Background: Most transplantation centers recognize a small patient population that unsuccessfully participates in all available, both living and deceased donor, transplantation programs for many years: the difficult-to-match patients. This population consists of highly immunized and/or ABO blood group O or B patients.
Methods: To improve their chances, Computerized Integration of Alternative Transplantation programs (CIAT) were developed to integrate kidney paired donation, altruistic/unspecified donation, and ABO and HLA desensitization. To compare CIAT with reality, a simulation was performed, including all patients, donors, and pairs who participated in our programs in 2015-2016. Criteria for inclusion as difficult-to-match, selected-highly immunized (sHI) patient were as follows: virtual panel reactive antibody >85% and participating for 2 years in Eurotransplant Acceptable Mismatch program. sHI patients were given priority, and ABO blood group incompatible (ABOi) and/or HLA incompatible (HLAi) matching with donor-specific antigen-mean fluorescence intensity (MFI) <8000 were allowed. For long-waiting blood group O or B patients, ABOi matches were allowed.
Results: In reality, 90 alternative program transplantations were carried out: 73 compatible, 16 ABOi, and 1 both ABOi and HLAi combination. Simulation with CIAT resulted in 95 hypothetical transplantations: 83 compatible (including 1 sHI) and 5 ABOi combinations. Eight sHI patients were matched: 1 compatible, 6 HLAi with donor-specific antigen-MFI <8000 (1 also ABOi), and 1 ABOi match. Six/eight combinations for sHI patients were complement-dependent cytotoxicity cross-match negative.
Conclusions: CIAT led to 8 times more matches for difficult-to-match sHI patients. This offers them better chances because of a more favorable MFI profile against the new donor. Besides, more ABO compatible matches were found for ABOi couples, while total number of transplantations was not hampered. Prioritizing difficult-to-match patients improves their chances without affecting the chances of regular patients.
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