A computer simulation for exploring the detection of monoclonal B-cell lymphocytosis by flow cytometry

Abstract

Background: Monoclonal B-cell lymphocytosis (MBL) is defined by the presence of monoclonal B-cells in peripheral blood in the absence of hematologic disease. MBL is detected by flow cytometry with increasing frequency as the number of B-cells acquired increases. Methods: Computer simulations in R language were used to examine the impact of increasing the number of B-cells acquired on the sensitivity of detecting MBL and to explore the possibility of detecting distinct B-cell clones among polyclonal B-cell populations. Results: With simulated populations containing 0.1%-1.0% monoclonal B-cells, the number of clonal B-cells detected showed a normal distribution in the upper range of clonal cells acquired and more nearly log-normal as the distributions became bounded by 0. The distributions peaked around the clonal prevalence. The detection of MBL increased sharply with a small increase in the total number of B-cells acquired when the number of clonal cells acquired was near the MBL cutoff point. MBL could be detected in log-normally distributed polyclonal B-cell populations. Conclusions: Sampling variability in detecting monoclonal B-cells can be investigated through simulation. The observed population prevalence of MBL can be approximated with reasonable assumptions about the distribution of clonotypes in the circulating B-cell compartment. © 2010 International Clinical Cytometry Society.