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Diagnostic performance of morphological analysis and red blood cell parameter-based algorithms in the routine laboratory screening of heterozygous haemoglobinopathies

  • Germain Simon ORCID logo EMAIL logo , François Boemer ORCID logo , Géraldine Luis ORCID logo , André Gothot ORCID logo , Françoise Tassin and Aurore Keutgens ORCID logo
Published/Copyright: May 22, 2025

Abstract

Objectives

The aim of this study was to carry out a cross-analysis of the morphological abnormalities (MA) and the electrophoretic profile (EP) of blood samples suspect for heterozygous haemoglobinopathies (HTZ HGP). Screening for HTZ HGP was based on erythrocyte parameters provided by the Sysmex XN analysers.

Methods

A total of 596,000 blood samples was included in the study. According to the results of the mean corpuscular haemoglobin concentration (MCHC), the percentage of microcytes (Micro%) and the standard deviation of the red blood cell distribution width (RDW-SD), 842 different adults were screened as suspect for HTZ HGP and underwent simultaneous morphological analysis of red blood cells (RBCMA) and haemoglobin fraction analysis.

Results

The majority (72.8 %) of HTZ HGP suspects presented a pathological EP, mostly compatible with a confirmed β-thalassaemia trait (50.1 %) or a heterozygous β-haemoglobin variant (12.2 %). MA were identified in 360 (42.8 %) samples and 70 (8.3 %) of these had 3 or more MA. The most common MA was poikilocytosis (28.1 %). Patients with at least 1 MA detected were more likely to have a pathological EP (p=0.003). However, correlation between the number of MA detected and the type of EP was negligible.

Conclusions

Screening for HTZ HGP based on erythrocyte parameters measured on Sysmex XN analysers is a relevant tool with a positive predictive value of 72.8 % and definitely superior to microscopic RBCMA which now appears to be of low added value and obsolete in this indication.


Corresponding author: Germain Simon, MD, Department of Laboratory Hematology, University Hospital Center of Liège, Avenue de l’Hôpital 1, 4000 Liège, Belgium, E-mail:

  1. Research ethics: The local Institutional Review Board deemed the study exempt from review.

  2. Informed consent: Not applicable.

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

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

1. Harteveld, CL, Achour, A, Arkesteijn, SJ, Ter Huurne, J, Verschuren, M, Bhagwandien-Bisoen, S, et al.. The hemoglobinopathies, molecular disease mechanisms and diagnostics. Int J Lab Hematol 2022;44:28–36. https://doi.org/10.1111/ijlh.13885.Search in Google Scholar PubMed PubMed Central

2. Giardine, B, Borg, J, Viennas, E, Pavlidis, C, Moradkhani, K, Joly, P, et al.. Updates of the HbVar database of human hemoglobin variants and thalassemia mutations. Nucleic Acids Res 2014;42:1063–9. https://doi.org/10.1093/nar/gkt911.Search in Google Scholar PubMed PubMed Central

3. Traeger-Synodinos, J, Harteveld, CL, Old, JM, Petrou, M, Galanello, R, Giordano, P, et al.. EMQN Best practice guidelines for molecular and haematology methods for carrier identification and prenatal diagnosis of the haemoglobinopathies. Eur J Hum Genet 2015;23:426–37. https://doi.org/10.1038/ejhg.2014.131.Search in Google Scholar PubMed PubMed Central

4. Modell, B, Darlison, M. Global epidemiology of haemoglobin disorders and derived service indicators. Bull World Health Organ 2008;86:480–7. https://doi.org/10.2471/blt.06.036673.Search in Google Scholar PubMed PubMed Central

5. Lippi, G, Mattiuzzi, C. Updated worldwide epidemiology of inherited erythrocyte disorders. Acta Haematol 2020;143:196–203. https://doi.org/10.1159/000502434.Search in Google Scholar PubMed

6. GBD Sickle Cell Disease Collaborators. Global, regional, and national prevalence and mortality burden of sickle cell disease, 2000–2021: a systematic analysis from the global burden of disease study 2021. Lancet Haematol 2023;10:585–99. https://doi.org/10.1016/s2352-3026(23)00118-7.Search in Google Scholar

7. Tuo, Y, Li, Y, Li, Y, Ma, J, Yang, X, Wu, S, et al.. Global, regional, and national burden of thalassemia, 1990–2021: a systematic analysis for the global burden of disease study 2021. eClinicalMedicine 2024;72:102619. https://doi.org/10.1016/j.eclinm.2024.102619.Search in Google Scholar PubMed PubMed Central

8. Modell, B, Darlison, M, Birgens, H, Cario, H, Faustino, P, Giordano, PC, et al.. Epidemiology of haemoglobin disorders in Europe: an overview. Scand J Clin Lab Invest 2007;67:39–69. https://doi.org/10.1080/00365510601046557.Search in Google Scholar PubMed

9. Kattamis, A, Forni, GL, Aydinok, Y, Viprakasit, V. Changing patterns in the epidemiology of beta-thalassemia. Eur J Haematol 2020;105:692–703. https://doi.org/10.1111/ejh.13512.Search in Google Scholar PubMed PubMed Central

10. Piel, FB, Tatem, AJ, Huang, Z, Gupta, S, Williams, TN, Weatherall, DJ. Global migration and the changing distribution of sickle haemoglobin: a quantitative study of temporal trends between 1960 and 2000. Lancet Global Health 2014;2:80–9. https://doi.org/10.1016/s2214-109x(13)70150-5.Search in Google Scholar PubMed PubMed Central

11. Piel, FB. The present and future global burden of the inherited disorders of hemoglobin. Hematol Oncol Clin North Am 2016;30:327–41. https://doi.org/10.1016/j.hoc.2015.11.004.Search in Google Scholar PubMed

12. Old, JM. Prevention and diagnosis of haemoglobinopathies [Online]. Nicosia, Cyprus: Thalassaemia International Federation (TIF); 2019. https://thalassaemia.org.cy/wp-content/uploads/2019/11/Preventiondiagnosis-of-Hbpathies_BOOKLETNEW-1.pdf [Accessed 14 Nov 2024].Search in Google Scholar

13. Bain, BJ. Haemoglobinopathy diagnosis: algorithms, lessons and pitfalls. Blood Rev 2011;25:205–13. https://doi.org/10.1016/j.blre.2011.04.001.Search in Google Scholar PubMed

14. Barnes, PW, McFadden, SL, Machin, SJ, Simson, E, International Consensus Group for Hematology. The international consensus group for hematology review: suggested criteria for action following automated CBC and WBC differential analysis. Lab Hematol 2005;11:83–90. https://doi.org/10.1532/lh96.05019.Search in Google Scholar PubMed

15. Geneviève, F, Galoisy, AC, Mercier-Bataille, D, Wagner-Ballon, O, Trimoreau, F, Fenneteau, O, et al.. Revue microscopique du frottis sanguin: propositions du Groupe Francophone d’Hematologie Cellulaire (GFHC). Rev Biol Med 2014;55:7–16.Search in Google Scholar

16. Palmer, L, Briggs, C, McFadden, S, Zini, G, Burthem, J, Rozenberg, G, et al.. ICSH recommendations for the standardization of nomenclature and grading of peripheral blood cell morphological features. Int J Lab Hematol 2015;37:287–303. https://doi.org/10.1111/ijlh.12327.Search in Google Scholar PubMed

17. Nivaggioni, V, Bouriche, L, Coito, S, Le Floch, AS, Ibrahim-Kosta, M, Leonnet, C, et al.. Use of Sysmex XN-10 red blood cell parameters for screening of hereditary red blood cell diseases and iron deficiency anaemia. Int J Lab Hematol 2020;42:697–704. https://doi.org/10.1111/ijlh.13278.Search in Google Scholar PubMed PubMed Central

18. Boemer, F, Ketelslegers, O, Minon, JM, Bours, V, Schoos, R. Newborn screening for sickle cell disease using tandem mass spectrometry. Clin Chem 2008;54:2036–41. https://doi.org/10.1373/clinchem.2008.106369.Search in Google Scholar PubMed

19. Boemer, F, Cornet, Y, Libioulle, C, Segers, K, Bours, V, Schoos, R. 3-years experience review of neonatal screening for hemoglobin disorders using tandem mass spectrometry. Clin Chim Acta 2011;412:1476–9. https://doi.org/10.1016/j.cca.2011.04.031.Search in Google Scholar PubMed

20. UK Government. SCT screening handbook for antenatal laboratories [Online]. https://www.gov.uk/government/publications/sct-screening-handbook-for-antenatal-laboratories [Accessed 14 Nov 2024].Search in Google Scholar

21. Aguilar-Martinez, P, Badens, C, Bonello-Palot, N, Cadet, E, Couque, N, Ducrocq, R, et al.. Flowcharts for the diagnosis and the molecular characterization of hemoglobinopathies. Ann Biol Clin 2010;68:455–64. https://doi.org/10.1684/abc.2010.0457.Search in Google Scholar PubMed

22. Weatherall, D, Clegg, J, editors. The thalassaemia syndromes, 4th ed. Oxford, UK: Blackwell Science Ltd; 2001:846 p.10.1002/9780470696705Search in Google Scholar

23. World Helath Organization (WHO). Serum ferritin concentrations for the assessment of iron status in individuals and populations: technical brief. Geneva, Switzerland: World Health Organization; 2020:6 p. Report No. WHO/NMH/NHD/MNM/20.5.Search in Google Scholar

24. Watson, PF, Petrie, A. Method agreement analysis: a review of correct methodology. Theriogenology 2010;73:1167–79. https://doi.org/10.1016/j.theriogenology.2010.01.003.Search in Google Scholar PubMed

25. GraphPad Software. Kappa statistic calculator [Online]. https://www.graphpad.com/quickcalcs/kappa1/ [Accessed 30 Nov 2024].Search in Google Scholar

26. Velasco-Rodriguez, D, Alonso-Dominguez, JM, Gonzalez-Fernandez, FA, Villarrubia, J, Ropero, P, Martinez-Nieto, J, et al.. Deltabeta-thalassemia trait: how can we discriminate it from beta-thalassemia trait and iron deficiency anemia? Am J Clin Pathol 2014;142:567–73. https://doi.org/10.1309/ajcppbq8ub1whxts.Search in Google Scholar

27. Brancaleoni, V, Di Pierro, E, Motta, I, Cappellini, MD. Laboratory diagnosis of thalassemia. Int J Lab Hematol 2016;38:32–40. https://doi.org/10.1111/ijlh.12527.Search in Google Scholar PubMed

28. Bain, BJ. Blood cell morphology in health and disease. In: Bain, BJ, Bates, I, Laffan, MA, editors. Dacie and Lewis practical haematology, 12th ed. Amsterdam: Elsevier; 2017.10.1016/B978-0-7020-6696-2.00005-9Search in Google Scholar

29. Ford, J. Red blood cell morphology. Int J Lab Hematol 2013;35:351–7. https://doi.org/10.1111/ijlh.12082.Search in Google Scholar PubMed

30. Bain, BJ, Daniel, Y, Henthorn, J, de la Salle, B, Hogan, A, Roy, NBA, et al.. Significant haemoglobinopathies: a guideline for screening and diagnosis: a British society for haematology (BSH) guideline. Br J Haematol 2023;201:1047–65. https://doi.org/10.1111/bjh.18794.Search in Google Scholar PubMed

31. Thilakarathne, S, Jayaweera, UP, Premawardhena, A. Unresolved laboratory issues of the heterozygous state of beta-thalassemia: a literature review. Haematologica 2024;109:23–32. https://doi.org/10.3324/haematol.2022.282667.Search in Google Scholar PubMed PubMed Central


Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2025-0210).


Received: 2025-02-21
Accepted: 2025-04-30
Published Online: 2025-05-22
Published in Print: 2025-08-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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