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Research use only and cell population data items obtained from the Beckman Coulter DxH800 automated hematology analyzer are useful in discriminating MDS patients from those with cytopenia without MDS

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Abstract

We investigated the performance of research use only/cell population data (RUO/CPD) items obtained from the Beckman Coulter DxH800 automated hematologic analyzer in discriminating MDS patients from cytopenic patients without MDS.

Total of 14 routine CBC, 18 research use only (RUO) items, and 70 CPD items were obtained retrospectively at diagnosis. The results were then compared between 94 MDS patients and 100 cytopenic patients without MDS. In items with statistically significant differences, receiver operating characteristic (ROC) analysis was performed and the results were compared.

Four CBC/RUO items [red cell distribution width-standard deviation (RDW-SD), immature reticulocyte fraction (IRF), mean sphered cell volume (MSCV), high light scatter reticulocytes (HLR)], and two CPD items [mean volume of neutrophils (NE-V-Mean) and mean volume of early granulated cells (EGC-V-Mean)] showed area-under the curve (AUC) scores > 0.750. Notably, four RUO/CPD items (MSCV > 81.4/HLR > 0.15%/NE-V-Mean > 145/EGC-V-Mean > 156) showed high sensitivity (91.9%/93.6%/88.1%/90.2%, respectively) in discriminating MDS patients from cytopenic patients without MDS. With these six items, scores ≥ 4 (defined as ≥ 4 items exceeding cutoff values out of six items) showed AUC scores/sensitivity/specificity/accuracy (0.891/87.3%/79.0%/83.0%, respectively).

Six CBC/RUO/CPD items showed satisfactory AUC scores of > 0.750, and four RUO/CPD items showed high sensitivity in discriminating MDS patients from cytopenic patients without MDS. Scoring system with six items showed high sensitivity, specificity, and accuracy with decision criteria of ≥ 4 scores. Therefore, DxH800 RUO/CPD items would be useful in discriminating MDS patients from cytopenic patients without MDS.

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Data Availability

The raw data of the evaluation is available from the corresponding author upon request.

References

  1. Cazzola M, Malcovati L (2005) Myelodysplastic syndromes--coping with ineffective hematopoiesis. N Engl J Med 362:536–538

    Article  Google Scholar 

  2. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H et al (2016) WHO classification of tumours of hematopoietic and lymphoid tissues. Revised 4th ed. IARC Press, Lyon

    Google Scholar 

  3. Khoury JD, Solary E, Abla O, Akkari Y, Alaggio R, Apperley JF et al (2022) The 5th edition of the World Health Organization classification of haematolymphoid tumours: myeloid and histiocytic/dendritic neoplasms. Leukemia 36:1703–1719

    Article  PubMed  PubMed Central  Google Scholar 

  4. Arber DA, Orazi A, Hasserjian RP, Borowitz MJ, Calvo KR, Kvasnicka HM et al (2022) International consensus classification of myeloid neoplasms and acute leukemias: integrating morphologic, clinical, and genomic data. Blood 140:1200–1228

    Article  CAS  PubMed  Google Scholar 

  5. Font P, Loscertales J, Benavente C, Bermejo A, Callejas M, Garcia-Alonso L et al (2013) Inter-observer variance with the diagnosis of myelodysplastic syndromes (MDS) following the 2008 WHO classification. Ann Hematol 92:19–24

    Article  CAS  PubMed  Google Scholar 

  6. Font P, Loscertales J, Soto C, Ricard P, Novas CM, Martín-Clavero E et al (2015) Interobserver variance in myelodysplastic syndromes with less than 5 % bone marrow blasts: unilineage vs. multilineage dysplasia and reproducibility of the threshold of 2 % blasts. Ann Hematol 94:565–573

    Article  PubMed  Google Scholar 

  7. Chaves F, Tierno B, Xu D (2006) Neutrophil volume distribution width: a new automated hematologic parameter for acute infection. Arch Pathol Lab Med 130:378–380

    Article  PubMed  Google Scholar 

  8. Bagdasaryan R, Zhou Z, Tierno B, Rosenman D, Xu D (2007) Neutrophil VCS parameters are superior indicators for acute infection. Lab Hematol 13:12–16

    Article  PubMed  Google Scholar 

  9. Mardi D, Fwity B, Lobmann R, Ambrosch A (2010) Mean cell volume of neutrophils and monocytes compared with C-reactive protein, interleukin-6 and white blood cell count for prediction of sepsis and nonsystemic bacterial infections. Int J Lab Hematol 32:410–418

    CAS  PubMed  Google Scholar 

  10. Miguel A, Orero M, Simon R, Collado R, Perez PL, Pacios A et al (2007) Automated neutrophil morphology and its utility in the assessment of neutrophil dysplasia. Lab Hematol 13:98–102

    Article  PubMed  Google Scholar 

  11. Haschke-Becher E, Vockenhuber M, Niedetzky P, Totzke U, Gabriel C (2008) A new high-throughput screening method for the detection of chronic lymphatic leukemia and myelodysplastic syndrome. Clin Chem Lab Med 46:85–88

    Article  CAS  PubMed  Google Scholar 

  12. Furundarena JR, Araiz M, Uranga M, Sainz MR, Agirre A, Trassorras M et al (2010) The utility of the Sysmex XE-2100 analyzer’s NEUTX and NEUT-Y parameters for detecting neutrophil dysplasia in myelodysplastic syndromes. Int J Lab Hematol 32:360–366

    Article  CAS  PubMed  Google Scholar 

  13. Raess PW, van de Geijn GJ, Njo TL, Klop B, Sukhachev D, Wertheim G et al (2014) Automated screening for myelodysplastic syndromes through analysis of complete blood count and cell population data parameters. Am J Hematol 89:369–374

    Article  PubMed  Google Scholar 

  14. Kim SY, Park Y, Kim H, Kim J, Kwon GC, Koo SH (2018) Discriminating myelodysplastic syndrome and other myeloid malignancies from non-clonal disorders by multiparametric analysis of automated cell data. Clin Chim Acta 480:56–64

    Article  CAS  PubMed  Google Scholar 

  15. Lee SE, Lim J, Kim Y, Min WS, Han K (2012) Leukocyte cell population analysis from the coulter automatic blood cell analyzer DxH800 to monitor the effect of G-CSF. J Clin Lab Anal 26:194–199

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Park DH, Park K, Park J, Park HH, Chae H, Lim J et al (2011) Screening of sepsis using leukocyte cell population data from the Coulter automatic blood cell analyzer DxH800. Int J Lab Hematol. 33:391–399

    Article  PubMed  Google Scholar 

  17. Jung YJ, Kim JH, Park YJ, Kahng J, Lee H, Lee KY et al (2012) Evaluation of cell population data on the UniCel DxH 800 Coulter cellular analysis system as a screening for viral infection in children. Int J Lab Hematol 34:283–289

    Article  PubMed  Google Scholar 

  18. Park J, Lee H, Kim YK, Kim KH, Lee W, Lee KY et al (2014) Automated screening for tuberculosis by multiparametric analysis of data obtained during routine complete blood count. Int J Lab Hematol 36:156–164

    Article  CAS  PubMed  Google Scholar 

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SHP, H-KK, JJ, SHL, YJL, YJK, J-CJ and J-HL performed the literature research and conceived the study. SHP, YJL, YJK, and J-CJ gathered clinical data. SHP performed statistical analyses and wrote the first draft of the manuscript. J-HL supervised the process and reviewed, edited, and approved the final version of this manuscript. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

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Correspondence to Ji-Hun Lim.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. This study was approved by the institutional review board of the Ulsan University Hospital (Approval number: UUH-2022-10-008).

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Since this study was based on the retrospective design, informed consent was waived and IRB approved this.

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Park, S.H., Kim, HK., Jeong, J. et al. Research use only and cell population data items obtained from the Beckman Coulter DxH800 automated hematology analyzer are useful in discriminating MDS patients from those with cytopenia without MDS. J Hematopathol 16, 143–154 (2023). https://doi.org/10.1007/s12308-023-00552-9

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