Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter July 24, 2019

Study of the analytical performance at different concentrations of hematological parameters using Spanish EQAS data

Angel Molina ORCID logo EMAIL logo , José Alcaraz , Leonor Guiñón , Aránzazu Pérez , Anna Segurana , Joan Carles Reverter , Josep Lluís Bedini and Anna Merino



External quality assessment programs are one of the currently available tools to evaluate the analytical performance of clinical laboratories, where the measurement error (ME) obtained can be compared with quality specifications to evaluate possible deviations. The objective of this work was to analyze the ME behavior over the analytical range to assess the need to establish concentration-dependent specifications.


A total of 389,000 results from 585 laboratories and 2628 analyzers were collected from the Spanish external quality assessment schemes (EQAS) in hematology during the years 2015–2016. The parameters evaluated included white blood cells, red blood cells, hemoglobin, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, platelets, prothrombin time, activated partial thromboplastin time, neutrophils, lymphocytes, monocytes, eosinophils, basophils, reticulocytes, hemoglobin A2, antithrombin, factor VIII, protein C and von Willebrand factor. The 90th percentile of ME was calculated for every concentration evaluated of each parameter.


We found a significant variation in the analytical performance of leukocytes, platelets, neutrophils, lymphocytes, monocytes, eosinophils, basophils, prothrombin time, reticulocytes, hemoglobin A2, antithrombin and protein C. Furthermore, this ME variation may not allow complying with the same biological variability requirements within the whole analytical range studied.


Our work shows the importance of implementing concentration-dependent specifications which can help laboratories to use proper criteria for quality specifications selection and for a better external quality control results evaluation.


This research was partially supported by FPCQLC (Fundació pel Control de Qualitat dels Laboratoris Clinics).

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

  2. Research funding: This work is part of a research project funded by the Directory of Science, Technology and Innovation of the Ministry of Economy and Competitiveness of Spain, with reference DPI2015-64493-R.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.


1. Laboratorio Clínico Central. Estándares y recomendaciones de calidad y seguridad. Ministerio de Sanidad, Servicios Sociales e Igualdad. Gobierno de España. 2013. Accessed: January 2019.Search in Google Scholar

2. Krouwer JS. Setting performance goals and evaluating total analytical error for diagnostic assays. Clin Chem 2002;48:919–27.10.1093/clinchem/48.6.919Search in Google Scholar

3. Libeer JC. Role of external quality assurance schemes in assessing and improving quality in medical laboratories. Clin Chim Acta 2001;309:173–7.10.1016/S0009-8981(01)00518-6Search in Google Scholar

4. Miller WG, Jones GR, Horowitz GL, Weykamp C. Proficiency testing/external quality assessment: current challenges and future directions. Clin Chem 2011;57:1670–80.10.1373/clinchem.2011.168641Search in Google Scholar PubMed

5. EN ISO 15189:2012. Medical laboratories – Particular requirements for quality and competence, Geneva: ISO, 2012.Search in Google Scholar

6. 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;53:833–5.10.1515/cclm-2015-0067Search in Google Scholar PubMed

7. Clinical Laboratory Improvement Act 2004. Part 493 laboratory requirements. Subpart I – proficiency testing programs for nonwaived testing. Accessed: January 2019.Search in Google Scholar

8. German Medical Association. Revision of the “Guideline of the German Medical Association on Quality Assurance in Medical Laboratory Examinations–RiliBAEK”. J Lab Med 2015;39:26–69.Search in Google Scholar

9. Jones GR, Sikaris K, Gill J. ‘Allowable limits of performance’ for external quality assurance programs – an approach to application of the Stockholm Criteria by the RCPA Quality Assurance Programs. Clin Biochem Rev 2012;33:133–9.Search in Google Scholar

10. Ricós C, Álvarez V, Cava F, García-Lario JV, Hernández A, Jiménez CV, et al. Current Database on biologic variation: prons, cons and progress. Scand J Clin Lab Invest 1999;59: 491–500.10.1080/00365519950185229Search in Google Scholar PubMed

11. Salas A, Ricós C, Prada E, Ramón F, Morancho J, Jou JM, et al. State of the art approach to goal setting. Clin Lab Med 2017;37:73–84.10.1016/j.cll.2016.09.007Search in Google Scholar PubMed

12. Ricós C, Baadenhuijsen H, Libeer JC, Hyltoft Petersen P, Stockl D, Thienpont L, et al. External quality assesment: currently used criteria for evaluating performance in European countries, and criteria for future harmonization. Eur J Clin Chem Clin Biochem 1996;34:159–65.Search in Google Scholar

13. Hübl W, Tlustos L, Bayer PM. Use of precision profiles to evaluate precision of the automated leukocyte differential. Clin Chem 1996;42:1068–73.10.1093/clinchem/42.7.1068Search in Google Scholar

14. Buttarello M, Bulian P, Farina G, Temporin V, Toffolo L, Trabuio E, et al. Flow cytometric reticulocyte counting: parallel evaluation of five fully automated analyzers: an NCCLS-ICSH approach. Am J Clin Pathol 2001;115:100–11.10.1309/M26B-1YNQ-VNU8-M1CESearch in Google Scholar PubMed

15. Buttarello M. Quality specification in haematology: the automated blood cell count. Clin Chim Acta 2004;346:45–54.10.1016/j.cccn.2004.02.038Search in Google Scholar PubMed

16. Vives-Corrons JL, Gutiérrez G, Jou JM, Reverter JC, Martínez-Brotons F, Domingo A, et al. Characteristics and performance of the external quality assessment scheme (EQAS) for hematology in Spain. Ten years of experience. Ann Ist Super Sanita 1995;31:95–101.Search in Google Scholar

17. EN ISO 13528:2015. Stastistical methods for use in proficiency testing by interlaboratory comparisons. ISO 13528. Geneva: ISO, 2015.Search in Google Scholar

18. Fraser CG, Petersen PH, Libeer JC, Ricós C. Proposals for setting generally applicable quality goals solely based on biology. Ann Clin Biochem 1997;34:8–12.10.1177/000456329703400103Search in Google Scholar PubMed

19. Ricós C, Álvarez V, Cava F, Garcia-Lario JV, Hernandez A, Jimenez CV, et al. Desirable specifications for total error, imprecision, and bias, derived from intra- and inter-individual biologic variation. The 2014 update. Original publication available from (Spanish only). Accessed: January 2019. Also available on (English): Accessed: January 2019.Search in Google Scholar

20. Coşkun A, Carobene A, Kilercik M, Serteser M, Sandberg S, Aarsand AK, et al. Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects. Clin Chem Lab Med 2018;56:1309–18.10.1515/cclm-2017-1155Search in Google Scholar PubMed

21. Soumali MR, Van Blerk M, Akharif A, Albarède S, Kesseler D, Gutierrez G, et al. A new approach to define acceptance limits for hematology in external quality assessment schemes. Clin Chem Lab Med 2017;55:1936–42.10.1515/cclm-2016-1048Search in Google Scholar PubMed

22. Horsti J, Uppa H, Vilpo JA. Poor agreement among prothrombin time international normalized ratio methods: comparison of seven commercial reagents. Clin Chem 2005;51:553–60.10.1373/clinchem.2004.043836Search in Google Scholar PubMed

23. Bowyer A, Kitchen S, Makris M. The responsiveness of different APTT reagents to mild factor VIII, IX and XI deficiencies. Int J Lab Hematol 2011;33:154–8.10.1111/j.1751-553X.2010.01261.xSearch in Google Scholar PubMed

24. Ricós C, Álvarez V, Minchinela J, Fernández-Calle P, Perich C, Boned B, et al. Biologic variation approach to daily laboratory. Clin Lab Med 2017;37:47–56.10.1016/j.cll.2016.09.005Search in Google Scholar PubMed

25. Ricós C, Iglesias N, García-Lario JV, Simón M, Cava F, Hernández A, et al. Within-subject biological variation in disease: collated data and clinical consequences. Ann Clin Biochem 2007;44:343–52.10.1258/000456307780945633Search in Google Scholar PubMed

26. Molina A, Guiñón L, Pérez A, Segurana A, Bedini JL, Reverter JC, et al. (2018). State of the art vs. biological variability: Comparison on hematology parameters using Spanish EQAS data. Int J Lab Hematol 2011;40:284–91.10.1111/ijlh.12783Search in Google Scholar PubMed

27. Westgard MolinaJ. 2016 State of the Art Hematology Performance Specifications. Accessed: January 2019.Search in Google Scholar

Received: 2019-01-29
Accepted: 2019-06-17
Published Online: 2019-07-24
Published in Print: 2019-11-26

© 2019 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 28.11.2022 from
Scroll Up Arrow