel_en.pdf/19700d5a-2c65-1827-15ca-463f612096fb?t=1699953898709 [Accessed 5 Mar 2024].Search in Google Scholar

43. TLV and BEI Documentation. Arsenic and soluble inorganic compounds BEI. Cincinnatti: ACGIH; 2023.Search in Google Scholar

44. U.S. EPA. Reference dose for methylmercury (external review draft). Washington, D.C.: U.S. Environmental Protection Agency; 2000. https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCEA&dirEntryId=20873 [Accessed 3 Apr 2024].Search in Google Scholar

45. Centers for Disease Control and Prevention. Case definitions for chemical poisoning. MMWR (Morb Mortal Wkly Rep) 2005;54:12–3.Search in Google Scholar


Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2024-0551).


Received: 2024-05-02
Accepted: 2024-07-07
Published Online: 2024-07-22
Published in Print: 2025-01-29

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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