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A new approach for diagnosing hematological malignancies using monocytosis workflow optimization and abnormal lymphocyte/blast flag of Sysmex XN series of blood count analyzers
Author(s) -
Kocaturk Evin,
Kusku Kiraz Zeynep,
Uskudar Teke Hava,
Demir Sukru Saygin,
Alatas Ibrahim Ozkan
Publication year - 2020
Publication title -
international journal of laboratory hematology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.705
H-Index - 55
eISSN - 1751-553X
pISSN - 1751-5521
DOI - 10.1111/ijlh.13281
Subject(s) - monocytosis , medicine , leukocytosis , chronic myelomonocytic leukemia , complete blood count , bone marrow , myelodysplastic syndromes
Monocytosis Workflow Optimization rule set has been developed by using mono‐dysplasia‐score to determine reactive monocytosis and prevent unnecessary blood smear of these patients and for detection of chronic myelomonocytic leukemia cases during complete blood count. In our study, we aimed to examine the contribution of Monocytosis Workflow Optimization rule set. Methods Adult patients with monocyte count ≥1.0 10 3 /µL and monocyte percentage ≥10% were included in our study. Blood smears were made from the samples in our laboratory. These smears were examined and patients were divided into two groups as reactive monocytosis or hematological malignancy. The groups were compared in terms of Monocytosis Workflow Optimization rule set and device flags. Results Twenty‐one patients had hematological malignancies of 155 patients who were included in our study. Monocytosis Workflow Optimization rule set suggested performing blood smear in 19 of the patients with hematological malignancy, and evaluated two patients as reactive monocytosis with 90.5% sensitivity and 76.9% specificity. There was an “abnormal lymphocyte/ blast” flag in 90.5% of patients with hematological malignancies and in patients whose Monocytosis Workflow Optimization rule set defined as reactive monocytosis and it was found that sensitivity and negative predictive value reached 100%. Conclusion Automated validation support systems and softwares developed especially for these systems make it possible to classify patients with their non‐specific findings, as a result both contributing to the reduction of laboratory workload and costs and assisting laboratory specialists and clinicians with adding value to laboratory results.