Back to Search
Start Over
Prediction of CD34+ hematopoietic stem cells in healthy allogeneic stem cell donors on the Optia cell separator based on CE2: Which formula is more correlated with actual CD34+?
- Source :
-
Transfusion . Oct2024, Vol. 64 Issue 10, p1959-1967. 9p. - Publication Year :
- 2024
-
Abstract
- Background: Peripheral blood‐derived hematopoietic stem cells (HSCs) are widely used for various adult stem cell transplants. To obtain sufficient HSCs from healthy volunteer donors during the apheresis process and ensure that the donors are exposed to fewer apheresis‐related side effects, calculation methods have been developed for the prediction of processed blood volume or CD34+ count. However, there is no consensus on a formula to predict the volume of blood to be processed or the number of stem cells to be obtained. Objective: This study aimed to estimate the predicted blood volume and CD34+ cell counts using collection efficiency (CE)‐based formulas and evaluate their accuracy compared to the actual CD34+ cell counts. It also seeks to identify the factors that affect CE. Methods: Data from 397 healthy, unrelated stem cell donors were retrospectively analyzed. An algorithm using four different CE2 metrics (1st quartile, mean, 3rd quartile, and median) was developed to predict the volume of blood to be processed using the Spectra Optia continuous mononuclear cell collection procedure. Results: When employing the mean CE2 algorithm, the results revealed a strong correlation (r =.894, p <.001) between predicted and actual CD34+ values. The study also identified strong associations between pre‐apheresis CD34+, pre‐apheresis leukocyte count, the use of two doses of G‐CSF, and low CE2. Conclusion: These findings suggest that the mean CE2 algorithm could be a potent, straightforward, and accurate tool for predicting CD34+ stem cell counts in healthy allogeneic stem cell donors and potentially optimizing stem cell collection procedures. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00411132
- Volume :
- 64
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- Transfusion
- Publication Type :
- Academic Journal
- Accession number :
- 180387379
- Full Text :
- https://doi.org/10.1111/trf.17990