BackgroundPeripheral 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.ObjectiveThis 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.MethodsData 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.ResultsWhen 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.ConclusionThese 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.

中文翻译：

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基于CE2在Optia细胞分离器上预测健康同种异体干细胞供体中的CD34+造血干细胞：哪个公式与实际CD34+更相关？


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志愿者捐献者那里获得足够的 HSC，并确保捐献者受到更少的单采相关副作用，已经开发了用于预测处理后的血容量或 CD34+ 计数的计算方法。然而，对于预测要处理的血液量或要获得的干细胞数量的公式尚未达成共识。 目的本研究旨在使用基于收集效率（CE）的公式估计预测的血量和 CD34+ 细胞计数并与实际 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。方法对来自 397 名健康、无关的干细胞捐献者的数据进行了回顾性分析。开发了一种使用四种不同 CE2 指标（第一四分位数、平均值、第三四分位数和中位数）的算法来预测使用 Spectra Optia 连续单核细胞采集程序要处理的血液量。结果当采用平均 CE2 算法时，结果显示强相关性（ r = .894, p < .001) 预测值和实际 CD34+ 值之间。该研究还发现，血浆分离前 CD34+、血浆分离前白细胞计数、使用两剂 G-CSF 和低 CE2 之间存在很强的关联。结论这些发现表明，平均 CE2 算法可能是一种有效、简单且准确的工具用于预测健康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采集程序。