Peripheral blood stem cell yield calculated using preapheresis absolute CD34+ cell count, peripheral blood volume processed, and donor body weight accurately predicts actual yield at multiple centers

CD34+ cell yield among healthy donors: Large-scale model development and validation

BACKGROUND

Successful engraftment in hematopoietic stem cell transplantation necessitates the collection of an adequate dose of CD34+ cells. Thus, the precise estimation of CD34+ cells harvested via apheresis is critical. Current CD34+ cell yield prediction models have limited reproducibility. This study aims to develop a more reliable and universally applicable model by utilizing a large dataset, enhancing yield predictions, optimizing the collection process, and improving clinical outcomes.

MATERIALS AND METHODS

A secondary analysis was conducted using the Center for International Blood and Marrow Transplant Research database, involving data from over 17 000 healthy donors who underwent filgrastim-mobilized hematopoietic progenitor cell apheresis. Linear regression, gradient boosting regressor, and logistic regression classification models were employed to predict CD34+ cell yield.

RESULTS

Key predictors identified include pre-apheresis CD34+ cell count, weight, age, sex, and blood volume processed. The linear regression model achieved a coefficient of determination (R2) value of 0.66 and a correlation coefficient (r) of 0.81. The gradient boosting regressor model demonstrated marginally improved results with an R2 value of 0.67 and an r value of 0.82. The logistic regression classification model achieved a predictive accuracy of 96% at the 200 × 106 CD34+ cell count threshold. At thresholds of 400, 600, 800, and 1000 × 106 CD34+ cell count, the accuracies were 88%, 83%, 83%, and 88%, respectively. The model demonstrated a high area under the receiver operator curve scores ranging from 0.90 to 0.93.

CONCLUSION

This study introduces advanced predictive models for estimating CD34+ cell yield, with the logistic regression classification model demonstrating remarkable accuracy and practical utility.

Predicting the CD34 content of mobilized peripheral blood leukapheresis products: single institution experience over 20 years

BACKGROUND AIMS

Since the standardization of CD34 measurement by flow cytometry, predictors of leukapheresis CD34 yield have played a pivotal role in planning donor leukaphereses. We describe here a single institution's experience with a multivariate predictor that was used for 2,929 products without alteration for 20 years.

METHODS

The ordinary least squares regression model variables included log peripheral CD34 count, collection duration (3- versus 4-hours), collection number, donor sex, and transplant type.

RESULTS

During the study period we changed flow cytometers twice and leukapheresis instruments once. During the Cobe Spectra era the predictor explained 90% of the variability in CD34 collection yield for autologous transplants (r2 = 0.90), and 70% for allogeneic transplants with an overall sensitivity to predict a CD34 yield of ≥ 1 × 106/kg of 97.7%, and specificity of 81.4%.

CONCLUSIONS

Implemented prospectively with real-time result reporting, the model allowed us to predict CD34 yield with both 3- and 4-hour collection scenarios. Given this guidance, 3-hour collections were selected by the clinical team 25% of the time, saving patient leukapheresis time and resources. When faced with a prediction of < 1 × 106 CD34/kg, the clinical team chose to defer collection 72% of the time. In instances where leukapheresis was performed despite a poor predicted outcome, 85% of patients collected on the Cobe Spectra, and 92% of patients collected on the Optia, failed to collect at least 1 × 106 CD34/kg. A revised model is tested retrospectively on Optia data, and suggestions for further improvements are discussed.

Primed for change: The effect of a blood prime on peripheral blood stem cell collection and accuracy of a prediction tool in pediatric patients

Pediatric apheresis collection of peripheral blood stem cells for autologous transplantation often requires use of a blood prime. We evaluated the relationship between pre-apheresis blood CD34+ counts and final CD34+ yield with use of a blood prime. Forty patients underwent apheresis stem cell collection in a 5 year period in our hospital, of which 27 required blood priming of the apheresis machine. Despite the blood prime group having significantly higher pre-apheresis CD34+ cell counts, this group processed a relatively higher volume of blood due to a higher dilutional effect and collected significantly less than predicted CD34+ cell yield. Use of weight-specific collection efficiencies and dilution-adjusted pre-apheresis CD34+ counts will help in accurately estimating the whole blood volume to process for PBSC collection and therefore increase efficiency and decrease the overall cost of collection.

Peripheral Blood Allogeneic Stem Cell Mobilization: Can We Predict a Suboptimal Mobilization?

Allogeneic peripheral blood stem cells mobilization is now the basis of most stem cell transplants. In a very limited number of cases, mobilization is suboptimal leading to further collection procedures, to suboptimal cell doses infusion with delayed engraftment time, increased risks of transplant procedure and of related costs. To date we have no recognized and shared criteria for early estimating the probability of poor mobilization in healthy donors. We then analyzed allogeneic peripheral blood stem cell donations performed at the Fondazione Policlinico Universitario A.Gemelli IRCCS Hospital from January 2013 to December 2021 in order to identify premobilization factors associated with successful mobilization. The following data were collected: age, gender, weight, complete blood cell count at baseline, G-CSF dose, number of collection procedures, CD34+ cell count in peripheral blood on the first day of collection, CD34+ cell dose per kg body weight of recipient. Mobilization efficacy was defined according to the number of CD34+ cells in peripheral blood on day +5 of G-CSF administration. We classified donors as sub-optimal mobilizers or good mobilizers according to the achievement of the 50 CD34+ cell/μL threshold. We observed 30 suboptimal mobilizations in 158 allogeneic peripheral blood stem cell donations. Age and baseline white blood cell count were factors significantly associated with negative or positive impact on mobilization, respectively. We did not find significant differences in mobilization based on gender or G-CSF dose. Using cut-off values of 43 years and 5.5×10⁹/L WBC count, we built a suboptimal mobilization score: donors who reach 2, 1 or 0 points have a 46%, 16% or 4% probability of suboptimal mobilization, respectively. Our model explains 26% of the variability of mobilization confirming that most of the mobilization magnitude depends on genetically determined factors; however, suboptimal mobilization score is a simple tool providing an early assessment of mobilization efficacy before G-CSF administration begins in order to support allogeneic stem cells selection, mobilization and collection. Through a systematic review, we looked for confirmation of our findings. According to the published articles, all the variables we included in our model are confirmed to be strongly related to the success of mobilization. We believe that score system approach could be applied in clinical practice to assess the risk of mobilization failure at baseline allowing for a priori intervention.

Impact of Mobilization Strategies on Peripheral Blood Stem Cell Collection Efficiency and Product Quality: A Retrospective Single-Center Study

Autologous stem cell transplantation is routinely used in the management of several hematological diseases, solid tumors, and immune disorders. Peripheral blood stem cell (PBSC) collection performed by apheresis is the preferred source of stem cells. In this study, the potential impact of mobilization regimens on the performance of the Spectra Optia^® continuous mononuclear cell collection system was evaluated. We performed a retrospective data analysis for patients undergoing autologous PBSC collection at the Medical University Vienna, Vienna General Hospital between September 2016 and June 2018. Collections were divided into two main groups according to the mobilization regimen received: without (210 collections) or with (99 collections) plerixafor. Assessed variables included product characteristics and collection efficiency (CE). Overall, product characteristics were similar between the groups. Median CD34+ CE2 was 50.1% versus 53.0%, and CE1 was 66.9% versus 69.9% following mobilization without and with plerixafor, respectively; the difference was not statistically significant. Simple linear regression showed a very weak positive correlation between the mobilization method and CE1 or CE2 (mobilization with plerixafor increased CE2 by 4.106%). In conclusion, the Spectra Optia^® apheresis system led to high CE and a good quality of PBSC products when mobilization regimens with or without plerixafor were used.

Low hematocrit reduces the efficiency of CD34+ cell collection when using the Spectra Optia continuous mononuclear cell collection procedure

BACKGROUND

CD34⁺ cell collection efficiency (CE) is the determining factor when calculating processed blood volume (PBV) for leukapheresis (LP). However, the factors affecting CE in the continuous mononuclear cell collection (cMNC) protocol performed by the Spectra Optia apheresis system are not well established.

STUDY DESIGN AND METHODS

We retrospectively collected the data from 147 consecutive apheresis procedures across 106 healthy donors and 27 patients completed between July 2016 and December 2020 at the Okayama University Hospital. All procedures were performed using the Optia cMNC protocol.

RESULTS

The median CD34⁺ CE2 was significantly higher in the donor samples (64.3%) than in the patient samples (46.8%) (p < .0001). WBC counts, hematocrit, and platelet counts were all significantly higher in the donors than in the patients, and there was a moderate positive correlation between CD34⁺ CE2 and hematocrit (r = .47, p < .0001), with the equation of the line being y = 1.23x + 12.23. In contrast, there was only a very weak correlation between CD34⁺ CE2 and WBC or platelet count. In addition, low hematocrit correlated with an increased time to interface formation.

CONCLUSION

These data revealed the negative impact of low hematocrit on the efficiency of CD34⁺ cell collection when using the Optia cMNC protocol and suggest that hematocrit values should also be considered when determining PBV.

NF-κB p50-deficient immature myeloid cell (p50-IMC) adoptive transfer slows the growth of murine prostate and pancreatic ductal carcinoma

Background

Macrophages and dendritic cells lacking the transcription factor nuclear factor kappa B p50 are skewed toward a proinflammatory phenotype, with increased cytokine expression and enhanced T cell activation; additionally, murine melanoma, fibrosarcoma, colon carcinoma, and glioblastoma grow slower in p50^−/− mice. We therefore evaluated the efficacy of p50-negative immature myeloid cells (p50-IMCs) adoptively transferred into tumor-bearing hosts. Immature cells were used to maximize tumor localization, and pretreatment with 5-fluorouracil (5FU) was examined due to its potential to impair marrow production of myeloid cells, to target tumor myeloid cells and to release tumor neoantigens.

Methods

Wild-type (WT)-IMC or p50-IMC were generated by culturing lineage-negative marrow cells from WT or p50^−/− mice in media containing thrombopoietin, stem cell factor and Flt3 ligand for 6 days followed by monocyte colony-stimulating factor for 1 day on ultralow attachment plates. Mice inoculated with Hi-Myc prostate cancer (PCa) cells or K-Ras^G12D pancreatic ductal carcinoma (PDC)-luciferase cells received 5FU followed 5 days later by three doses of 10⁷ immature myeloid cells (IMC) every 3–4 days.

Results

PCa cells grew slower in p50^−/− mice, and absence of host p50 prolonged the survival of mice inoculated orthotopically with PDC cells. IMC from Cytomegalovirus (CMV)-luciferase mice localized to tumor, nodes, spleen, marrow, and lung. 5FU followed by p50-IMC slowed PCa and PDC tumor growth, ~3-fold on average, in contrast to 5FU followed by WT-IMC, 5FU alone or p50-IMC alone. Slowed tumor growth was evident for 93% of PCa but only 53% of PDC tumors; we therefore focused on PCa for additional IMC analyses. In PCa, p50-IMC matured into F4/80⁺ macrophages, as well as CD11b⁺F4/80⁻CD11c⁺ conventional dendritic cells (cDCs). In both tumor and draining lymph nodes, p50-IMC generated more macrophages and cDCs than WT-IMC. Activated tumor CD8⁺ T cells were increased fivefold by p50-IMC compared with WT-IMC, and antibody-mediated CD8⁺ T cell depletion obviated slower tumor growth induced by 5FU followed by p50-IMC.

Conclusions

5FU followed by p50-IMC slows the growth of murine prostate and pancreatic carcinoma and depends on CD8⁺ T cell activation. Deletion of p50 in patient-derived marrow CD34⁺ cells and subsequent production of IMC for adoptive transfer may contribute to the therapy of these and additional cancers.

A simplified CD34+ based preharvest prediction tool for HPC(A) collection

BACKGROUND

Hematopoietic stem cell transplantation is an important treatment that is dependent on the collection of sufficient CD34+ hematopoietic progenitor cells. The peripheral blood CD34 count (PB CD34+ counts) measured by flow cytometry can be used in predicting CD34+ stem cell yields hours before the completion of collection. Previously described formulas to predict the yield have used many different variables. As such, there is currently no consensus on an industry-standard algorithm or formula.

STUDY DESIGN AND METHODS

Retrospective reviews of same-day PB CD34+ counts and the ensuing absolute CD34+ yields of mobilized donors (allogeneic and autologous) were used to develop and validate a formula using regression analysis to predict the CD34+ stem cell yield. A metric of prediction correlation, using root mean square error (RMSE), was used to assess the robustness of our prediction formula in addition to comparisons with two other published formulas, as well as subset analysis.

RESULTS

A formula in the form of y = mx^b with r = 0.95 and 95% confidence intervals was generated and validated. The ratio of actual to predicted yield demonstrated a high correlation coefficient (r = 0.96) with linear regression and overall RMSE of 228.4, which was lower than the two prior studies (calculated RMSE = 330.8 and 405.2). Subset analyses indicated male patients, lymphoma patients, and patients >60 years of age demonstrated lower RMSEs.

CONCLUSION

We have demonstrated a simple yet robust formula that can be used prospectively to accurately predict the CD34+ stem cell yield in both autologous and allogeneic donors, which also accounts for recipient weight.

Transfusion Medicine Equations Made Internet Accessible

Multiple mathematical equations inform the practice of transfusion medicine. These equations apply to a wide range of topics: dosage of blood products, calculation of fluid volumes, and even specific treatment decisions (e.g. corrected count increment for determination of platelet refractoriness). The calculation of these equations can be complicated, prone to error, and time-consuming. A trusted source is needed to accurately perform these calculations 24 hours a day without error and without monetary cost. We sought to build internet-enabled calculators relevant to the practice of transfusion medicine. We partnered with MDCalc, an online host of medical calculators with 1 million monthly users in 196 countries, to design and host the calculators. The calculators guide users in the application of transfusion medicine equations by providing indications for use, inputs for the equations variables, error-checking, warnings for bad inputs, and interpretive guidance of the result. The following calculators were built: blood volume, corrected count increment (CCI), plasma dosage, cryoprecipitated antihemophilic factor dosage, approximate number of units for compatibility testing, maternal-fetal hemorrhage Rh(D) immune globulin dosage, intrauterine RBC transfusion dosage, neonatal polycythemia partial exchange, theoretical removal of a substance by plasmapheresis, sickle cell RBC exchange volume, peripheral blood stem cell collection, and a calculator relevant to donor lymphocyte infusion. Clinicians can now utilize this reputable and highly visible online source to access these common transfusion medicine equations at any time with an internet-enabled device (https://www.mdcalc.com/search?filter=transfusion+medicine).

Validation of a formula predictive of peripheral blood stem cell yield and successful collection in healthy allogeneic donors

BACKGROUND

An efficient mobilization and collection of peripheral blood stem cells (PBSCs) are crucial to optimize engraftment in the recipient. We aim to validate a formula that predicted CD34⁺ cell yield and to describe variables that correlated with high yield mobilization and collection in healthy donors.

METHODS

We retrospectively analyzed clinical and laboratory data from healthy donors who underwent PBSC collection from 2006 to 2015. The predicted number of collected cells was calculated using the following formula: Total number of CD34⁺ (cells×10⁶/kg) yield=[(peripheral CD34⁺ cells/μL)×(0.43)/recipient body weight (kg)]×total liters processed.

RESULTS

We evaluated 338 collections from 307 allogeneic PBSC donors. The predicted versus the observed number of CD34⁺ cells/kg collected yielded an r-value of 0.775 (0.726-0.816; p<0.0001). Overall, 55.7% donors had an acceptable mobilization level. Donors with a body weight <67kg were less likely to yield a satisfactory CD34⁺ cell count (OR=0.44; 95% CI 0.24-0.81), while a white blood cell (WBC) count >40×10⁹/L (OR=3.69; 2.11-6.46) and platelet count ≥200×10⁹/L (OR=2.09; 1.26-3.47) on the day of collection predicted a good level of mobilization. Predictors of a CD34⁺ cell yield/kg of ≥4×10⁶ with only one apheresis session were: circulating CD34⁺ cells/μL >40 (OR=16; 6.94-36.93), hemoglobin ≥14g/dL (OR=3.40; 1.53-7.57), WBC >40×10⁹/L (OR=4.61; 2.10-10.10) on the first collection day, and a positive delta weight between donor and recipient (OR=3.10; 1.36-7.06).

CONCLUSION

The formula for predicting CD34⁺ cell yield is accurate and suggests the optimal length of time for successful leukapheresis. Validation of the predictors of successful mobilization will help to further refine PBSC leukapheresis procedures.

Collection and immunoselection of CD34+ cells: the impact of age, sex, and diabetes in patients with chronic heart failure

BACKGROUND

Mobilized peripheral blood is the most common source of CD34+ cells intended for transplantations. The collection and enrichment of CD34+ cells could be affected by various factors and there are some controversies regarding the effects of patient-related factors. The aim of this study was to assess the impact of age, sex, and diabetes on the CD34+ cell grafts in patients with chronic heart failure.

STUDY DESIGN AND METHODS

Cell grafts from 100 adult patients scheduled for autologous CD34+ cell transplantation were investigated. The CD34+ cells were collected using leukapheresis after granulocyte-colony-stimulating factor mobilization and further enriched using the immunomagnetic CD34+ selection. The number of CD34+ cells and their viability were determined by flow cytometry.

RESULTS

Older patients had significantly lower CD34+ cell counts than younger patients. The differences between men and women were not found. There was a trend toward an inverse relationship between diabetes and the CD34+ cell count, however, without any significance. No differences in the CD34+ cell viability (97.6% before and 97.9% after selection) were found. The mean CD34+ cell recovery was 59.7% and was not statistically different between age groups, sex, and diabetic patients.

CONCLUSION

Before the CD34+ cells are collected the patient's age should be considered. The study did not demonstrate a significant impact of sex and diabetes on the CD34+ cell count. While age and sex did not affect the immunoselection process, diabetes slightly reduced cell recovery. Cell viabilities before and after the cell enrichment were comparable between the tested samples.