Preventing alloimmunization using a new model for matching extensively typed red blood cells.

Background And Objectives: Alloimmunization is a well-known adverse event associated with red blood cell (RBC) transfusions, caused by phenotype incompatibilities between donor and patient RBCs that may lead to haemolytic transfusion reactions on subsequent transfusions. Alloimmunization can be prevented by transfusing fully matched RBC units. Advances in RBC genotyping render the extensive typing of both donors and patients affordable in the foreseeable future. However, the exponential increase in the variety of extensively typed RBCs asks for a software-driven selection to determine the 'best product for a given patient'.

Materials And Methods: We propose the MINimize Relative Alloimmunization Risks (MINRAR) model for matching extensively typed RBC units to extensively typed patients to minimize the risk of alloimmunization. The key idea behind this model is to use antigen immunogenicity to represent the clinical implication of a mismatch. Using simulations of non-elective transfusions in Caucasian donor and patient populations, the effect on the alloimmunization rate of the MINRAR model is compared with that of a baseline model that matches antigens A, B and RhD only.

Results: Our simulations show that with the MINRAR model, even for small inventories, the expected number of alloimmunizations can be reduced by 78.3% compared with a policy of only matching on antigens A, B and RhD. Furthermore, a reduction of 93.7% can be achieved when blood is issued from larger inventories.

Conclusion: Despite an exponential increase in phenotype variety, matching of extensively typed RBCs can be effectively implemented using our MINRAR model, effectuating a substantial reduction in alloimmunization risk without introducing additional outdating or shortages.