Utility of Flowcytometry in the Diagnosis of Myelodysplasia in Routine Laboratories
Authors: Ramamoorthy Suthanthira , Tipping Peta , Li Zi 
Published: December 2023

INTRODUCTION

Myelodysplastic syndromes (MDSs) cover a wide range of abnormalities, ranging from subtle morphological changes to overt findings such as prominently skewed morphology. The clinical picture is dominated by cytopenia of one or more lineages, defined by Haemoglobin&lt;100g/L, absolute neutrophil count &lt;1.8 x 10^9/L and platelets less than 100 x 10^9/L. The aberrant features, suggestive of MDS that can be picked up by flow cytometry can occasionally be missed on morphological features. In the presence of clonal haematopoiesis, these features detected by flow cytometry may help us to confidentially apply a label of MDS to an individual.

MATERIALS AND METHODS All patients with suspected myelodysplastic syndrome and patients with acute myeloid leukemia (AML) &lt;30% blasts. Profound dominance of myeloid blasts in a patient with AML automatically earns the patient the 2 points needed for the MDS label and the myeloblast dominance inevitably outnumbers B-cell progenitors, which will affect the Ogata scoring.Exclusion criteria: &gt;2% monoclonal lymphocytes by flow cytometry&lt;400 CD34+ events in the collected sample

Parameters included: Ogata

A simple 4-point scoring system by Ogata. Other features included as per European Leukemia Net guidelines on flow cytometry on MDS

We included following nine parameters to be analysed in addition to the Ogata criteria:

Myeloid progenitors: Increased expression of CD11bAbnormal expression of CD7 in progenitor cells (CD34/CD117 Positive cells)

Monocytic Lineage: Decreased expression of CD11bDecreased expression of HLA-DRDecreased expression of CD14

Myeloid Lineage: Diminished expression of CD45Decreased expression of CD11bDecreased expression of CD13 or CD33 (Any one of them)Decreased expression of CD10

RESULTS

In our analysis of normal patients, Ogata score was frequently positive in the category lymphocyte/ myeloblast CD45 ratio. This obviously may affect the sensitivity. In the series of 20 patients we analysed, we had only one patient with combined score of four or less (patient no: 12). Two patients with Ogata score of less than two fulfilled the flow cytometric criteria using the combined criteria (Patient no: 3 and 5). Since our numbers were low, we do not know whether the combined scoring system would gain more significance in a large cohort of patients.

In one of the normal patients who presented with cytopenia with high MCV (patient no: 10) the morphological and flow cytometry features were not consistent with myelodysplasia. Moreover, the patient did not have clonal abnormalities. This patient could have classified as myelodysplasia by flow cytomeric criteria if Ogata score alone had been used.

The sensitivity of the combined parameters in detecting myelodysplasia is 89.4% and specificity is 90.9%.

CONCLUSION

We devised this system based on the principles that, the Ogata scoring system is simple and reproducible. Moreover, its sensitivity can be improved by using nine additional markers based on WELLS criteria, which can be analysed based on mean fluorescence intensity (MFI) alone without much complexity. Our methodology was not demanding and it did not involve usage of special fluorescent dyes and hence can be reproduced in any routine diagnostic laboratories. In addition, we found that both sensitivity and specificity of Ogata scoring system has been improved by inclusion of the other parameters in this study. Our scoring system did not show any correlation with reference to the R-IPSS (Revised International Scoring System in myelodysplasia) at diagnosis.

Many attempts have been made so far with extensive markers and application of Automated Intelligence strategies for the analysis of more complex combinations of parameters. However, a simplified, user friendly and cost effective method is the need of the hour.