"Bone marrow aspirate automated counts on hematology analyzers: formulating a scoring system based on hematology parameters, to discriminate reactive versus myelodysplastic syndrome‐related bone marrows". (18th May 2019)

• Record Type: Journal Article
• Authors: Tsagarakis, Nikolaos J.; Paterakis, Georgios; Papadhimitriou, Stefanos I.; Kritikou‐Griva, Elpiniki; Goumakou, Eleni; Oudatzis, Georgios; Theodorakos, Ioannis; Vasileiou, Paraskevi
• Is Part Of: International journal of laboratory hematology. Volume 41:Number 4(2019:Aug.)
• Page Start: 542
• Page End: 549
• Publication Date: 2019-05-18
• Subjects: hematology analyzer -- MDS -- myelodysplastic syndromes -- reactive bone marrow -- scoring system; Hematology -- Periodicals; Blood -- Diseases -- Periodicals; Hematology -- Periodicals; 616.15005
• DOI: 10.1111/ijlh.13049
• Languages: English
• ISSNs: 1751-5521

Abstract

Abstract: Introduction: Diagnosis of myelodysplastic syndromes (MDS) is usually challenging. In this context, we have attempted to employ data derived from automated analysis of bone marrow (BM) samples as an ancillary tool for the discrimination between reactive marrow and MDS. Methods: A total of 101 BM anticoagulated samples referred for flow cytometry (FCM) analysis on the clinical suspicion of MDS had been previously counted in a Mindray BC‐6800 hematology analyzer (testing set). Among them, 22/101 randomly selected BM samples (comparison set) had been also simultaneously counted by an Advia 2120 and a CELL‐DYN Sapphire hematology analyzer. Selected parameters obtained by Mindray BC‐6800 were retrospectively evaluated with ROC and regression analysis in an attempt to formulate a discriminative scoring system (SS) for MDS. This system was further evaluated in the comparison set. Results: The diagnosis of MDS was established in 37/101 patients assessed ("MDS" group). Three patients were diagnosed with myelodysplastic/myeloproliferative neoplasm (MDS/MPN), while 61 revealed a "reactive" bone marrow ("RBM" group). Statistical analysis revealed significant differences in Hb, RDW‐CV%, NRBC%, and RET% values between the "MDS" and the "RBM" group. Specific cutoff values were then indicated and employed for the formulation of a SS of high sensitivity (86.84%) and specificity (86.89%). The encouraging performance characteristics of the proposed SS were also confirmed in the BM comparison set. Conclusion: Automated BM counts on hematology analyzers contributed to the formulation of a SS for the screening discrimination between reactive and MDS BM fluids, which seems to be applicable and informative, regardless of the analyzer used.