Determination of the relationship between CD34+ stem cell amount and DMSO in hematopoetic stem cell transplantation.

It is important to calculate the CD34+ stem cell (SC) count at the right time in patients with hematological malignancies who will undergo Hematopoietic Stem Cell Transplantation (HSCT). The amount of SC infused into the patient affects the engraftment time and healing process of the patient. In this study, we aimed to compare which of the DMSO-not removed and DMSO-removed samples showed the CD34 + SC amount more accurately as the SC amount determination method after the SC was dissolved after cryopreservation in patients who will undergo HSCT. A total of 22 patients were included in the study. All 22 patients were transplanted from frozen samples using DMSO. After the SC products were dissolved in a 37 °C water bath, they were washed 2 times and the amount of CD34+ SC was studied from the samples taken by removing DMSO and without removing DMSO. In the findings, the amounts of CD34+ SC studied with both methods were compared. The increase in the number and percentage of CD34+ SC after DMSO-removed was found to be statistically significant both in terms of difference and proportionally, and the calculated effect sizes also showed that the increase was clinically significant (Cohen's d is between 0.43 and 0.677). After thawing the frozen SCs of the patients who will undergo HSCT, the analysis of CD34+ SCs from which DMSO is removed provides a more accurate calculation of the CD34+ SC amount in the AP.

Ten Color Multiparameter Flow Cytometry in Bone Marrow and Apheresis Products for Assessment and Outcome Prediction in Multiple Myeloma Patients.

OBJECTIVE: In clinical trials (CTs), the assessment of minimal residual disease (MRD) has proven to have prognostic value for multiple myeloma (MM) patients. Multiparameter flow cytometry (MFC) and next-generation sequencing are currently used in CTs as effective tools for outcome prediction. We have previously described 6- and 8-color MFC panels with and without kappa/lambda, which were equally reliable in detecting aberrant plasma cells (aPC) in myeloma bone marrow (BM) specimens. This follow-up study a) established a highly sensitive single-tube 10-color MFC panel for MRD detection in myeloma samples carrying different disease burden (monoclonal gammopathy of unknown significance (MGUS), smoldering multiple myeloma (SMM), MM), b) evaluated additional, rarely used markers included in this panel, and c) assessed MRD levels and the predictive value in apheresis vs. BM samples of MM patients undergoing autologous stem cell transplantation (ASCT). METHODS + RESULTS: The 10-color MFC was performed in BM and apheresis samples of 128 MM and pre-MM (MGUS/SMM) patients. The markers CD28, CD200, CD19, and CD117 underwent closer examination. The analysis revealed distinct differences in these antigens between MM, MGUS/SMM, and patients under treatment. In apheresis samples, the 10-color panel determined MRD negativity in 44% of patients. Absence of aPC in apheresis corresponded with disease burden, cytogenetics, and response to induction. It also determined MRD negativity in BM samples after ASCT and was associated with improved progression-free survival. CONCLUSION: These results highlight the significance of the evaluation of both BM and apheresis samples with a novel highly sensitive 10-color MFC panel.

Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

BACKGROUND: Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. STUDY DESIGN AND METHODS: This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. RESULTS: Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P < .001). Means of software machine-derived values differed significantly from actual PLT yield, 4.72 × 1011 vs.6.12 × 1011 , respectively, (P < .001). The following equation was developed to adjust these values: actual PLT yield= 0.221 + (1.254 × theoretical platelet yield). ROC curve model showed an optimal apheresis device software prediction cut-off of 4.65 × 1011 to obtain a DP, with a sensitivity of 82.2%, specificity of 93.3%, and an area under the curve (AUC) of 0.909. CONCLUSION: Trima Accel v6.0 software consistently underestimated PLT yields. Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP.