自体造血干细胞移植（ASCT）在淋巴瘤和多发性骨髓瘤（MM）的治疗中获得了广泛的应用。大量研究表明，外周血指标可被视为造血干细胞 (HSC) 收集效率的潜在预测生物标志物，包括白细胞计数 (WBC)、单核细胞计数 (Mono)、血小板计数 (PLT)、血细胞比容和血红蛋白水平。目前临床上缺乏基于这些外周检测指标快速、方便、准确预测采集效率的实用预测模型。 本研究对139例接受ASCT动员采集的MM合并淋巴瘤患者进行回顾性研究。研究终点是成功收集自体 HSC。我们分析了临床特征和外周血标志物对采集成功的影响，并筛选变量建立预测模型。我们确定了预测成功干细胞采集的外周血标记物的最佳截止值以及多标记物预测方法的临床价值。我们还建立了收集效果的预测模型。单变量和多变量逻辑回归分析表明，动员方案、Mono、PLT、单核细胞计数（MNC）和外周血 CD34 细胞计数（PB CD34 计数）是成功收集的显着预测因素外周血干细胞（PBSC）。根据多变量逻辑分析的结果构建了两个预测模型。模型 1 包括动员方案、Mono、PLT 和 MNC，而模型 2 包括动员方案、Mono、PLT、MNC 和 PB CD34 计数。受试者工作特征（ROC）曲线分析表明，PB CD34 计数、模型 1 和模型 2 可以预测 HSC 采集的成功，截止值分别为 26.92 × 106/L、0.548 和 0.355。模型 1 可以预测成功的 HSC 采集，敏感性为 84.62%，特异性为 75.73%，曲线下面积 (AUC) 为 0.863。模型2可以预测HSCs采集成功，敏感性为83.52%，特异性为94.17%，AUC为0.946；因此，它优于单独的 PB CD34 计数。我们的研究结果表明，收集前结合动员方案、Mono、PLT、MNC 和 PB CD34 计数对于 MM 和 MM 患者自体 HSC 收集的效果具有预测价值。淋巴瘤。使用基于这些预测标记的模型可能有助于避免过度收集并改善患者的治疗结果。© 2024 作者。约翰·威利 (John Wiley) 出版的《国际实验室血液学杂志》

Autologous hematopoietic stem cell transplantation (ASCT) has gained extensive application in the treatment of lymphoma and multiple myeloma (MM). Plenty of studies demonstrate that peripheral blood indicators could be considered potential predictive biomarkers for hematopoietic stem cells (HSCs) collection efficiency, including white blood cell count (WBC), monocyte count (Mono), platelet count (PLT), hematocrit, and hemoglobin levels. Currently, clinically practical predictive models based on these peripheral detection indicators to quickly, conveniently, and accurately predict collection efficiency are lacking.In total, 139 patients with MM and lymphoma undergoing mobilization and collection of ASCT were retrospectively studied. The study endpoint was successful collection of autologous HSCs. We analyzed the effects of clinical characteristics and peripheral blood markers on collection success, and screened variables to establish a prediction model. We determined the optimal cutoff value of peripheral blood markers for predicting successful stem cell collection and the clinical value of a multi-marker prediction approach. We also established a prediction model for collection efficacy.Univariate and multivariate logistic regression analyses showed that the mobilization regimen, Mono, PLT, mononuclear cell count (MNC), and peripheral blood CD34+ cell count (PB CD34+ counts) were significant predictors of successful collection of peripheral blood stem cells (PBSC). Two predictive models were constructed based on the results of multivariate logistic analyses. Model 1 included the mobilization regimen, Mono, PLT, and MNC, whereas Model 2 included the mobilization regimen, Mono, PLT, MNC, and PB CD34+ counts. Receiver operating characteristic (ROC) curve analysis showed that the PB CD34+ counts, Model 1, and Model 2 could predict successful HSCs collection, with cutoff values of 26.92 × 106/L, 0.548, and 0.355, respectively. Model 1 could predict successful HSCs collection with a sensitivity of 84.62%, specificity of 75.73%, and area under the curve (AUC) of 0.863. Model 2 could predict successful HSCs collection with a sensitivity of 83.52%, specificity of 94.17%, and AUC of 0.946; thus, it was superior to the PB CD34+ counts alone.Our findings suggest that the combination of the mobilization regimen, Mono, PLT, MNC, and PB CD34+ counts before collection has predictive value for the efficacy of autologous HSCs collection in patients with MM and lymphoma. Using models based on these predictive markers may help to avoid over-collection and improve patient outcomes.© 2024 The Author(s). International Journal of Laboratory Hematology published by John Wiley & Sons Ltd.