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Autor(en) / Beteiligte
Titel
Discriminating myelodysplastic syndrome and other myeloid malignancies from non-clonal disorders by multiparametric analysis of automated cell data
Ist Teil von
  • Clinica chimica acta, 2018-05, Vol.480, p.56-64
Ort / Verlag
Netherlands: Elsevier B.V
Erscheinungsjahr
2018
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • We investigated the usefulness of novel complete blood count (CBC) data for discriminating myeloid malignancies from non-clonal CBC abnormalities. Data were obtained during routine CBC tests of 119 samples from 37 myelodysplastic syndrome (MDS) patients, 92 samples from 45 myeloproliferative neoplasm (MPN) patients, and 15 samples from 11 chronic myelogenous leukemia (CML) patients using a DxH800 (Beckman Coulter). Data obtained from patients with hypocellular bone marrow and from those with other non-clonal diseases with CBC abnormalities were included in the comparisons. For cell population data of neutrophils, the means of median, upper median, lower median, and low angle light scatters were significantly lower in MDS patients than in patients without hematological malignancies. Low hemoglobin density (LHD) did not significantly differ between the MDS and non-clonal cytopenia patients, but it was significantly higher in the MPN and CML patients. We selected 13 parameters and scored the MDS diagnosis using cut-off values obtained from receiver operating characteristic (ROC) curve analysis. Using a score > 9, MDS was distinguished from non-clonal cytopenia with a sensitivity of 92.4% and a specificity of 85.4%. Multiparametric analyses of new automated parameters are useful for discriminating MDS from non-clonal cytopenia. •For neutrohpils, median of light scatters are significantly lower in MDS patients.•Low hemoglobin density was significantly higher in MPN and CML patients.•Multiparametric analysis of new automated parameters is useful for screening MDS.
Sprache
Englisch
Identifikatoren
ISSN: 0009-8981
eISSN: 1873-3492
DOI: 10.1016/j.cca.2018.01.029
Titel-ID: cdi_proquest_miscellaneous_1993016302

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