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A Novel Method to Assess Bone Marrow Purity is Useful in Determining Blast Percentage by Flow Cytometry in Acute Myeloid Leukemia and Myelodysplasia

Journal: Annals of Hematology & Oncology (Vol.2, No. 5)

Publication Date:

Authors : ; ; ; ; ; ;

Page : 1-8

Keywords : Acute myeloid leukemia; Myelodysplastic syndrome; Blast normalization; Flow cytometry; Peripheral blood dilution; Bone marrow purity;

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Abstract

Blast quantification by Flow Cytometry (FCM) may become essential in situations where morphologic evaluation is difficult or unavailable. As hemodilution invariably occurs, a means of determining Bone Marrow Purity (BMP) and normalizing FCM blast counts is essential, especially when blast percentages are diagnostically critical as in Acute Myeloid Leukemia (AML) and Myelodysplasia (MDS). By evaluating different leukocyte populations in eight initial patients, a formula to predict BMP was developed and compared to the actual BMP determined by manual counts. Performance of the formula was then validated in 86 AML/MDS patients by comparing normalized FCM blast counts to those determined by the reference manual method. A Acronym previously defined in abstract formula was empirically developed, primarily based on changes in lymphocytes which reliably correlated with the actual BMP (R2 = 0.8955). Components of the formula were derived entirely from automated lymphocyte and total leukocyte counts from the peripheral blood and FCM analyses. BMP formula was then validated in 86 AML/MDS patients. When used to normalize blast counts, the formula showed accurate correction when BMP fell between 40%-90%. In this group, correlation of normalized FCM and manual blast counts was acceptable (R? = 0.8335), being greatest at lower blast percentages. Normalization of the FCM blast count appropriately reclassified disease in 26.8% of cases. We identified a practical means of estimating hemodilution and allowing FCM blast normalization in the evaluation of AML and MDS. BMP assessment by this simple method improves the quality of the FCM data and facilitates accurate diagnosis and patient management.

Last modified: 2016-08-03 17:47:14