title: 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.
authors.affiliation: patnyoun@gmail.com
authors.forename: Patrick D
authors.initials: PD
authors.lastname: Champion
mesh_terms: D001402:B-Lymphocytes / Q000276:immunology / Q000473:pathology*; D002999:Clone Cells; D003198:Computer Simulation; D005434:Flow Cytometry / Q000379:methods* / Q000706:statistics & numerical data; D018655:Lymphocyte Count / Q000706:statistics & numerical data; D008218:Lymphocytosis / Q000097:blood / Q000175:diagnosis* / Q000276:immunology; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D018401:Sample Size; D013269:Stochastic Processes