Extensive red blood cell matching considering patient alloimmunization risk

Author:

Wemelsfelder Merel L.12ORCID,van de Weem Ronald H. G.1ORCID,Luken Jessie S.34ORCID,de Haas Masja345ORCID,Niessen René W. L. M.6,van der Schoot C. Ellen4ORCID,Hoogeveen Han7ORCID,Oyebolu Folarin B.8ORCID,den Hertog Dick2ORCID,Janssen Mart P.1ORCID

Affiliation:

1. Donor Medicine Research Department Sanquin Research Amsterdam the Netherlands

2. Business Analytics Department University of Amsterdam Amsterdam the Netherlands

3. Department of Immunohematology Diagnostics Sanquin Diagnostic Services Amsterdam the Netherlands

4. Department of Experimental Immunohematology Sanquin Research Amsterdam the Netherlands

5. Department of Hematology Leiden University Medical Center Leiden the Netherlands

6. OLVG Laboratory BV Amsterdam the Netherlands

7. Department of Information and Computing Sciences Utrecht University Utrecht the Netherlands

8. MRC Biostatistics Unit University of Cambridge Cambridge UK

Abstract

AbstractBackground and ObjectivesRed blood cell (RBC) transfusions pose a risk of alloantibody development in patients. For patients with increased alloimmunization risk, extended preventive matching is advised, encompassing not only the ABO‐D blood groups but also the most clinically relevant minor antigens: C, c, E, e, K, Fya, Fyb, Jka, Jkb, S and s. This study incorporates patient‐specific data and the clinical consequences of mismatching into the allocation process.Materials and MethodsWe have redefined the MINimize Relative Alloimmunization Risks (MINRAR) model to include patient group preferences in selecting RBC units from a finite supply. A linear optimization approach was employed, considering both antigen immunogenicity and the clinical impact of mismatches for specific patient groups. We also explore the advantages of informing the blood bank about scheduled transfusions, allowing for a more strategic blood distribution. The model is evaluated using historical data from two Dutch hospitals, measuring shortages and minor antigen mismatches.ResultsThe updated model, emphasizing patient group‐specific considerations, achieves a similar number of mismatches as the original, yet shifts mismatches among patient groups and antigens, reducing expected alloimmunization consequences. Simultaneous matching for multiple hospitals at the distribution centre level, considering scheduled demands, led to a 30% decrease in mismatches and a 92% reduction in shortages.ConclusionThe reduction of expected alloimmunization consequences by incorporating patient group preferences demonstrates our strategy's effectiveness for patient health. Substantial reductions in mismatches and shortages with multi‐hospital collaboration highlights the importance of sharing information in the blood supply chain.

Funder

Stichting Sanquin Bloedvoorziening

NIHR Cambridge Biomedical Research Centre

Publisher

Wiley

Reference22 articles.

1. Stichting Sanquin Bloedvoorziening.Stichting Sanquin Bloedvoorziening Jaarverslag 2021. [cited 23 Aug 2023]. Available from:https://www.sanquin.nl/binaries/content/assets/sanquinnl/over‐sanquin/pers‐‐actueel/jaarverslagen/stichting‐sanquinbloedvoorziening_jaarverslag‐2021.pdf

2. International Society of Blood Transfusion Working Party on Red Cell Immunogenetics and Blood Group Terminology.Classifications in Blood Group Terminology: Systems Collections 700 Series and 901 Series. [cited 23 Aug 2023]. Available from:https://www.isbtweb.org/isbt-working-parties/rcibgt/blood-group-terminology.html

3. Federatie Medisch Specialisten.Bloedtransfusiebeleid. [cited 23 Aug 2023]. Available from:https://richtlijnendatabase.nl/richtlijn/bloedtransfusiebeleid/

4. HLA and RBC immunization after filtered and buffy coat-depleted blood transfusion in cardiac surgery: a randomized controlled trial

5. Incidence of alloantibody formation after ABO-D or extended matched red blood cell transfusions: a randomized trial (MATCH study)

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