Evaluation of new automated hematopoietic progenitor cell analysis in the clinical management of peripheral blood stem cell collections

Apheresis product total CD34+ cell count prediction at peripheral stem cell collection via a formula: A multicenter study

INTRODUCTION

Effective mobilization of Stem Cells(SCs) to peripheral blood (PB) is crucial for obtaining sufficient CD34+ cell numbers via apheresis. The ratio of pre-apheresis PB CD34+ cells is the best parameter for predicting the product CD34+ cell count. However, quantitating CD34+ PB cells requires flow cytometry, which usually takes two or more hours to obtain the results. We hypothesized that the product CD34+ cell count could be predicted using the counts of white blood cells (WBCs), mononuclear cells (MNCs), and pre-apheresis CD34+ cells. A formula that achieves this would substantially affect the efficiency and effectiveness of apheresis. We, therefore, aimed to estimate the number of CD34+ cells in the product using a formula that incorporates pre-apheresis PB WBC, MNC, and CD34+ cell counts and product WBC and MNC counts.

METHODS

We examined the results of 373 leukapheresis procedures for SC mobilization. Effective separation of CD34+ PBSCs (count/μL) via apheresis was estimated using the following formula: [Product WBC (count/μL) × MNC (count/μL) × pre-apheresis CD34+ cell (percentage/μL)] ÷ [PB WBC count/μL × PB MNC (count/μL)].

RESULTS

A strong correlation was observed between the CD34+ cell count calculated using our formula and the post-apheresis CD34+ cell count measured via flow cytometry (R = 0.939, based on linear regression analysis). In the subgroup analysis, this correlation was observed for all the disease subgroups and healthy donors.

CONCLUSION

We developed a formula that predicts the product CD34+ cell count and is useful for determining whether a second apheresis procedure will be required.

Sysmex XN-HPC: study of reference intervals and clinical decision limits in healthy allogeneic donors mobilised with G-CSF

The Sysmex XN series haematopoietic progenitor cell (XN-HPC) is a novel tool for assessing stem cell yield before allogeneic haematopoietic stem cell transplantation. This study aimed to establish a reference interval (RI) for XN-HPC in peripheral blood allogeneic transplant donors following granulocyte colony-stimulating factor (G-CSF) stimulation and determine its clinical significance. All specimens were analysed using Sysmex XN-20. Samples were collected and analysed using non-parametric percentile methods to define the RIs. Quantile regression was used to explore the dependency of the RIs on sex and age. Samples were included in clinical decision limits for apheresis based on receiver operating characteristic curve analysis. The non-parametrically estimated RI for XN-HPC was 623.50 (90% confidence interval [CI90%] 510.00-657.00) to 4,144.28 (CI90% 3,761.00-4,547.00). The RIs for the XN-HPC were not age-dependent but were sex-dependent. The RI for males was 648.40 (CI90% 582.00-709.00)-4,502.60 (CI90% 4,046.00-5,219.00) and for females was 490.90 (CI90% 311.00-652.00)-3,096.90 (CI90% 2,749.00-3,782.00). Comparisons based on XN-HPC values between the poor and less-than-optimal groups, good and less-than-optimal groups, and good and non-good groups had areas under the curve of 0.794 (P < 0.001), 0.768 (P < 0.001), and 0.806 (P < 0.001), respectively, indicating a good predictive value for mobilisation effectiveness. XN-HPC data exceeding 3974 × 106/L suggested that a sufficient number of stem cells could be collected clinically. Values > 5318 < 106/L indicated 100% mobilisation effectiveness. We established an RI for XN-HPC in peripheral blood allogeneic transplant donors following G-CSF stimulation and determined clinical decision thresholds for mobilisation efficiency.

Prediction of Viable CD34 Count in Harvested Product by Peripheral Blood Hematopoietic Progenitor Count of Automated Hematology Analyzer Undergoing Hematopoietic Stem Cell Transplantation

Introduction

The CD34+ hematopoietic cell count was used to define cell harvest goals. Successful peripheral blood stem cell transplantation depends on infusion of an appropriate number of HPCs to achieve rapid and durable hematologic recovery.

Purpose

In this study, we evaluated the use of the Hematopoietic Progenitor Cell count program on the Sysmex XN-3000 hematology analyzer as an effective parameter for enumerating CD34+ cells.

Patients and Methods

Whole blood samples from 144 subjects who are either healthy donors or patients scheduled to undergo peripheral blood stem cell collection were collected and hemopoietic stem cells were quantified using CD34 cell enumeration by flow cytometry and XN-HPC by hematology analyzer.

Results

The correlation between the two methods was high (r = 0.766; 95% CI: 0.702-0.818). Passing-Bablok showed an intercept at 3.45 (2.54 to 4.74) with a slope of 0.78 (95% CI 0.69 to 0.89). Residual analysis of this model indicated no significant deviation from linearity (p = 0.360). The receiver operating characteristic curve demonstrated an area under curve to be 0.88 (0.82 to 0.92), with a positive predictive value of 80.3%. The correlation between CD34+ and XN-HPC showed a strong relationship and good agreement with minimal bias.

Conclusion

The XN-HPC showed good analytical performance. With the increasing requirements for stem cell transplantation, a technically simple and rapid alternative for stem cell enumeration that is sustainable is highly useful.

Hematopoietic progenitor cell count as a potential quantitative marker in apheresis products during allogeneic stem cell transplantation

BACKGROUND

The quality and quantity of hematopoietic stem cells in apheresis products are essential to the success of peripheral blood hematopoietic stem cell transplantation (PB-HSCT). While the flow cytometry measurement of CD34+ cells as a golden standard for stem cell count is labor and cost-intensive, hematopoietic progenitor cell number evaluated by XN Sysmex series automated hematology analyzers (XN-HPC) is suggested as a surrogate marker.

MATERIALS AND METHODS

We evaluated the correlation and consistency of XN-HPC and CD34+ cell count in apheresis samples from both allogeneic donors and autologous patients during PB-HSCT.

RESULTS

Good correlation and consistency were observed between XN-HPC and CD34+ cell counts in harvests collected from healthy donors (R = .852) rather than autologous patients (R = .375). Subgroup analysis showed that the correlation was especially poor when autologous patients used plerixafor as an additional mobilizer or were diagnosed with multiple myeloma (MM). In the setting of allogeneic transplantation, the correlation coefficients were even better in samples from non-first-round apheresis (R = .951), with high white blood cell (WBC) counts (R = .941), or having successful engraftment within 2 weeks (R = .895). ROC analysis suggested that an optimal XN-HPC count of 1127 × 106 /L best predicted a sufficient yield of CD34+ stem cells, with diagnostic sensitivity and specificity being 92% and 72%, respectively (AUC = 0.852).

CONCLUSIONS

XN-HPC is a sufficient quantitative marker for stem cell assessment of harvest yield in allogeneic but not autologous HSCT.

Hematopoietic Progenitor Cell Counts of the Leukapheresis Product Determined Using Sysmex XN Analyzers Predict a Sufficient Number of CD34+ Stem Cells in a Peripheral Blood Stem Cell Harvest for Autologous Transplantation

Objective Several institutions outsource CD34+ cell counting of leukapheresis products, limiting rapid measurements, as results are obtained the next day. This problem is compounded with plerixafor use, a stem cell-mobilizing drug that increases leukapheresis efficiency but requires administration the day before leukapheresis. Use of this drug for a second leukapheresis procedure before the first-day leukapheresis CD34+ count results are confirmed causes unnecessary leukapheresis and expensive plerixafor administration. We investigated whether or not measuring hematopoietic progenitor cells in leukapheresis products (AP-HPCs) using a Sysmex XN-series analyzer could resolve this problem. Methods We retrospectively compared the absolute AP-HPC value per body weight with the CD34+ (AP-CD34+) count in 96 first-day leukapheresis product samples obtained between September 2013 and January 2021. Comparisons were also conducted according to regimen: granulocyte colony-stimulating factor (G-CSF) monotherapy, chemotherapy plus G-CSF, or plerixafor mobilization. Results AP-CD34+ and AP-HPC counts correlated strongly (rs=0.846) overall and, in particular, under chemotherapy plus G-CSF (rs=0.92) but correlated mildly under G-CSF monotherapy (rs=0.655). AP-HPCs could not completely be dichotomized based on an AP-CD34+ threshold of 2×106/kg for any stimulation procedure. In most cases with AP-HPCs >6×106/kg, the AP-CD34+ count exceeded 2.0×106/kg, but in 5.7% of these cases, the AP-CD34+ count was <2.0×106/kg. A cut-off of AP-HPCs >4.843×106/kg yielded a sensitivity of 71% and specificity of 96% for predicting AP-CD34+≥2×106/kg. Conclusion AP-HPCs can identify cases in which sufficient stem cells have been collected.

Flow Cytometric Characterization of Hematopoietic Stem and Progenitor Cell Subpopulations in Autologous Peripheral Blood Stem Cell Preparations after Cryopreservation

Introduction

Autologous stem cell transplantation is a successful routine procedure with only a small number of non-engraftment cases, although the time to hematopoietic recovery may vary considerably across patients. While CD34 has been the decisive marker for enumerating hematopoietic stem and progenitor cells (HSPCs) for more than 30 years, the impact of CD34-positive cellular subpopulations in autologous HSPC grafts on hematopoietic reconstitution remains unclear.

Methods

The two-color ISHAGE protocol represents the current gold standard for CD34+ cell enumeration but includes only the number of viable CD45+/CD34+ cells relative to the body weight of the recipient. We adapted a multicolor flow cytometry marker panel for advanced characterization of CD34 subpopulations in retained samples of autologous peripheral blood stem cell products (n = 49), which had been cryostored for a wide range from 4 to 15 years. The flow cytometric analysis included CD10, CD34, CD38, CD45, CD45RA, CD133, and viability staining with 7AAD. The findings were correlated with clinical engraftment data, including reconstitution of leukocytes, neutrophils, and platelets after transplantation (TPL).

Results

We demonstrated that the identification of autologous HSPC subpopulations by flow cytometry after cryopreservation is feasible. Regarding the distribution of HSPC subpopulations, a markedly different pattern was observed in comparison to previously published data obtained using fresh autologous material. Our data revealed the largest ratio of lympho-myeloid progenitors (LMPPs) after freezing and thawing, followed by multipotent progenitors and erythroid-myeloid progenitors. A high ratio of LMPPs, representing an immature stage of differentiation, correlated significantly with early neutrophilic granulocyte and leukocyte engraftment (p = 0.025 and p = 0.003). Conversely, a large ratio of differentiated cells correlated with late engraftment of neutrophilic granulocytes (p = 0.024). Overall, successful engraftment was documented for all patients.

Conclusion

We established an advanced flow cytometry panel to assess the differentiation ability of cryostored autologous peripheral blood stem cell grafts and correlated it with timely hematopoietic reconstitution. This approach represents a novel and comprehensive way to identify hematopoietic stem and progenitor subpopulations. It is a feasible way to indicate the engraftment capacity of stem cell products.

Correlation of various methods of hematopoietic progenitor cell estimation with standard flowcytometric CD34 enumeration

BACKGROUND AND OBJECTIVES

Enumeration of hematopoietic progenitor cell (HPC) is vital to decide the time to initiate harvest (TTIH) and adequacy of harvest dose (AOHD). Standard of care used for HPC enumeration is flowcytometric CD34+ enumeration, but it is expensive, time-consuming and requires skilled staff to perform the test. Alternatively, HPC-count by advanced automated cell analyzer is cheaper, quicker, and easy-to-perform test. Our objective was to find a correlation of HPC count with CD34+ enumeration in leukapheresis.

MATERIALS AND METHODS

An observational, prospective study was conducted in the year 2018-2019. A total of 126 samples were included in the study, the peripheral blood (PB) group comprised of 42samples and apheresis group of 84 samples. The samples were simultaneously tested for CD34+ expression and complete blood count which included the HPC count, white blood cells (WBC) count and multinational corporation (MNC) count and correlation analysis was performed with CD34+ flowcytometric count. The cut-off of PB HPC count for the target dose of 5 × 106 CD34+ cells/kg was established using Receiver Operator Curve.

RESULTS

The correlation coefficient (r) of HPC with CD34+ count was 0.617 and 0.699 for PB group and apheresis group sample respectively, which was statistically significant. The correlation with MNC and WBC count was not very significant. A cut-off value of PB HPC was established to be 66 HPC/μl with a positive predictive value of 94.12%. The cost of CD34 + flow cytometric enumeration was six times that of HPC enumeration by analyzer.

CONCLUSION

The HPC count is a cheaper, rapid and easy test and can be clinically applied to predict TTIH and AOHD but requires more studies to validate its efficacy in clinical use.

High D-index during mobilization predicts poor mobilization of CD34+ cells after anti-lymphoma salvage chemotherapy

BACKGROUND

Performing stem cell collection after mobilization chemotherapy was a well-balanced strategy between anti-tumor effect and efficient collection of CD34+ cells, but deep and prolonged nadir exposed patients to risk of febrile neutropenia. Febrile neutropenia was known to be associated with lower yields of CD34+ cells, but quantitative data referring to association between yields of CD34+ cells and severity of neutropenia was lacking. We hypothesized that D-index, which was developed for quantitative evaluation of severity of neutropenia especially in the field of hematologic malignancies, could predict yields of CD34+ cells.

METHODS

We performed a single center, retrospective analysis of patients with relapsed or refractory aggressive lymphoma who were mobilized with ESHAP or modified ESHAP. We evaluated the association between yields of CD34+ cells at first apheresis and D-index.

RESULTS

Thirty-six patients were included, and we demonstrated that yields of CD34+ cells from patients with higher D-index were significantly lower than those from patients with lower D-index. Multivariate linear regression analysis and logistic regression analysis also demonstrated the significant predictive power of D-index. Further, D-index was significantly correlated to platelet count before starting mobilization chemotherapy. Platelet count was known to predict yields of CD34+ cells, and combination of platelet count and D-index could identify patients with lowest CD34+ yields.

CONCLUSION

D-index could predict yields of CD34+ cells and it seemed that its predictive power was not less than that of platelet count. Prospective studies including more heterogeneous patients were needed to validate our study.

Hematopoietic progenitor cell counting can optimize peripheral blood stem cell apheresis process

INTRODUCTION

Monitoring of stem cell concentration in transplantation settings is crucial to determine the optimal time of apheresis and is currently based on enumeration of CD34+ cells by flow cytometry. No surrogate marker has replaced CD34+ cell enumeration to date. The aim of this study was the evaluation of the hematopoietic progenitor cell (HPC) parameter of the Sysmex XN-1000 analyzer in terms of optimizing the peripheral blood stem cell apheresis process.

MATERIALS AND METHODS

Results of flow cytometric CD34+ cell and Sysmex HPC count were compared in 208 preharvest samples and 139 apheresis products.

RESULTS

HPC and CD34+ cell counts showed significant differences in the multiple myeloma (MM) group. The correlation between preharvest HPC and CD34+ cell counts was good in the MM group (rho = .613) and strong in the lymphoma group (rho = .802), allogeneic donors (rho = .923), and other group of samples (rho = .816). The HPC positive cutoff demonstrating 100% specificity and positive predictive value for MM patients was high for ≥20/μL and ≥10/μL CD34+ cell counts, and therefore of limited value. The HPC negative cutoff demonstrating 100% sensitivity and negative predictive value was approximately <4/μL, irrespective of diagnosis.

CONCLUSIONS

Based on proposed HPC positive cutoffs (≥31/μL in the lymphoma group and ≥11/μL in the other group of samples), routine HPC enumeration could improve the workflow by replacing CD34+ cell counting in allogeneic donors as well as non-MM patients. Furthermore, based on proposed HPC negative cutoff (<4/μL), CD34+ cell counting could be fully omitted in donors and patients that are not adequately mobilized.

Measurement of hematopoietic progenitor cells using XN2000 hematology analyzer

INTRODUCTION

Stem cell enumeration by the hematopoietic progenitor cells (HPC) mode is a novel method available from Sysmex XN2000 hematology analyzer. A small amount of blood (190 μL) is required, and the results are available in a few minutes without manual gating or presample treatment. The present study compares stem cell measurements using XN2000 analyzer HPC mode and FC500 flow cytometry analyzer using peripheral blood (PB) specimens and apheresis products.

METHODS

In this prospective study, CD34-positive cell counts were enumerated using an FC500 flow cytometry analyzer and compared with XN2000 Sysmex analyzer (XN-HPC mode) in the same samples. Results were compared using Bland-Altman plots.

RESULTS

A total of 103 samples were used. In the PB samples, the median HPC count and CD34-positive cells were 83.5 × 10⁶ /L and 78.0 × 10⁶ /L, respectively. The mean Bland-Altman difference was 4.5 × 10⁶ /L (Limits: -51.7 to 60.7 × 10⁶ /L), with a Pearson's correlation of 0.79. In the apheresis products, the median HPC count and CD34-positive cells were 1468 × 10⁶ /L (IQR: 1049 - 1960 × 10⁶ /L) and 1327 × 10⁶ /L (IQR: 910 - 2001 × 10⁶ /L), respectively. The mean Bland-Altman difference was 179.0 × 10⁶ /L (Limits: -2022.2 - 2380.2 × 10⁶ /L), with a Pearson's correlation of 0.58.

CONCLUSION

The XN-HPC mode has an excellent correlation and minimal disagreement for stem cell enumeration in PB compared with flow cytometry and could replace it. There is high disagreement in apheresis products, and therefore, the XN-HPC mode cannot be recommended.

Correlation between peripheral blood automated hematopoietic progenitor cell counts and flow cytometric CD34+ cell counts differs according to diagnosis in patients undergoing autologous peripheral blood stem cell transplantation

BACKGROUND

An automated hematopoietic progenitor cell count measurement in Sysmex XN analyzer (XN-HPC) has been developed to assist flow cytometry CD34⁺ cell count measurement, which requires technical expertise and a long turnaround time. Here, we evaluated the correlation between XN-HPC count and flow cytometric CD34⁺ cell count in pre-harvest peripheral blood (PB) samples from patients undergoing autologous peripheral blood stem cell (PBSC) transplantation according to diagnosis and investigated the possible cause of the decreased correlation in plasma cell neoplasm patients.

MATERIALS AND METHODS

We retrospectively included 399 patient data that had matched PB XN-HPC count and CD34⁺ cell count of PB and apheresis product from Samsung Medical Center (SMC) and the Hematopoietic Stem Cell (HSC) registry. We assessed the diagnostic accuracy and the potential cutoff values of XN-HPC count for predicting adequate PBSC collection.

RESULTS

The PB XN-HPC count was 1.6 and 1.3-fold higher than the CD34⁺ cell count in SMC (25.0 vs 15.9/μl) and the HSC registry (20.0 vs 15.2/μl), respectively. Overall the correlation between the PB XN-HPC and CD34⁺ cell count was moderate (SMC, r = 0.71; HSC registry, r = 0.66). A significant proportional and systemic bias with overestimation of XN-HPC count were noted in the plasma cell neoplasm patients in both SMC and the HSC registry. However, no significant difference in correlation was observed according to myeloma-related laboratory parameters in plasma cell neoplasm patients.

CONCLUSION

Our results suggest that XN-HPC count should be interpreted cautiously in cancer patients undergoing autologous PBSC transplantation, especially in those with plasma cell neoplasm.

A study to compare Hematopoietic Progenitor Cell count determined on a next-generation automated cell counter with flow cytometric CD34 count in peripheral blood and the harvested peripheral blood stem cell graft from autologous and allogenic donors

INTRODUCTION

A successful bone marrow transplant requires a minimum of 2-4 × 10⁶ cells/kg patient body weight of CD 34+ cells to be transfused, where peripheral blood CD34+ cell count being and ideal predictor. We compared the correlation and predictive capacity of both hematopoietic progenitor cell count (HPC) determined on the Sysmex XN-9000 and flow cytometric CD34 in autologous and allogenic donors.

METHODS

Autologous and allogenic donors were taken as per criteria. TLC (Total Leukocyte Count), MNC (Mononuclear cell count), HPC, and CD34 assay were done in both the peripheral blood prior to apheresis, and the harvest product postapheresis. Sysmex XN-9000 was used for TLC, MNC, and HPC tests, and a modified ISH-AGE protocol was used to enumerate CD34 by flow cytometry. Statistical analysis was done using SPSS 16.0.

RESULTS

Sixty-seven allogenic and 35 autologous donors were enrolled. 45% were females, and 55% were males. Correlation between HPC and CD34 was found to be 0.887 with P value < .01 in peripheral blood and 0.847 with P value < .01 in the harvested product. On the other hand, TLC had a correlation of 0.424 and 0.520 in peripheral blood and harvested, respectively. MNC had a weak association. The cutoff value for a target dose of 2 × 10⁶ CD34 cells/kg was 37 × 10⁶ /L for pre-HPC. For a target of 4 × 10⁶ CD34 cells/kg, the cutoff value calculated to be 54 × 10⁶ /L (Sensitivity: 85%, Specificity: 89%) for peripheral blood HPC.

CONCLUSION

We conclude that HPC is comparable to CD34 in predicting harvest product's adequacy.

Peripheral Blood Stem Cell Harvest HPC Count Is an Effective Surrogate Marker for CD34+ Cell Count in Allogeneic Stem Cell Transplant Setting

OBJECTIVE: We assessed the predictive potential of XN-HPC for CD34+ cell count as obtained through Sysmex automated hematology analyzers (XN-1000). METHODS: This study was conducted at the National Institute of Blood Diseases and Bone Marrow Transplantation in 84 donors between December 2012 and December 2017 in the first phase and later validated in 112 donors between December 2017 and December 2018. Sysmex XN-1000 and BD FACS Calibur estimated XN-HPC and CD34+ cells of peripheral blood apheresis product, respectively. Spearman's correlation was assessed between XN-HPC and CD34+ cell count followed by receiver operating characteristic curve calculation to determine the XN-HPC cutoff for a CD34+ count of ≥2 million cells/kg of recipient's body weight RESULTS: There is a moderately positive correlation (P value = .003) between XN-HPC and CD34+ count. Receiver operating characteristic curve analyses demonstrated that a cutoff value for XN-HPC of ≥1·845×10⁶cells/kg of recipient's body weight has a specificity and sensitivity of 100% and 78·2%, respectively, for predicting the CD34+ count of ≥2 million cells/kg of recipient's body weight. This cutoff value of XN-HPC was prospectively validated in 112 donors. The positive predictive value was found to be 100%, while negative predictive value was 17%. CONCLUSION: XN-HPC has a highly promising potential to serve as a cost-effective and time-saving surrogate for CD34+ cell count.

Assessment of haematopoietic progenitor cell counting with the Sysmex® XN-1000 to guide timing of apheresis of peripheral blood stem cells

BACKGROUND

Successful peripheral blood stem cell (PBSC) collection depends on optimal timing of apheresis, as usually determined by flow cytometry CD34-positive (⁺) cell count in peripheral blood (PB). Since this method is costly and labour-intensive, we evaluated the use of the Hematopoietic Progenitor Cell count programme on a Sysmex^® XN haematologic analyser (XN-HPC) as a rapid and inexpensive alternative for predicting CD34⁺ cell count in PB samples.

MATERIALS AND METHODS

Haematopoietic progenitor cell and CD34⁺ cell counts were compared using 273 PB samples collected from 78 healthy donors and 72 patients who underwent PBSC transplantation. We assessed the effectiveness of the XN-HPC in safely predicting pre-harvest CD34⁺ counts. The most efficient cut-off values of XNHPC were identified. We also evaluated the imprecision (coefficient of variation, CV) and functional sensitivity.

RESULTS

Imprecision of the XN-HPC count was <6.3% on daily measurement of three levels of quality control material. Functional sensitivity was 8.9×10⁶/L. A cut-off value of ≥62×10⁶/L XN-HPC for multiple myeloma (MM) patients and ≥30×10⁶/L for all other subjects had both 100% specificity and 100% positive predictive value for identifying samples with CD34⁺ cells ≥20×10⁶/L. An XN-HPC threshold of <13×10⁶/L identified preharvest CD34⁺ cell count <10×10⁶/L with 100% sensitivity and 100% negative predictive value.

DISCUSSION

The XN-HPC is a fast, easy and inexpensive test that can safely improve apheresis workflow thus possibly replacing other more expensive CD34 counts currently performed and promoting optimal timing of PBSC collection.

Evaluation of peripheral blood mononuclear cell collection by leukapheresis

BACKGROUND

Adoptive immunotherapy using engineered lymphocytes has shown promising results in treating cancers even in patients who have failed other treatments. As the first essential step, the number of peripheral mononuclear cell (MNC) collection procedures is rapidly increasing. In this retrospective study, we reviewed the collection results to determine factors that affect MNC collection.

STUDY DESIGN AND METHODS

We reviewed 184 collections that were performed on 169 adult allogenic donors and patients with acute lymphoid leukemia, chronic lymphoid leukemia, lymphoma, multiple myeloma, or solid-organ tumors. All the leukapheresis procedures were performed after a complete cell count with differential was obtained. Total blood volume (TBV) was defined as processed blood volume divided by patient blood volume.

RESULTS

There was a significant association between the precollection MNC count (pre-MNC) and the MNC yields normalized by TBV (r = 0.926; p < 0.001) and a regression formula was created to predict MNC yields. Multiple regression analyses showed that pre-MNC, TBV, and precollection hemoglobin were strongly associated with MNC yield (R ² = 0.866; F (3180) = 388.472; p < 0.001), and pre-MNC had the greatest influence on MNC yield (β = 0.960; p < 0.001) followed by TBV (β = 0.302; p < 0.001), and Hgb (β = 0.136; p < 0.001).

CONCLUSION

Our results suggest that the optimal time for MNC collection can be determined based on pre-MNC and that processing volume should be determined based on collection goal and pre-MNC to optimize and personalize the harvesting procedure.

Exercise-Mobilized Platelet-Rich Plasma: Short-Term Exercise Increases Stem Cell and Platelet Concentrations in Platelet-Rich Plasma

PURPOSE

To evaluate the effects of vigorous short-term exercise on the platelet and other cellular components of 2 point-of-care blood-processing devices: a buffy coat-based platelet-rich plasma (PRP) product and a plasma-based PRP product.

METHODS

Twenty healthy subjects (aged 21-45 years) participated in a 20-minute vigorous exercise regimen on an upright stationary bike at 70% to 85% of maximum target heart rate. Pre- and post-exercise blood was processed in either a plasma-based or automated buffy coat-based PRP system. Complete blood counts were used to compare the cellular components in whole blood and the PRP products.

RESULTS

Exercise significantly increased the concentrations of platelets by over 20% in whole blood (P < .001) and in both PRP products (P = .002 and P = .018). Both devices performed consistently with pre- and post-exercise blood. Buffy coat-based PRP prepared after exercise was also significantly larger in volume and had a significantly higher concentration of mobilized hematopoietic stem cells (hematopoietic progenitor cells [HPCs], from 1.7/μL to 2.7/μL, P = .043). The concentrations of all white blood cell types were increased, which could be differentially collected in the devices studied.

CONCLUSIONS

Exercise can be used to consistently alter the composition of PRP. Twenty minutes of vigorous exercise can increase platelet concentrations in plasma-based and buffy coat-based PRP products and can increase HPC concentrations and volume in buffy coat-based PRP.

CLINICAL RELEVANCE

This study shows a nonpharmacologic method to increase platelet and HPC harvests from peripheral blood. This is important because it highlights a method for altering biological therapies with limited comorbidity.

Rapid prediction of stem cell mobilization using volume and conductivity data from automated hematology analyzers

BACKGROUND

Rapid analytics to predict circulating hematopoietic stem cells are valuable for optimal management of mobilization, particularly for the use of newer and costly mobilization agents such as plerixafor.

STUDY DESIGN AND METHODS

We used stepwise, linear multiple regression modeling applied to cell population data collected by routine hematology analyzers (Beckman Coulter DxH 800) on patients undergoing autologous stem cell collection (n = 131). Beta coefficients were used to derive a formula for a stem cell index (SCI). We then tested the correlation of SCI with stem cell counts and performance of the SCI as a predictor of poor mobilization with external validation in a separate cohort (n = 183).

RESULTS

The SCI correlated strongly with CD34 counts by flow cytometry (r = 0.8372 in the development cohort, r = 0.8332 in the external validation cohort) and compares favorably with other rapid stem cell enumerating technologies. In the external validation cohort, the SCI performed well as a predictor (receiver operating characteristic area under the curve, 0.9336) of poor mobilization (CD34 count < 10), with a sensitivity of 72% and a specificity of 93%. When prevalence of poor mobilization was 33%, this resulted in a positive predictive value of 83% and a negative predictive value of 87%. The SCI also showed promise in tracking responses to plerixafor administration.

CONCLUSION

The findings demonstrate the utility of the cell population data collected by hematology analyzers to provide rapid data beyond standard complete blood counts, particularly for stem cell count prediction, requiring no additional reagents, specimen, or instrumentation.

Novel Automated Hematology Parameters in Clinical Pediatric Practice

Blood sampling in children is a challenging task, and to extract maximum possible information from these 'precious' samples, the modern-day automated hematology analyzers have been aided with much technological advancement. Various novel blood cell parameters are now available to narrow down the differential diagnoses. However, only few of these are available for routine clinical reporting. Knowledge about their interpretation and reference ranges can prove useful in challenging situations.

Algorithms utilizing peripheral blood hematopoietic progenitor cell counts in lieu of some CD34+ cell counts predict successful peripheral blood stem cell collections with substantial time and cost savings

Background and Objectives

Hematopoietic progenitor cell (HPC) counts from Sysmex hematology analyzers have been shown to correlate with peripheral blood (PB) CD34+ cell counts by flow cytometry. Algorithms utilizing HPC counts to guide stem cell collections have been proposed but rarely tested. This study describes the development and validation of algorithms utilizing HPC and PB CD34+cell counts to predict adequate peripheral blood stem cell (PBSC) collections for chemomobilized and cytokine-mobilized individuals.

Materials and Methods

Utilizing a test set of 83 PB samples from chemomobilized or cytokine-mobilized PBSC collection patients, PB CD34+ counts were correlated with HPC counts and a receiver operating characteristic curve was constructed. Cut-offs of ≤0.5 HPC/μl and ≥7 HPC/μl were established to maximize sensitivity and specificity for using HPC to predict PB CD34+ ≥ 10 cells/μl. These cut-offs were subsequently validated using a separate prospective validation set of 88 HPC/CD34+ cell sample pairs.

Results

Using the algorithms, all patients in the prospective validation data set achieved adequate collections of ≥1 × 10⁶ CD34⁺ cells/kg, and a 67% reduction in the number of CD34⁺ cell counts performed was achieved. This lead to a direct cost savings of at least $18,700 USD over a 21-month period (88% reduction in direct costs).

Conclusion

Use of the algorithms provides significant time and cost savings for the laboratory while accurately predicting (i) timing of PBSC collections to obtain adequate CD34⁺ product yields for chemomobilized patients and (ii) when to administer plerixafor to cytokine-mobilized patients to improve the likelihood of achieving adequate collections.