Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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%). CONCLUSIONS: 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.