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.
CONCLUSIONS: 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.
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.
CONCLUSIONS: 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.
摘要：
背景：外周血来源的造血干细胞（HSC）广泛用于各种成体干细胞移植。为了在单采过程中从健康的志愿者供体获得足够的HSC，并确保供体接触较少的单采相关副作用，已经开发了用于预测处理的血容量或CD34+计数的计算方法。然而,在预测要处理的血液体积或要获得的干细胞数量的公式上没有达成共识。
目的：本研究旨在使用基于收集效率（CE）的公式估算预测的血容量和CD34+细胞计数，并与实际的CD34+细胞计数相比评估其准确性。它还试图确定影响CE的因素。
方法：来自397个健康，对无关干细胞供者进行回顾性分析.一种使用四个不同CE2度量(第一四分位数，意思是，第三四分位数,和中位数）用于使用SpectraOptia连续单核细胞收集程序预测要处理的血液体积。
结果：采用均值CE2算法时，结果显示预测和实际CD34+值之间有很强的相关性(r=.894，p<.001)。该研究还确定了分离前CD34+之间的强关联，分离术前白细胞计数,使用两种剂量的G-CSF，低CE2。
结论：这些发现表明，平均CE2算法可能是一种有效的，直截了当，和准确的工具，用于预测健康的同种异体干细胞供体中的CD34+干细胞计数，并可能优化干细胞收集程序。
目的：本研究旨在使用基于收集效率（CE）的公式估算预测的血容量和CD34+细胞计数，并与实际的CD34+细胞计数相比评估其准确性。它还试图确定影响CE的因素。
方法：来自397个健康，对无关干细胞供者进行回顾性分析.一种使用四个不同CE2度量(第一四分位数，意思是，第三四分位数,和中位数）用于使用SpectraOptia连续单核细胞收集程序预测要处理的血液体积。
结果：采用均值CE2算法时，结果显示预测和实际CD34+值之间有很强的相关性(r=.894，p<.001)。该研究还确定了分离前CD34+之间的强关联，分离术前白细胞计数,使用两种剂量的G-CSF，低CE2。
结论：这些发现表明，平均CE2算法可能是一种有效的，直截了当，和准确的工具，用于预测健康的同种异体干细胞供体中的CD34+干细胞计数，并可能优化干细胞收集程序。
