Establishing disease-specific thresholds for automated hematopoietic progenitor cell counting in hematological...

Flow cytometry remains the gold-standard method for enumerating CD34 + cells during peripheral blood stem cell (PBSC) transplantation, but it is resource- and time-intensive. This study aimed to assess the correlation between hematopoietic progenitor cell (HPC) counts measured by a Sysmex XN-series analyzer and CD34 + cell counts obtained by flow cytometry in pre-apheresis peripheral blood and apheresis products, and to establish HPC cutoffs for predicting adequate PBSC yields.

We analyzed 334 samples (167 pre-apheresis peripheral blood, 167 PBSC apheresis products) collected from patients and healthy donors. HPC and CD34 + cell counts were measured in all samples. Receiver operating characteristic (ROC) curve analysis was performed to determine HPC cutoff values predictive of adequate PBSC harvest.

Intraclass correlation coefficients (ICCs) indicated strong HPC‒CD34 + concordance in pre-apheresis peripheral blood (ICC = 0.896, p < 0.001) and apheresis products (ICC = 0.958, p < 0.001). Median HPC counts were significantly higher than CD34 + cell counts overall (16 vs. 14.6/µL, p < 0.001; 1,040 vs. 804.73/µL, p < 0.001). The same trend was observed in multiple myeloma (50 vs. 23.92/µL, p < 0.001; 1,290 vs. 1,132.85/µL, p = 0.002) and lymphoma (7 vs. 2.48/µL, p = 0.011; 615 vs. 475.12/µL, p = 0.004). In healthy donors, median HPC counts in apheresis products also exceeded CD34 + cell counts (1,580 vs. 1,430.45/µL, p = 0.005). The HPC cutoffs predicting peripheral blood CD34+ > 20/µL and a CD34 + cell yield of ≥ 2 × 106 cells/kg were 21/µL overall (sensitivity 91.5%, specificity 90.6%), 27/µL for multiple myeloma (87.2%, 81.3%), and 20/µL for lymphoma (83.3%, 95.2%).

This study establishes the first disease-specific HPC cutoff values targeting the clinically critical 2 × 106 cells/kg threshold: 27 cells/μL for multiple myeloma and 20 cells/μL for lymphoma. This precision medicine approach advances beyond universal cutoffs, enabling optimized collection timing and potentially reducing healthcare costs.