The Open Pathology Journal
2008, 2 : 78-85Published online 2008 July 9. DOI: 10.2174/1874375700802010078
Publisher ID: TOPATJ-2-78
Quantitative Flow Cytometry Immunophenotypic Data in Myelodysplastic Syndromes (MDS)
ABSTRACT
Background:
Recent studies using qualitative analysis of flow cytometry data have demonstrated various immunophenotypic abnormalities associated with myelodysplastic syndromes (MDS). However, there are limited reports assessing the ability of quantitative immunophenotypic analysis to discriminate MDS from other cytopenic conditions.
Design:
Using flow cytometry, we studied 37 bone marrow specimens from 23 patients with MDS and 14 cytopenic patients with non-clonal hematologic disorders. Samples were analyzed quantitatively for percentages of T-cells, B-cells, NK cells, granulocytes, monocytes, blasts, erythroid precursors, and plasma cells; CD4:CD8 ratio; % granulocyte subsets; % CD56+ monocytes; and % erythroid precursor subsets.
Results:
Quantitative analysis of immunophenotypic data in MDS patients compared to controls showed decreases in total granulocytes (p=0.037) and more mature subsets of CD11b+CD16bright granulocytes (p=0.0046) and CD10+ granulocytes (p=0.022). MDS patients also showed a trending increase in subset percentage of CD56+monocytes (p=0.056). Using receiver operating characteristic (ROC) analysis, cut-off values for these parameters favoring a diagnosis of MDS were identified as follows: total granulocytes < 60%, CD11b+CD16bright granulocytic subset < 40%, CD10+ granulocytic subset < 40%, and CD56+ monocytic subset > 10%. Subsequently, a scoring system was proposed whereby a score of one was assigned for the presence of each quantitative abnormality. Using this system on the original study population, the presence of at least two abnormalities (score2) revealed optimal sensitivity (69.6%) and specificity (71.4%) for a diagnosis of MDS.Quantitative analysis of immunophenotypic data in MDS patients compared to controls showed decreases in total granulocytes (p=0.037) and more mature subsets of CD11b+CD16bright granulocytes (p=0.0046) and CD10+ granulocytes (p=0.022). MDS patients also showed a trending increase in subset percentage of CD56+monocytes (p=0.056). Using receiver operating characteristic (ROC) analysis, cut-off values for these parameters favoring a diagnosis of MDS were identified as follows: total granulocytes < 60%, CD11b+CD16bright granulocytic subset < 40%, CD10+ granulocytic subset < 40%, and CD56+ monocytic subset > 10%. Subsequently, a scoring system was proposed whereby a score of one was assigned for the presence of each quantitative abnormality. Using this system on the original study population, the presence of at least two abnormalities (score≥2) revealed optimal sensitivity (69.6%) and specificity (71.4%) for a diagnosis of MDS.
Conclusion:
These findings suggest that quantitative analysis of immunophenotypic data can be complementary to qualitative interpretation. These data may be useful for distinguishing MDS from non-clonal cytopenic disorders and warrant prospective study in additional MDS patients.