Automated Early Detection of Myelodysplastic Syndrome within the General Population Using the Research Parameters of Beckman-Coulter DxH 800 Hematology Analyzer.
Cancers (Basel) 2021;
13:cancers13030389. [PMID:
33494332 PMCID:
PMC7865695 DOI:
10.3390/cancers13030389]
[Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 01/09/2021] [Accepted: 01/18/2021] [Indexed: 11/17/2022] Open
Abstract
Simple Summary
A substantial fraction of the elderly population suffers from moderate anemia, and blood smear analysis can guide towards a diagnosis of myelodysplastic syndrome (MDS). Nevertheless, in medical laboratories, blood smear review is only performed when quantitative or qualitative flags occur upon complete blood count (CBC). Consequently, the suspicion of MDS can be delayed in the absence of systematic blood smear observation, which is crucial to initiate a full diagnosis process by cytological analysis of bone marrow aspiration. The Beckman Coulter DxH 800 hematology analyzer (Beckman-Coulter, Brea, CA) is widely used over the world. We propose in this study the clinical use of 10 unexploited “research parameters” for early detection of subclinical MDS by selective triggering of blood smear examination.
Abstract
The incidence of myelodysplastic syndrome increases with aging and the early diagnosis enables optimal care of these diseases. The DxH 800 hematology analyzer measures and calculates 126 cytological parameters, but only 23 are used for routine CBC assessment. The goal of this study was to use the 103 unexploited “research parameters” to develop an algorithm allowing for an early detection of subclinical MDS patients by triggering morphological analysis. Blood sample parameters from 101 MDS patients and 88 healthy volunteers were analyzed to identify the critical “research parameters” with: (i) the most significant differences between MDS patients and healthy volunteers, (ii) the best contributions to principal component analysis (PCA), first axis, and (iii) the best correlations with PCA, first two axes (cos2 > 0.6). Ten critical “research parameters” of white blood cells were identified, allowing for the calculation of an MDS-likelihood score (MDS-LS), based on logistic regression. Automatic calculation of the MDS-LS is easily implementable on the middleware system of the DxH 800 to generate a flag for blood smear review, and possibly early detection of MDS patients in the general population.
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