Aligning the flow cytometric evaluation with the diagnostic need: an evidence-based approach

J Clin Pathol. 2017 Sep;70(9):740-744. doi: 10.1136/jclinpath-2016-204316. Epub 2017 Feb 9.


Aims: Elimination of non-value added testing without compromising high-quality clinical care is an important mandate for laboratories in a value-based reimbursement system. The goal of this study was to determine the optimal combination of flow cytometric markers for a screening approach that balances efficiency and accuracy.

Methods: An audit over 9 months of flow cytometric testing was performed, including rereview of all dot plots from positive cases.

Results: Of the 807 cases in which leukaemia/lymphoma testing was performed, 23 were non-diagnostic and 189 represented bronchoalveolar lavage specimens. Of the remaining 595 cases, 137 (23%) were positive for an abnormal haematolymphoid population. Review of the positive cases identified minimum requirements for a screening tube as well as analysis strategies to overcome the diagnostic pitfalls noted. It is estimated that 38% fewer antibodies would be used in a screening approach, representing an opportunity for significant cost savings.

Conclusions: We provide a framework for developing an evidence-based screening combination for cost-effective characterisation of haematolymphoid malignancies, promoting adoption of 'just-in-time' testing systems that tailor the evaluation to the diagnostic need.


MeSH terms

  • Biomarkers, Tumor / analysis*
  • Cost Savings
  • Cost-Benefit Analysis
  • Diagnosis, Differential
  • Diagnostic Errors
  • Evidence-Based Medicine*
  • Flow Cytometry* / economics
  • Flow Cytometry* / standards
  • Health Care Costs
  • Humans
  • Immunophenotyping / economics
  • Immunophenotyping / methods*
  • Immunophenotyping / standards
  • Leukemia / metabolism*
  • Leukemia / pathology
  • Lymphoma / metabolism*
  • Lymphoma / pathology
  • Medical Audit
  • Predictive Value of Tests
  • Quality Indicators, Health Care
  • Reproducibility of Results
  • Workflow


  • Biomarkers, Tumor