The Banff 97 working classification refines earlier schemas and represents input from two classifications most widely used in clinical rejection trials and in clinical practice worldwide. Major changes include the following: rejection with vasculitis is separated from tubulointerstitial rejection; severe rejection requires transmural changes in arteries; "borderline" rejection can only be interpreted in a clinical context; antibody-mediated rejection is further defined, and lesion scoring focuses on most severely involved structures. Criteria for specimen adequacy have also been modified. Banff 97 represents a significant refinement of allograft assessment, developed via international consensus discussions.

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Evidence of antibody-mediated injury (DSA or C4d) is common (57%) in patients with new onset late kidney allograft dysfunction. The risk of subsequent graft failure is significantly worse in the presence of C4d+ staining.

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De novo donor‐specific antibody (dnDSA) develops in 15–25% of renal transplant recipients within 5 years of transplantation and is associated with 40% lower graft survival at 10 years. HLA epitope matching is a novel strategy that may minimize dnDSA development. HLAMatchmaker software was used to characterize epitope mismatches at 395 potential HLA‐DR/DQ/DP conformational epitopes for 286 donor–recipient pairs. Epitope specificities were assigned using single antigen HLA bead analysis and correlated with known monoclonal alloantibody epitope targets. Locus‐specific epitope mismatches were more numerous in patients who developed HLA‐DR dnDSA alone (21.4 vs. 13.2, p < 0.02) or HLA‐DQ dnDSA alone (27.5 vs. 17.3, p < 0.001). An optimal threshold for epitope mismatches (10 for HLA‐DR, 17 for HLA‐DQ) was defined that was associated with minimal development of Class II dnDSA. Applying these thresholds, zero and 2.7% of patients developed dnDSA against HLA‐DR and HLA‐DQ, respectively, after a median of 6.9 years. Epitope specificity analysis revealed that 3 HLA‐DR and 3 HLA‐DQ epitopes were independent multivariate predictors of Class II dnDSA. HLA‐DR and DQ epitope matching outperforms traditional low‐resolution antigen‐based matching and has the potential to minimize the risk of de novo Class II DSA development, thereby improving long‐term graft outcome.

Despite more than two decades of use, the optimal maintenance dose of tacrolimus for kidney transplant recipients is unknown. We hypothesized that HLA class II donor-specific antibody (DSA) development correlates with tacrolimus trough levels and the recipient's individualized alloimmune risk determined by HLA-DR/DQ epitope mismatch. A cohort of 596 renal transplant recipients with 50,011 serial tacrolimus trough levels had HLA-DR/DQ eplet mismatch determined using HLAMatchmaker software. We analyzed the frequency of tacrolimus trough levels below a series of thresholds <6 ng/ml and the mean tacrolimus levels before DSA development in the context of HLA-DR/DQ eplet mismatch. HLA-DR/DQ eplet mismatch was a significant multivariate predictor ofDSA development. Recipients treated with a cyclosporin regimen had a 2.7-fold higher incidence of DSA development than recipients on a tacrolimus regimen. Recipients treated with tacrolimus who developed HLA-DR/DQDSA had a higher proportion of tacrolimus trough levels <5 ng/ml, which continued to be significant after adjustment for HLA-DR/DQ eplet mismatch. Mean tacrolimus trough levels in the 6 months before DSA development were significantly lower than the levels>6 months before DSA development in the same patients. Recipients with a high-risk HLA eplet mismatch score were less likely to tolerate low tacrolimus levels without developingDSA. We conclude that HLA-DR/DQ eplet mismatch and tacrolimus trough levels are independent predictors of DSA development. Recipients with high HLA alloimmune risk should not target tacrolimus levels<5 ng/ml unless essential, and monitoring for DSA may be advisable in this setting.

SELDI-TOF-MS offers a unique platform for high throughput urine protein profiling; however, standardization of analysis conditions is critical, and both extrinsic and intrinsic factors must be taken into account for accurate data interpretation.