Abstract Objective Although peripheral blood flow cytometry (PBFC) can aid in the diagnosis of hematolymphoid malignancies, it is often ordered in clinical situations for which it is not useful. We hypothesized that patient clinical data could be used to design an algorithm to guide better test utilization and performance. Methods Patient records for 250 consecutive PBFC orders were reviewed to determine test indication, patient demographics and history, blood count, and leukocyte differential. These variables were analyzed to determine whether they could predict the detection of hematolymphoid malignancy. Using these data, a test ordering algorithm was designed to maximize positive and minimize negative results, which was then validated on an additional set of 250 consecutive cases. Results Peripheral blood flow cytometry was infrequently positive for most indications. The presence of circulating blasts, history of hematolymphoid malignancy, and lymphocytosis or pancytopenia in patients 50 years of age and older are most predictive of positive results. Application of an algorithm incorporating these criteria would substantially reduce PBFC utilization while increasing the fraction of positive cases. Similar results were seen when the algorithm was applied to an independent validation set. Conclusions An evidence-based algorithm for ordering PBFC based on 5 clinical factors can substantially reduce utilization and increase positive results.
Dar et al. (Tue,) studied this question.