Literature DB >> 34877795

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.

Sang Mee Hwang1,2, Youngwon Nam1,2.   

Abstract

INTRODUCTION: Myelodysplastic syndromes (MDS) are characterized by morphologic dysplasia and cytopenia and have a propensity for acute leukemic transformation. However, dysplasia is diagnosed by morphology, thus having cell population data (CPD) that can differentiate cytopenic patients with MDS from other conditions may facilitate accurate diagnosis. We assessed the utility of complete blood count (CBC) parameters and CPD derived from an Abbott Alinity hq analyzer to discriminate MDS-related cytopenia.
METHODS: The patient cohort (n = 345) included 64 samples from patients with MDS, 162 from patients with other cytopenia, and 119 from healthy controls. The hematological parameters and research use-only parameters of the Abbott Alinity hq analyzer were compared between the cytopenic groups. The effectiveness of the individual standard and research CBC parameters to differentiate MDS from other forms of cytopenia was assessed through a receiver operating characteristics (ROC) analysis.
RESULTS: The percentage of MAC (Macrocytic RBCs) and hemoglobin distribution width (HDW) were higher in the MDS group than in the other cytopenia group and showed the greatest difference between both groups, with an area under the curve (AUC) of 0.766 (0.678-0.855) and 0.786 (0.702-0.870), respectively. The platelet distribution width was higher in the MDS group than in the other cytopenia group, with an AUC of 0.697 (0.623-0.770). WBC CPD extracted from histograms, especially Atyp-PMN-loc and Neu-ALL-M, showed high AUCs of 0.815 (0.750-0.879) and 0.778 (0.711-0.845), respectively.
CONCLUSION: Our findings demonstrate the clinical utility of CPD and hematology parameters of the Abbott Alinity hq analyzer in the differential diagnosis of MDS.
© 2021 John Wiley & Sons Ltd.

Entities:  

Keywords:  Abbott Alinity hq; cell population parameter; complete blood count; hematology analyzer; myelodysplastic syndromes

Mesh:

Year:  2021        PMID: 34877795     DOI: 10.1111/ijlh.13777

Source DB:  PubMed          Journal:  Int J Lab Hematol        ISSN: 1751-5521            Impact factor:   2.877


  2 in total

Review 1.  Automated Detection of Dysplasia: Data Mining from Our Hematology Analyzers.

Authors:  Jaja Zhu; Sylvain Clauser; Nicolas Freynet; Valérie Bardet
Journal:  Diagnostics (Basel)       Date:  2022-06-26

2.  Machine learning-based improvement of MDS-CBC score brings platelets into the limelight to optimize smear review in the hematology laboratory.

Authors:  Jaja Zhu; Pierre Lemaire; Stéphanie Mathis; Emily Ronez; Sylvain Clauser; Katayoun Jondeau; Pierre Fenaux; Lionel Adès; Valérie Bardet
Journal:  BMC Cancer       Date:  2022-09-10       Impact factor: 4.638

  2 in total

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