In our high-sensitivity flow cytometric approach for systemic mastocytosis (SM), we identified mast cell event clustering as a new diagnostic criterion for the disease.
To objectively characterize mast cell gated event distributions, we performed cluster analysis using FLOCK, a computational approach to identify cell subsets in multidimensional flow cytometry data in an unbiased, automated fashion.
FLOCK identified discrete mast cell populations in most cases of SM (56/75 [75%]) but only a minority of non-SM cases (17/124 [14%]). FLOCK-identified mast cell populations accounted for 2.46% of total cells on average in SM cases and 0.09% of total cells on average in non-SM cases (P < .0001) and were predictive of SM, with a sensitivity of 75%, a specificity of 86%, a positive predictive value of 76%, and a negative predictive value of 85%.
FLOCK analysis provides useful diagnostic information for evaluating patients with suspected SM, and may be useful for the analysis of other hematopoietic neoplasms.