MO010TREATMENT STRATEGIES OF ANTIBODY MEDIATED REJECTION IN KIDNEY TRANSPLANTATION: A SYSTEMATIC REVIEW AND META-ANALYSIS
Authors: Buttigieg Jesmar , Kim Jon Jim , Mason Stephen , Camilleri Brian , Halawa Ahmed 
Published: June 2020

Background and Aims

Antibody mediated rejection (AMR) remains accountable for the majority of death-censored graft failure following the first year of kidney transplantation. Despite significant advances in transplant immunology and immunosuppressive agents, long-term graft survival has not improved significantly. The objective of this systematic review and meta-analysis is to determine the optimal treatment strategy for AMR by investigating the effect on kidney function, proteinuria, donor specific antibody (DSA), histopathology, graft survival, adverse events and patient survival.

Method

MEDLINE (PubMed), Scopus, Cochrane Central Register of Controlled Trials and ClinicalTrials.gov databases were systematically searched following the PRISMA guidelines. Any kidney transplant study conducted between 1997-2018, which investigated treatment strategies for biopsy-proven AMR, and reported at least one of the following outcomes; serum creatinine, glomerular filtration rate (GFR), proteinuria, DSA, histopathology scores, graft survival, adverse events and/or patient survival were eligible for inclusion. Risk of bias was evaluated using the Cochrane Risk of Bias Tool for randomised controlled trials (RCTs) and the ROBINS-I tool for non-randomised controlled studies.

Results

Our analysis identified a total of 27 studies consisting of 6 RCTs and 21 non-randomised controlled studies. Together these studies included 1,237 transplant recipients; 748 patients with acute AMR (AAMR) and 489 with chronic AMR (CAMR). Meta-analysis identified significantly better 1-year graft survival in patients with AAMR when treated with Rituximab in addition to plasmapheresis and intravenous immunoglobulin (IVIG) compared to plasmapheresis and IVIG alone [risk ratio (RR): 0.48, 95% confidence interval (CI): 0.27-0.86, Z=2.46, P=0.01, I2=0%] (Fig-1A). Pooled analysis of GFR in the AAMR group was not possible due to insufficient data. There was no significant difference in the GFR at 6-12 months after treatment of CAMR with IVIG plus Rituximab compared to no treatment [mean difference: 0.36, 95% CI: -11.80-12.52, Z=0.06, P=0.95, I2=89%] (Fig-1B). Similarly, there was no significant difference in the 1-year graft survival after treatment of CAMR with IVIG plus Rituximab compared to no treatment [RR: 0.77, 95% CI: 0.42-1.40, Z=0.86, P=0.39, I2=9%] (Fig-1C). Late diagnosis of AMR and established transplant glomerulopathy seem associated with graft dysfunction and poor prognosis. Additionally, declining GFR and proteinuria seem to impact considerably on the overall outcome of the graft. Pooled analysis of proteinuria, DSA titres, and histopathology scores was not possible due to insufficient data. Similarly, pooled analysis of adverse events was not possible; however, these therapeutic strategies were generally well tolerated and associated with excellent patient survival throughout the included studies. Novel therapeutic approaches seem promising, but currently there is insufficient evidence for their routine use in AMR. The risk of bias ranged between low-risk to high-risk throughout the included RCTs and between moderate-risk to critical-risk amongst the non-randomised controlled studies.

Conclusion

This systematic review and meta-analysis outlines the treatment of AMR in kidney transplantation using the current best available evidence. We identified low-quality evidence in favour of treatment with combined plasmapheresis, IVIG and Rituximab in AAMR. Treatment of established CAMR does not seem advantageous in terms of graft function and survival. Additionally, the treatment of AMR is particularly heterogeneous between transplant centres, reflecting the lack of good quality evidence to guide practice. RCTs conducted via multicentre collaboration are urgently required to establish the optimal therapeutic strategies and validate models for predicting therapeutic response in AMR.