Skip to main content
SpringerLink
Log in

Flow cytometric analysis of peripheral blood neutrophil myeloperoxidase expression for ruling out myelodysplastic syndromes: a prospective validation study

  • Original Article
  • Published:
Annals of Hematology Aims and scope Submit manuscript

Abstract

Suspicion of myelodysplastic syndromes (MDS) is the most common reason for bone marrow aspirate in elderly patients. This study aimed to prospectively validate the accuracy for flow cytometric analysis of peripheral blood neutrophil myeloperoxidase expression in ruling out MDS. We enrolled 62 consecutive patients who were referred for suspected MDS, based on medical history and peripheral blood cytopenia. The accuracy of intra-individual robust coefficient of variation (RCV) for peripheral blood neutrophil myeloperoxidase expression was assessed with a prespecified 30% threshold. Cytomorphological evaluation of bone marrow aspirate performed by experienced hematopathologists confirmed MDS in 23 patients (prevalence, 37%), unconfirmed MDS in 32 patients (52%, including 3 patients with idiopathic cytopenia of undetermined significance (ICUS)), and was uninterpretable in 7 patients (11%). The median intra-individual RCV values for neutrophil myeloperoxidase expression in peripheral blood were 37.4% (range, 30.7–54.1), 29.2% (range, 28.1–32.1), and 29.1% (range, 24.7–37.8) for patients with confirmed suspicion of MDS, ICUS, and unconfirmed suspicion of MDS, respectively (P<0.001). The area under the ROC curve was 0.92 (95% confidence interval, 0.86–0.99). An intra-individual RCV value lower than 30% ruled out MDS for 35% (i.e., 19/55) patients referred for suspected disease, with 100% sensitivity (95% CI, 85–100%) and 100% negative predictive value (95% CI, 82–100%) estimates. This study shows that flow cytometric analysis of peripheral blood neutrophil myeloperoxidase expression might obviate the need for bone marrow aspirate for 35% of patients with suspected MDS. Trial registration: ClinicalTrials.gov identifier: NCT03363399 (first posted on December 6, 2017)

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Data Availability

The de-identified datasets analyzed as part of the current study are available upon request to the corresponding author after arranging a data sharing agreement.

Code availability

Not applicable.

References

  1. Cazzola M (2020) Myelodysplastic syndromes. N Engl J Med 383:1358–1374

    Article  CAS  Google Scholar 

  2. Nachtkamp K, Stark R, Strupp C, Kündgen A, Giagounidis A, Aul C, Hildebrandt B, Haas R, Gattermann N, Germing U (2016) Causes of death in 2877 patients with myelodysplastic syndromes. Ann Hematol 95:937–944

    Article  Google Scholar 

  3. Zeidan AM, Shallis RM, Wang R, Davidoff A, Ma X (2019) Epidemiology of myelodysplastic syndromes: why characterizing the beast is a prerequisite to taming it. Blood Rev 34:1–15

    Article  Google Scholar 

  4. Garcia-Manero G, Chien K, Montalban-Bravo G (2020) Myelodysplastic syndromes: 2021 update on diagnosis, risk-stratification and management. Am J Hematol 95:1399–1420

    Article  Google Scholar 

  5. Fenaux P, Haase D, Santini V, Sanz GF, Platzbecker U, Mey U (2021) Myelodysplastic syndromes: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol 32:142–156

    Article  CAS  Google Scholar 

  6. Buckstein R, Jang K, Friedlich J, Zhang L, Reis M, Chesney A, Wells RA (2009) Estimating the prevalence of myelodysplastic syndromes in patients with unexplained cytopenias: a retrospective study of 322 bone marrows. Leuk Res 33:1313–1318

    Article  Google Scholar 

  7. Gendron N, Zia Chahabi S, Poenou G, Rivet N, Belleville-Rolland T, Lemaire P et al (2019) Pain assessment and factors influencing pain during bone marrow aspiration: a prospective study. PLoS One 14:e0221534

    Article  CAS  Google Scholar 

  8. Bain BJ (2006) Morbidity associated with bone marrow aspiration and trephine biopsy - a review of UK data for 2004. Haematologica 91:1293–1294

    PubMed  Google Scholar 

  9. Shestakova A, Nael A, Nora V, Rezk S, Zhao X (2020) Automated leukocyte parameters are useful in the assessment of myelodysplastic syndromes. Cytometry B Clin Cytom. https://doi.org/10.1002/cyto.b.21947

  10. Boutault R, Peterlin P, Boubaya M, Sockel K, Chevallier P, Garnier A et al (2018) A novel complete blood count-based score to screen for myelodysplastic syndrome in cytopenic patients. Br J Haematol 183:736–746

    Article  CAS  Google Scholar 

  11. Raskovalova T, Berger MG, Jacob MC, Park S, Campos L, Aanei CM et al (2019) Flow cytometric analysis of neutrophil myeloperoxidase expression in peripheral blood for ruling out myelodysplastic syndromes: a diagnostic accuracy study. Haematologica 104:2382–2390

    Article  CAS  Google Scholar 

  12. Sackett DL, Haynes RB (2002) The architecture of diagnostic research. BMJ 324:539–541

    Article  CAS  Google Scholar 

  13. Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L et al (2015) STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ 351:h5527

    Article  Google Scholar 

  14. Della Porta MG, Picone C, Pascutto C, Malcovati L, Tamura H, Handa H et al (2012) Multicenter validation of a reproducible flow cytometric score for the diagnosis of low-grade myelodysplastic syndromes: results of a European LeukemiaNET study. Haematologica 97:1209–1217

    Article  Google Scholar 

  15. Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM et al (2016) The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood 127:2391–2405

    Article  CAS  Google Scholar 

  16. Valent P (2019) ICUS, IDUS, CHIP and CCUS: diagnostic criteria, separation from MDS and clinical implications. Pathobiology 86:30–38

    Article  CAS  Google Scholar 

  17. Patnaik MM, Tefferi A (2020) Chronic myelomonocytic leukemia: 2020 update on diagnosis, risk stratification and management. Am J Hematol 95:97–115

    Article  CAS  Google Scholar 

  18. Greenberg P, Cox C, LeBeau MM, Fenaux P, Morel P, Sanz G et al (1997) International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood 89:2079–2088

    Article  CAS  Google Scholar 

  19. Aires A, Teixeira MDA, Lau C, Moreira C, Spinola A, Mota A et al (2018) A pilot study on the usefulness of peripheral blood flow cytometry for the diagnosis of lower risk myelodysplastic syndromes: the “MDS thermometer”. BMC Hematol 18:6

    Article  Google Scholar 

  20. Cherian S, Moore J, Bantly A, Vergilio JA, Klein P, Luger S, Bagg A (2005) Peripheral blood MDS score: a new flow cytometric tool for the diagnosis of myelodysplastic syndromes. Cytometry B Clin Cytom 64:9–17

    Article  Google Scholar 

  21. Meyerson HJ, Osei E, Schweitzer K, Blidaru G, Edinger A, Balog A (2013) CD177 expression on neutrophils: in search of a clonal assay for myeloid neoplasia by flow cytometry. Am J Clin Pathol 140:658–669

    Article  Google Scholar 

  22. Rashidi HH, Xu X, Wang HY, Shafi NQ, Rameshkumar K, Messer K et al (2012) Utility of peripheral blood flow cytometry in differentiating low grade versus high grade myelodysplastic syndromes (MDS) and in the evaluation of cytopenias. Int J Clin Exp Pathol 5:224–230

    PubMed  PubMed Central  Google Scholar 

  23. Sandes AF, Yamamoto M, Matarraz S, Chauffaille Mde L, Quijano S, Lopez A et al (2012) Altered immunophenotypic features of peripheral blood platelets in myelodysplastic syndromes. Haematologica 97:895–902

    Article  Google Scholar 

  24. Selimoglu-Buet D, Wagner-Ballon O, Saada V, Bardet V, Itzykson R, Bencheikh L et al (2015) Characteristic repartition of monocyte subsets as a diagnostic signature of chronic myelomonocytic leukemia. Blood 125:3618–3626

    Article  CAS  Google Scholar 

  25. Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB et al (2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155:529–536

    Article  Google Scholar 

  26. Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Sole F et al (2016) Cytopenia levels for aiding establishment of the diagnosis of myelodysplastic syndromes. Blood 128:2096–2097

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors thank Drs. Frédéric Garban, Lysiane Molina, Martin Carré, Stéphane Courby, Brigitte Pégourié, Anne Thiebaut-Bertrand, and Rémy Gressin for patient recruitment and Drs. Christine Lefebvre, Sylvie Tondeur, and Claire Vettier for cytogenetic, molecular, and cytomorphological analysis. The authors are indebted to Séverine Beatrix, Laure Dusset, Ghislaine Del-Vecchio, Richard Di Schiena, Michel Drouin, Claire Gasquez, Frédérique Martinez, Karine Nicolino, and Christine Vallet for their technical assistance. The authors also thank Nicolas Gonnet for administrative support.

Funding

Becton Dickinson Biosciences provided antibodies free of charge. Statistical analysis was performed within the Grenoble Alpes Data Institute (ANR-15-IDEX-02). This research received no other specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Laboratoire d’immunologie, Centre Hospitalier Universitaire Grenoble Alpes, CS 10217, F-38043, Grenoble Cedex 9, France

    Tatiana Raskovalova, Marie-Christine Jacob & Laura Scheffen

  2. Clinique Universitaire d’Hématologie, Grenoble University Hospital, F-38043, Grenoble, France

    Claude-Eric Bulabois, Clara Mariette & Sophie Park

  3. Institute for Advanced Biosciences (IAB), INSERM U1209, CNRS UMR 5309, Université Grenoble Alpes, Grenoble, France

    Sophie Park

  4. Quality of Care Unit, INSERM CIC 1406, Grenoble University Hospital, F-38043, Grenoble, France

    José Labarère

  5. TIMC-IMAG, UMR 5525, CNRS, Université Grenoble Alpes, F-38043, Grenoble, France

    José Labarère

Authors
  1. Tatiana Raskovalova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marie-Christine Jacob
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Claude-Eric Bulabois
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Clara Mariette
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Laura Scheffen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sophie Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. José Labarère
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Tatiana Raskovalova provided project leadership, had full access to the data in the study, and takes responsibility for data integrity and accuracy of data analysis. Tatiana Raskovalova and Marie-Christine Jacob contributed to the study design, data acquisition, interpretation of the results, and manuscript preparation. Laura Scheffen contributed to data acquisition, interpretation of the results, and critical revision of the manuscript. Claude-Eric Bulabois, Clara Mariette, and Sophie Park enrolled participants, contributed to interpretation of the results, and critically revised the manuscript. José Labarère contributed to data management, statistical analysis, interpretation of the results, and manuscript preparation. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to Tatiana Raskovalova.

Ethics declarations

Ethics approval

An institutional review board (Comité de Protection des Personnes Sud Méditerranée I, Marseille, France) reviewed and approved the study protocol and the information form, prior to study initiation.

Consent to participate

According to French regulations, the consent to participate was sought under a regime of “non-opposition” (opt-out): after appropriate written information was delivered, data were collected except in case of opposition from the patient.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

ESM 1

(DOCX 16 kb).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Raskovalova, T., Jacob, MC., Bulabois, CE. et al. Flow cytometric analysis of peripheral blood neutrophil myeloperoxidase expression for ruling out myelodysplastic syndromes: a prospective validation study. Ann Hematol 100, 1149–1158 (2021). https://doi.org/10.1007/s00277-021-04446-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00277-021-04446-7

Keywords

Search

Navigation