Evaluation of the Flagging Performance of the Hematology Analyzer Sysmex XN Series on the Basis of "Q Values"

Arch Pathol Lab Med. 2018 Jan;142(1):83-88. doi: 10.5858/arpa.2016-0502-OA. Epub 2017 Aug 31.

Abstract

Context: - In the XN series of hematology analyzers (Sysmex, Kobe, Japan), the probability of the presence of abnormal cells is indicated by flags based on Q values.

Objective: - To evaluate the Q value performance of the Sysmex XN-20 modular analyzer.

Design: - The interinstrumental concordance, intrainstrumental precision, and diagnostic accuracy of Q values, with tested flags of "blasts/abnormal lymphocytes," "atypical lymphocytes," and "blasts," were investigated.

Results: - Absolute concordance rates in flagging between 2 analyzers ranged from 69.8% to 80.8%, and κ values ranged from 0.43 to 0.61. In samples with absolute related cell counts lower than 100/μL, the values ranged from 0.31 to 0.52. For intrainstrumental precision, standard deviations ranged from 4.8 to 23.9 for the blasts/abnormal lymphocytes, from 18.7 to 59.1 for the blasts, and from 11.0 to 23.0 for the atypical lymphocytes. Using a default Q value cutoff, diagnostic accuracy values based on the area under the curve, sensitivity, and specificity were, respectively, 0.910, 90.9%, and 72.2% for blasts/abnormal lymphocytes; 0.927, 84.9%, and 89.8% for blasts; and 0.865, 74.4%, and 84.9% for atypical lymphocytes. The diagnostic accuracy of Q values was much lower in samples with absolute related cell counts lower than 100/μL than in those 100/μL or higher.

Conclusions: - Q values of the Sysmex XN-20 analyzer were found to be imprecise and irreproducible, especially with samples containing a small number of pathologic cells. Adjustments in the Q value threshold may help in the detection of these cells.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Blood Cell Count / instrumentation*
  • Blood Cell Count / statistics & numerical data
  • Humans
  • Lymphocyte Count / instrumentation
  • Lymphocyte Count / statistics & numerical data
  • ROC Curve
  • Regression Analysis
  • Reproducibility of Results
  • Sensitivity and Specificity