Analysis of Luminex-based algorithms to define unacceptable HLA antibodies in CDC-crossmatch negative kidney transplant recipients

AbstractBackgroundHLA-specific antibodies detected by solid phase assays are increasingly used to define unacceptable HLA antigen mismatches (UAM) prior to renal transplantation. The accuracy of this approach is unclear.MethodsDay of transplant sera from 211 CDC-crossmatch-negative patients were retrospectively analyzed for donor-specific anti-HLA antibodies (DSA) using Luminex technology. HLA were defined as UAM if DSA had mean fluorescence intensity above (I) 3000 (patients retransplanted and those with DSA against HLA class I and II) or 5000 (all other patients), (II) 5000 for HLA A, B and DR and 10,000 for HLA DQ or (III) 10,000 (all HLA). We then studied the accuracy of these algorithms to identify patients with antibody-mediated rejection (AMR) and graft loss. UAM were also determined in 256 transplant candidates and virtual panel-reactive antibody (vPRA) levels calculated.ResultsAt transplantation, 67/211 patients had DSA. Of these, 31 (algorithm I), 24 (II) and 17 (III) had UAM. 9 (I and II) and 8 (III) of 11 early AMR episodes and 7 (I), 6 (II) and 5 (III) of 9 graft losses occurred in UAM-positive patients during 4.9 years of follow-up. Algorithms (I) and (II) identified patients with persistently lower GFR even in the absence of overt AMR. 23-33% of waiting list patients had UAM with median vPRA of 69.2-79.1%.ConclusionsAlgorithms (I) and (II) had comparable efficacy but were superior to (III) in identifying at-risk patients at an acceptable false positive rate. However, Luminex-defined UAM significantly restrict the donor pool of affected patients, which might prolong waiting time. Background HLA-specific antibodies detected by solid phase assays are increasingly used to define unacceptable HLA antigen mismatches (UAM) prior to renal transplantation. The accuracy of this approach is unclear. Methods Day of transplant sera from 211 CDC-crossmatch-negative patients were retrospectively analyzed for donor-specific anti-HLA antibodies (DSA) using Luminex technology. HLA were defined as UAM if DSA had mean fluorescence intensity above (I) 3000 (patients retransplanted and those with DSA against HLA class I and II) or 5000 (all other patients), (II) 5000 for HLA A, B and DR and 10,000 for HLA DQ or (III) 10,000 (all HLA). We then studied the accuracy of these algorithms to identify patients with antibody-mediated rejection (AMR) and graft loss. UAM were also determined in 256 transplant candidates and virtual panel-reactive antibody (vPRA) levels calculated. Results At transplantation, 67/211 patients had DSA. Of these, 31 (algorithm I), 24 (II) and 17 (III) had UAM. 9 (I and II) and 8 (III) of 11 early AMR episodes and 7 (I), 6 (II) and 5 (III) of 9 graft losses occurred in UAM-positive patients during 4.9 years of follow-up. Algorithms (I) and (II) identified patients with persistently lower GFR even in the absence of overt AMR. 23-33% of waiting list patients had UAM with median vPRA of 69.2-79.1%. Conclusions Algorithms (I) and (II) had comparable efficacy but were superior to (III) in identifying at-risk patients at an acceptable false positive rate. However, Luminex-defined UAM significantly restrict the donor pool of affected patients, which might prolong waiting time. Corresponding author: Daniel Zecher, MD, Department of Nephrology, Regensburg University Hospital, Franz Josef Strauss-Allee 11, 93042 Regensburg. daniel.zecher@ukr.de Authorship D.Z. designed the study, performed data analysis and wrote the manuscript. C.B. performed Luminex analyses and data interpretation and contributed to the writing of the manuscript. C.S. and AP collected data. KU and ME performed histological analyses of kidney biopsies. T.B., B.J., C.A.B., B.S. and B.B. gave conceptual advice and contributed to the writing of the manuscript. Disclosure The authors declare no conflicts of interest. Funding There was no relevant funding related to this research. Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.

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