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Updated: Apr 17, 2026
Flow Cytometric Characterization of Murine B Cell Development
Published on: January 22, 2021
A classification tree approach for improving the utilization of flow cytometry testing of blood specimens for B-cell
Ryan Healey1, Christopher Naugler1,2, Lawrence de Koning1
1a Department of Pathology and Laboratory Medicine , University of Calgary , Calgary, Alberta , Canada.
Insights
New guidelines improve flow cytometry diagnostic efficiency by identifying non-leukemic bloods. Data-driven rules decrease unnecessary testing, reducing healthcare costs and improving test utilization.
Area of Science:
- Hematology
- Clinical Pathology
- Laboratory Medicine
Background:
- Flow cytometry is a crucial diagnostic tool for hematologic malignancies.
- Current utilization patterns may lead to non-informative testing and increased healthcare expenditure.
- Development of evidence-based guidelines can optimize test ordering and resource allocation.
Purpose of the Study:
- To develop data-driven guidelines for flow cytometry testing on blood samples.
- To enhance diagnostic efficiency and reduce the rate of negative or non-informative tests.
- To decrease healthcare costs associated with unnecessary flow cytometry investigations.
Main Methods:
- Analysis of laboratory test results and patient demographics.
- Application of receiver-operator characteristic (ROC) curve analysis, logistic regression, and classification trees.
- Identification of significant predictors and development of decision rules for test ordering.
Main Results:
- Flow cytometry is largely non-informative in patients under 50 years with an absolute lymphocyte count (ALC) below 5.0 × 10(9)/L, absent specific clinical indications.
- In patients over 50 with ALC < 5.0 × 10(9)/L, a ferritin level > 450 μg/L indicates a low probability of B-cell clonality.
- The developed guidelines accurately predicted 26% of negative cases with >97% accuracy.
Conclusions:
- Data-driven guidelines can significantly improve the diagnostic utility of flow cytometry.
- Specific patient demographics and laboratory markers (ALC, ferritin) can effectively guide flow cytometry test ordering.
- Implementation of these guidelines can lead to more efficient healthcare resource utilization in hematologic diagnostics.
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 × 10(9)/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.
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