Daniele Mazzocchetti, Amy Maria Berti, Roberta Sartini, Alessandra Lucarini, Giuseppe Ragusa, Matteo Caroli, and Luca Pierelli, “Total nucleated cells as a sole predictor of distinct targets of hematopoietic potential (CD34+ cells) in cord blood units: the results of a large series analysis in autologous cord blood units.” Transfusion, 54(5):1256-1262
Rapid identification of eligible cord blood units (CBUs) for banking is an important number in hematopoietic stem cell procurement. Distinct contents of CD34+ cells in CBU can contribute to identify grafts that may be banked also for unrelated transplants or limited to family-directed or autologous use.
Considering thresholds of CD34+ cell content of $3 × 10^6$, $2 × 10^6$, and $1 × 10^6$ CD34+ cells, we analyzed a consecutive series of 1309 CBUs. CBUs were collected for autologous banking without any volume-based preselection criteria. Predictors of distinct content of CD34+ cells have been assessed by receiver operating characteristic (ROC) curve analysis.
Median total nucleated cell (TNC) and CD34+ cell counts of the series were $6.97 × 10^8$ (range, $0.36 × 10^8-34.9 × 10^8$) and $1.47 × 10^6$ $(0-20.56 × 10^6)$. Volumes ranged from 21 to 163 mL, with a median of 73.8 mL. For the CD34+ target of $1 × 10^6$, the best predictor was TNC count with a threshold of $6.63 × 10^8$; volume results were less predictive with a value of 68.1 mL. For CD34+ targets of $2 × 10^6$ and $3 × 10^6$, ROC curves confirmed a stronger predictive power of TNC, above the collected volume, with thresholds of $7.55 × 10^8$ and $8.98 × 10^8$. ROC analysis by combining all predictors (TNC, volume, TNC2, volume2, age of mothers, types of delivery, birthweight) gave worse results than TNC count alone.
This analysis, carried out on a large, unrestricted CBU series, shows that TNC alone is the best predictor of distinct targets of hematopoietic potential with the chance to predict CBU potentially useful for unrelated recipients or limited for family-directed or autologous use.
Giuseppe Ragusa teaches in the Department of Economics and Business and in the Business School at Luiss University. His research is mostly about econometrics.
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