A classification tree approach for improving the utilization of flow cytometry testing of blood specimens for B-cell non-Hodgkin lymphoproliferative disorders

Abstract

We sought to improve the diagnostic efficiency of flow cytometry investigation on blood by developing data-driven ordering guidelines. Our goal was to improve flow cytometry utilization by decreasing negative testing, therefore reducing healthcare costs. We investigated several laboratory tests performed alongside flow cytometry to identify biomarkers useful in excluding non-leukemic bloods. Test results and patient demographic features were subjected to receiver-operator characteristic (ROC) curve, logistic regression and classification tree analyses to find significant predictors and develop decision rules. Our data show that, in the absence of a compelling clinical indication, flow cytometry testing is largely non-informative on bloods from patients less than 50 years of age having an absolute lymphocyte count (ALC) below 5.0 × 10⁹/L. For patients over age 50 having an ALC below this value, a ferritin value above 450 μg/L is counter-indicative of B-cell clonality. Using these guidelines, 26% of cases were correctly predicted as negative with greater than 97% accuracy.

Keywords::

• Flow cytometry
• utilization
• classification tree
• chronic lymphocytic leukemia
• monoclonal B-cell lymphocytosis

Acknowledgements

The authors would like to especially thank Jeannine Viczko for her efforts in retrieving patient demographic and laboratory test data for this study. (Ms. Viczko has provided written consent for this acknowledgement.)

Potential conflict of interest

Disclosure forms provided by the authors are available with the full text of this article at www.informahealthcare.com/lal.