Analysis of Luminex-based Algorithms to Define Unacceptable HLA Antibodies in CDC-crossmatch Negative Kidney Transplant Recipients.

Abstract:

BACKGROUND:HLA-specific antibodies detected by solid phase assays are increasingly used to define unacceptable HLA antigen mismatches (UAM) before renal transplantation. The accuracy of this approach is unclear. METHODS:Day of transplant sera from 211 complement-dependent cytotoxicity 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 vPRA levels calculated. RESULTS:At transplantation, 67 of 211 patients had DSA. Of these, 31 (algorithm I), 24 (II) and 17 (III) had UAM. Nine (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 glomerular filtration rate even in the absence of overt AMR. Of the waiting list patients, 22-33% had UAM with median virtual panel reactive antibody of 69.2% to 79.1%. CONCLUSIONS:Algorithms I and II had comparable efficacy but were superior to Algorithm 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.

journal_name

Transplantation

journal_title

Transplantation

authors

Zecher D,Bach C,Preiss A,Staudner C,Utpatel K,Evert M,Jung B,Bergler T,Böger CA,Spriewald BM,Banas B

doi

10.1097/TP.0000000000002129

subject

Has Abstract

pub_date

2018-06-01 00:00:00

pages

969-977

issue

6

eissn

0041-1337

issn

1534-6080

journal_volume

102

pub_type

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