Abstract
Objectives
The aim of the study was to determine the diagnostic performance of novel automated red cell parameters for estimating bone marrow iron stores.
Methods
The study was a retrospective single-centre study based on data from an automated haematology analyser and results of bone marrow iron staining. Red cell parameters were measured on a Sysmex XN-series haematology analyser. Bone marrow iron stores were assessed semiquantitatively by cytochemical reaction according to Perls.
Results
The analysis included 429 bone marrow aspirate smears from 393 patients. Median age of patients was 67 years, 52 % of them were female. The most common indication for bone marrow examination was a plasma cell dyscrasia (n=104; 24 %). Median values of percentage of hypochromic and hyperchromic red blood cells (%HYPO-He, %HYPER-He), reticulocyte haemoglobin equivalent (RET-He) and microcytic red blood cells (MicroR) were statistically significantly different between cases with iron deplete and iron replete bone marrow. In a logistic regression model, ferritin was the best predictor of bone marrow iron stores (AUC=0.891), outperforming RET-He and %HYPER-He (AUC=0.736 and AUC=0.722, respectively). In a combined model, ferritin/MicroR index achieved the highest diagnostic accuracy (AUC=0.915), outperforming sTfR/log ferritin index (AUC=0.855).
Conclusions
While single automated red cell parameters did not show improved diagnostic accuracy when compared to traditional iron biomarkers, a novel index ferritin/MicroR has the potential to outperform ferritin and sTfR/log ferritin index for predicting bone marrow iron stores. Further research is needed for interpretation and implementation of novel parameters and indices, especially in the context of unexplained anaemia and myelodysplastic syndromes.
Funding source: European Regional Development Fund
Award Identifier / Grant number: Project No. 2014-2020.4.01.15-0012
Acknowledgments
Tiit Salum and Triin Tammert participated in the conceptualization of the research.
-
Research ethics: The study was conducted in accordance with the Declaration of Helsinki and approved by Research Ethics Committee of the University of Tartu.
-
Informed consent: Not applicable.
-
Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Competing interests: The authors state no conflict of interest.
-
Research funding: This research was supported by the European Union through the European Regional Development Fund (Project No. 2014-2020.4.01.15-0012).
-
Data availability: Not applicable.
References
1. WHO. Iron deficiency anaemia. Assessment, prevention, and control. A guide for programme managers. Geneva: World Health Organization; 2001. https://www.who.int/publications/m/item/iron-children-6to23--archived-iron-deficiency-anaemia-assessment-prevention-and-control [Accessed 8 Sep 2023].Search in Google Scholar
2. Kassebaum, NJ. The global burden of anemia. Hematol Oncol Clin N Am 2016;30:247–308. https://doi.org/10.1016/j.hoc.2015.11.002.Search in Google Scholar PubMed
3. Ezzati, M. Comparative quantification of health risks: global and regional burden of disease attributable to selected major risk factors. Geneva: World Health Organization; 2004.Search in Google Scholar
4. Stevens, GA, Finucane, MM, De-Regil, LM, Paciorek, CJ, Flaxman, SR, Branca, F, et al.. Global, regional, and national trends in haemoglobin concentration and prevalence of total and severe anaemia in children and pregnant and non-pregnant women for 1995–2011: a systematic analysis of population-representative data. Lancet Global Health 2013;1:e16–25. https://doi.org/10.1016/s2214-109x(13)70001-9.Search in Google Scholar
5. Weiss, G. Anemia of chronic disease. N Engl J Med 2005;352:1011–23. https://doi.org/10.1056/nejmra041809.Search in Google Scholar PubMed
6. Weiss, G, Ganz, T, Goodnough, LT. Anemia of inflammation. Blood 2019;133:40–50. https://doi.org/10.1182/blood-2018-06-856500.Search in Google Scholar PubMed PubMed Central
7. Krause, JR, Stolc, V. Serum ferritin and bone marrow iron stores: I. Correlation with absence of iron in biopsy specimens. Am J Clin Pathol 1979;72:817–20. https://doi.org/10.1093/ajcp/72.5.817.Search in Google Scholar PubMed
8. Punnonen, K, Irjala, K, Rajamäki, A. Serum transferrin receptor and its ratio to serum ferritin in the diagnosis of iron deficiency. Blood 1997;89:1052–7. https://doi.org/10.1182/blood.v89.3.1052.Search in Google Scholar
9. Infusino, I, Braga, F, Dolci, A, Panteghini, M. Soluble transferrin receptor (sTfR) and sTfR/log ferritin index for the diagnosis of iron-deficiency anemia. Am J Clin Pathol 2012;138:642–9. https://doi.org/10.1309/ajcp16ntxzlzfaib.Search in Google Scholar
10. Gale, E, Torrance, J, Bothwell, T. The quantitative estimation of total iron stores in human bone marrow. J Clin Invest 1963;42:1076–82. https://doi.org/10.1172/jci104793.Search in Google Scholar PubMed PubMed Central
11. Barron, BA, Hoyer, JD, Tefferi, A. A bone marrow report of absent stainable iron is not diagnostic of iron deficiency. Ann Hematol 2001;80:166–9. https://doi.org/10.1007/s002770000261.Search in Google Scholar PubMed
12. Lee, SH, Erber, WN, Porwit, A, Tomonaga, M, Peterson, LC, International Council for Standardization in Hematology. ICSH guidelines for the standardization of bone marrow specimens and reports. Int J Lab Hematol 2008;30:349–64. https://doi.org/10.1111/j.1751-553x.2008.01100.x.Search in Google Scholar
13. Thomas, DW, Hinchliffe, RF, Briggs, C, Macdougall, IC, Littlewood, T, Cavill, I, et al.. Guideline for the laboratory diagnosis of functional iron deficiency. Br J Haematol 2013;161:639–48. https://doi.org/10.1111/bjh.12311.Search in Google Scholar PubMed
14. Lecompte, TP, Bernimoulin, MP. Novel parameters in blood cell counters. Clin Lab Med 2015;35:16. https://doi.org/10.1016/j.cll.2014.11.001.Search in Google Scholar PubMed
15. Buttarello, M. Laboratory diagnosis of anemia: are the old and new red cell parameters useful in classification and treatment, how? Int J Lab Hematol 2016;38:10. https://doi.org/10.1111/ijlh.12500.Search in Google Scholar PubMed
16. Skadberg, O, Brun, A, Sandberg, S. Human reticulocytes isolated from peripheral blood: maturation time and hemoglobin synthesis. Lab Hematol 2003;9:198–206.Search in Google Scholar
17. Adane, T, Asrie, F, Getaneh, Z. Clinical utility of immature reticulocyte fraction. J Clin Chem Lab Med 2021;4:1–5.Search in Google Scholar
18. Piva, E, Brugnara, C, Spolaore, F, Plebani, M. Clinical utility of reticulocyte parameters. Clin Lab Med 2015;35:133–63. https://doi.org/10.1016/j.cll.2014.10.004.Search in Google Scholar PubMed
19. Chung, Y, Lee, K, Han, M, Kim, JS, Park, J. Comparison of erythrocyte and reticulocyte indices for evaluation of iron deficiency by two automated hematologic analyzers. Clin Lab 2022;68. https://doi.org/10.7754/clin.lab.2021.210544.Search in Google Scholar
20. Jarc, E, Preložnik Zupan, I, Buturović Ponikvar, J, Snoj, N, Podgornik, H. Comparison of erythrocyte and reticulocyte indices for the diagnosis of iron deficiency. SlovMedJour [Internet];86; 2017. http://vestnik.szd.si/index.php/ZdravVest/article/view/2403 [Cited 5 Sep 2023].10.6016/ZdravVestn.2403Search in Google Scholar
21. Buttarello, M, Pajola, R, Novello, E, Rebeschini, M, Cantaro, S, Oliosi, F, et al.. Diagnosis of iron deficiency in patients undergoing hemodialysis. Am J Clin Pathol 2010;133:949–54. https://doi.org/10.1309/ajcpqax0jfhfs0oa.Search in Google Scholar
22. Schapkaitz, E. Stability of new erythrocyte and reticulocyte parameters in testing for anemia on the Sysmex XN 9000. Laboratory Medicine [Internet]; 2018. http://academic.oup.com/labmed/advance-article/doi/10.1093/labmed/lmx095/4820725 [Cited 4 Sep 2023].10.1093/labmed/lmx095Search in Google Scholar PubMed
23. Gaweda, AE. Markers of iron status in chronic kidney disease diagnosing iron deficiency. Hemodial Int 2017;21:S21–7. https://doi.org/10.1111/hdi.12556.Search in Google Scholar PubMed PubMed Central
24. Levy, S, Schapkaitz, E. The clinical utility of new reticulocyte and erythrocyte parameters on the Sysmex XN 9000 for iron deficiency in pregnant patients. Int J Lab Hematol 2018;40:683–90. https://doi.org/10.1111/ijlh.12904.Search in Google Scholar PubMed
25. Urrechaga, E, Borque, L, Escanero, JF. The role of automated measurement of red cell subpopulations on the Sysmex XE 5000 analyzer in the differential diagnosis of microcytic anemia: differential diagnosis of microcytic anemia. Int J Lab Hematol 2011;33:30–6. https://doi.org/10.1111/j.1751-553x.2010.01237.x.Search in Google Scholar PubMed
26. Urrechaga, E, Borque, L, Escanero, JF. Potential utility of the new Sysmex XE 5000 red blood cell extended parameters in the study of disorders of iron metabolism. Clinical Chemistry and Laboratory Medicine [Internet];47; 2009. https://www.degruyter.com/document/doi/10.1515/CCLM.2009.301/html [Cited 4 Sep 2023].10.1515/CCLM.2009.301Search in Google Scholar PubMed
27. Bahr, TM, Christensen, TR, Henry, E, Wilkes, J, Ohls, RK, Bennett, ST, et al.. Neonatal reference intervals for the complete blood count parameters MicroR and HYPO-He: sensitivity beyond the red cell indices for identifying microcytic and hypochromic disorders. J Pediatr 2021;239:95–100.e2. https://doi.org/10.1016/j.jpeds.2021.08.002.Search in Google Scholar PubMed PubMed Central
28. Xiao, H, Wang, Y, Ye, Y, Yang, C, Wu, X, Wu, X, et al.. Differential diagnosis of thalassemia and iron deficiency anemia in pregnant women using new formulas from multidimensional analysis of red blood cells. Ann Transl Med 2021;9:141. https://doi.org/10.21037/atm-20-7896.Search in Google Scholar PubMed PubMed Central
29. National Institute for Health and Care, Excellence. Chronic kidney disease: assessment and management. London: NICE; 2021. https://www.nice.org.uk/guidance/ng203/resources/chronic-kidney-disease-assessment-and-management-pdf-66143713055173 [Accessed 8 Sep 2023].Search in Google Scholar
30. Snook, J, Bhala, N, Beales, ILP, Cannings, D, Kightley, C, Logan, RP, et al.. British Society of Gastroenterology guidelines for the management of iron deficiency anaemia in adults. Gut 2021;70:2030–51. https://doi.org/10.1136/gutjnl-2021-325210.Search in Google Scholar PubMed PubMed Central
31. Fletcher, A, Forbes, A, Svenson, N, Wayne Thomas, D, A British Society for Haematology Good Practice Paper. Guideline for the laboratory diagnosis of iron deficiency in adults (excluding pregnancy) and children. Br J Haematol 2022;196:523–9. https://doi.org/10.1111/bjh.17900.Search in Google Scholar PubMed
32. Cai, J, Wu, M, Ren, J, Du, Y, Long, Z, Li, G, et al.. Evaluation of the efficiency of the reticulocyte hemoglobin content on diagnosis for iron deficiency anemia in Chinese adults. Nutrients 2017;9:450. https://doi.org/10.3390/nu9050450.Search in Google Scholar PubMed PubMed Central
33. Rehu, M. The diagnostic accuracy of the percentage of hypochromic red blood cells (%HYPOm) and cellular hemoglobin in reticulocytes (CHr) in differentiating iron deficiency anemia and anemia of chronic diseases. Clin Chim Acta 2011;5:1809–13.10.1016/j.cca.2011.06.004Search in Google Scholar PubMed
34. Grote Beverborg, N, Klip, IJT, Meijers, WC, Voors, AA, Vegter, EL, van der Wal, HH, et al.. Definition of iron deficiency based on the gold standard of bone marrow iron staining in heart failure patients. Circ: Heart Fail 2018;11:e004519. https://doi.org/10.1161/circheartfailure.117.004519.Search in Google Scholar
35. Mehta, S, Goyal, LK, Kaushik, D, Gulati, S, Sharma, N, Harshvardhan, L, et al.. Reticulocyte hemoglobin vis-a-vis serum ferritin as a marker of bone marrow iron store in iron deficiency anemia. J Assoc Phys India 2016;64:38–42.Search in Google Scholar
36. Sysmex Corporation. Automated hematology analyzer/transportation units. XN-series (XN-9000/XN9100). Instructions for use. 2017.Search in Google Scholar
37. Posit, Team. RStudio. Integrated development environment for R. Posit Software. Boston, MA: PBC; 2023. Available from: http://www.posit.co/.Search in Google Scholar
38. Carstensen, B, Plummer, M, Laara, E, Hills, M. Epi: a package for statistical analysis in epidemiology. R package version 2.47; 2022. Available from: https://CRAN.R-project.org/package=Epi.Search in Google Scholar
39. Robin, X, Turck, N, Hainard, A, Tiberti, N, Lisacek, F, Sanchez, JC, et al.. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinf 2011;12:77. https://doi.org/10.1186/1471-2105-12-77.Search in Google Scholar PubMed PubMed Central
40. Wei, T, Simko, V. R package ‘corrplot’: visualization of a correlation matrix (Version 0.92); 2021. Available from: https://github.com/taiyun/corrplot.Search in Google Scholar
41. Tomberg, K, Kool, P, Lind, E, Jerjomina, J, Tomberg, K, Barotov, O, et al.. Hematoloogilise automaatuuringu referentsväärtused Eesti täiskasvanutel. Eesti Arst 2020;99:277–83.Search in Google Scholar
42. van Pelt, JL, Klatte, S, Hwandih, T, Barcaru, A, Riphagen, IJ, Linssen, J, et al.. Reference intervals for Sysmex XN hematological parameters as assessed in the Dutch Lifelines cohort. Clin Chem Lab Med 2022;60:907–20. https://doi.org/10.1515/cclm-2022-0094.Search in Google Scholar PubMed
43. Koca, E. Bone marrow iron staining is a reliable test for elimination of iron deficiency anemia rather than its diagnosis. UHOD 2013;23:260–3. https://doi.org/10.4999/uhod.13011.Search in Google Scholar
44. Cappellini, MD, Comin-Colet, J, de Francisco, A, Dignass, A, Doehner, W, Lam, CS, et al.. Iron deficiency across chronic inflammatory conditions: international expert opinion on definition, diagnosis, and management: CAPPELLINI et al. Am J Hematol 2017;92:1068–78. https://doi.org/10.1002/ajh.24820.Search in Google Scholar PubMed PubMed Central
45. Speeckaert, MM, Speeckaert, R, Delanghe, JR. Biological and clinical aspects of soluble transferrin receptor. Crit Rev Clin Lab Sci 2010;47:213–28. https://doi.org/10.3109/10408363.2010.550461.Search in Google Scholar PubMed
46. Girelli, D, Marchi, G, Camaschella, C. Anemia in the elderly. HemaSphere 2018;2:e40. https://doi.org/10.1097/hs9.0000000000000040.Search in Google Scholar PubMed PubMed Central
47. Lyle, L, Hirose, A. Iron overload in myelodysplastic syndromes: pathophysiology, consequences, diagnosis, and treatment. J Adv Pract Oncol 2018;9:392–405. https://doi.org/10.6004/jadpro.2018.9.4.3.Search in Google Scholar
48. Kim, SY, Park, Y, Kim, H, Kim, J, Kwon, GC, Koo, SH. Discriminating myelodysplastic syndrome and other myeloid malignancies from non-clonal disorders by multiparametric analysis of automated cell data. Clin Chim Acta 2018;480:56–64. https://doi.org/10.1016/j.cca.2018.01.029.Search in Google Scholar PubMed
49. Oster, HS, Crouch, S, Smith, A, Yu, G, Abu Shrkihe, B, Baruch, S, et al.. A predictive algorithm using clinical and laboratory parameters may assist in ruling out and in diagnosing MDS. Blood Adv 2021;5:3066–75. https://doi.org/10.1182/bloodadvances.2020004055.Search in Google Scholar PubMed PubMed Central
50. Torres Gomez, A, Casaño, J, Sánchez, J, Madrigal, E, Blanco, F, Alvarez, MA. Utility of reticulocyte maturation parameters in the differential diagnosis of macrocytic anemias. Clin Lab Haematol 2003;25:283–8. https://doi.org/10.1046/j.1365-2257.2003.00536.x.Search in Google Scholar PubMed
51. Lesesve, JF, Daliphard, S, Callat, MP, Lenormand, B. Increase of immature reticulocyte fraction in myelodysplastic syndromes. Clin Lab Haematol 2004;26:301–2. https://doi.org/10.1111/j.1365-2257.2004.00620.x.Search in Google Scholar PubMed
52. Rauw, J, Wells, RA, Chesney, A, Reis, M, Zhang, L, Buckstein, R. Validation of a scoring system to establish the probability of myelodysplastic syndrome in patients with unexplained cytopenias or macrocytosis. Leuk Res 2011;35:1335–8. https://doi.org/10.1016/j.leukres.2011.05.001.Search in Google Scholar PubMed
53. Hwang, SM, Nam, Y. Complete blood count and cell population data parameters from the Abbott Alinity hq analyzer are useful in differentiating myelodysplastic syndromes from other forms of cytopenia. Int J Lab Hematol 2022;44:468–76. https://doi.org/10.1111/ijlh.13777.Search in Google Scholar PubMed
Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/cclm-2023-0772).
© 2023 Walter de Gruyter GmbH, Berlin/Boston
