Evidence map›Paper›PMID 36710226›Full record

ArticleCytotherapy2023

Optimizing a fully automated and closed system process for red blood cell reduction of human bone marrow products.

Victoria Ann Remley, Ashley Collins, Sarah Underwood, Jianjian Jin, Yoon Kim, Yihua Cai, Michaela Prochazkova, Larry Moses, Karen M Byrne, Ping Jin and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Cytotherapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 1 institution in 1 country.

Victoria Ann RemleyDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Ashley CollinsDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Sarah UnderwoodDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Jianjian JinDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Yoon KimDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Yihua CaiDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Michaela ProchazkovaDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Larry MosesDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Karen M ByrneDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Ping JinDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
David F StroncekDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Steven L HighfillDepartment of Transfusion Medicine, Center for Cellular Engineering, National Institutes of Health Clinical Center, Bethesda, Maryland, USA. Electronic address: steven.highfill@nih.gov.
National Institutes of Health Clinical Center · US

Funding

The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Intramural NIH HHS Z99 CL999999NCATS NIH HHS UL1 TR000445
6 · The paper itself

Abstract

BACKGROUND

aimsHematopoietic stem cell transplantation using bone marrow as the graft source is a common treatment for hematopoietic malignancies and disorders. For allogeneic transplants, processing of bone marrow requires the depletion of ABO-mismatched red blood cells (RBCs) to avoid transfusion reactions. Here the authors tested the use of an automated closed system for depleting RBCs from bone marrow and compared the results to a semi-automated platform that is more commonly used in transplant centers today. The authors found that fully automated processing using the Sepax instrument (Cytiva, Marlborough, MA, USA) resulted in depletion of RBCs and total mononuclear cell recovery that were comparable to that achieved with the COBE 2991 (Terumo BCT, Lakewood, CO, USA) semi-automated process.

methodsThe authors optimized the fully automated and closed Sepax SmartRedux (Cytiva) protocol. Three reduction folds (10×, 12× and 15×) were tested on the Sepax. Each run was compared with the standard processing performed in the authors' center on the COBE 2991. Given that bone marrow is difficult to acquire for these purposes, the authors opted to create a surrogate that is more easily obtainable, which consisted of cryopreserved peripheral blood stem cells that were thawed and mixed with RBCs and supplemented with Plasma-Lyte A (Baxter, Deerfield, IL, USA) and 4% human serum albumin (Baxalta, Westlake Village, CA, USA). This "bone marrow-like" product was split into two starting products of approximately 600 mL, and these were loaded onto the COBE and Sepax for direct comparison testing. Samples were taken from the final products for cell counts and flow cytometry. The authors also tested a 10× Sepax reduction using human bone marrow supplemented with human liquid plasma and RBCs.

resultsRBC reduction increased as the Sepax reduction rate increased, with an average of 86.06% (range of 70.85-96.39%) in the 10×, 98.80% (range of 98.1-99.5%) in the 12× and 98.89% (range of 98.80-98.89%) in the 15×. The reduction rate on the COBE ranged an average of 69.0-93.15%. However, white blood cell (WBC) recovery decreased as the Sepax reduction rate increased, with an average of 47.65% (range of 38.9-62.35%) in the 10×, 14.56% (range of 14.34-14.78%) in the 12× and 27.97% (range of 24.7-31.23%) in the 15×. COBE WBC recovery ranged an average of 53.17-76.12%. Testing a supplemented human bone marrow sample using a 10× Sepax reduction resulted in an average RBC reduction of 84.22% (range of 84.0-84.36%) and WBC recovery of 43.37% (range of 37.48-49.26%). Flow cytometry analysis also showed that 10× Sepax reduction resulted in higher purity and better recovery of CD34+, CD3+ and CD19+ cells compared with 12× and 15× reduction. Therefore, a 10× reduction rate was selected for the Sepax process.

conclusionsThe fully automated and closed SmartRedux program on the Sepax was shown to be effective at reducing RBCs from "bone marrow-like" products and a supplemented bone marrow product using a 10× reduction rate.

Indexed as

Bone MarrowHematopoietic Stem Cell TransplantationBone Marrow TransplantationErythrocytesFlow CytometryHumansbone marrowCD34COBEPBSCsred blood cellsSepaxtransplantation

Identifiers

PMID36710226
PMCPMC10006340
OpenAlexW4318273597

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.