The ability to predict outcomes for individual patients would be a significant advance for not only counseling, but also identifying those for whom interventions may be needed. The goals of this study were to validate an existing risk prediction score that incorporates easily obtainable clinical factors and determine if histologic findings at 1-year surveillance biopsy and/or serum donor-specific alloantibody status could improve predictability of graft loss by 5 years. We retrospectively studied 1465 adults who received a solitary kidney transplant between January of 1999 and December of 2008 and had sufficiently detailed 5-year follow-up data for modeling. In this cohort, the Birmingham risk model (incorporating recipient factors at 1 year, including age, sex, ethnicity, renal function, proteinuria, and prior acute rejection) predicted death-censored and overall graft survival (c statistics =0.84 and 0.78, respectively). The presence of glomerulitis or chronic interstitial fibrosis (g and ci scores by Banff, respectively) on 1-year biopsy specimens independently correlated with graft loss by 5 years. Adding these variables to the model for death-censored graft loss increased predictability (c statistic =0.90), improved calibration (ability to stratify risk from high to low), and reclassified risk of failure in 29% of patients. Adding the presence of donor-specific alloantibody at 1 year did not improve predictability or reclassification but did improve calibration marginally. We conclude that, at 1 year after kidney transplant, a risk model of graft survival that incorporates clinical factors and histologic findings at surveillance biopsy is highly predictive of individual risk and well calibrated.
Renal retransplantation after a failed prior kidney and pancreas transplant is being increasingly performed. In these complex cases, both iliac fossae have been used for prior transplants, and the placement of the new allograft can be problematic. We describe our experience with an alternative technique for renal retransplantation (RRTx) in the setting of severe bilateral aortoiliac atherosclerosis or scarring and fibrosis on the iliac vessels. Nephrectomy of the failed allograft is performed, and the renal vessels of the failed allograft (RVFA) are preserved. The new kidney is implanted on RVFA at the same operative time. This technique was attempted and successfully accomplished in a total of six patients (mean operative time = 240 ± 63 min). One postoperative complication occurred: poor arterial inflow to the allograft, being corrected reoperatively. Hospitalizations ranged from five to eight d. Five of the six patients were alive with a functioning allograft at last follow-up (a single graft failure occurred 21 months postoperatively in the setting of post-transplant lymphoproliferative disease that also led to patient death). Renal vessels of the failed allograft seem to be suitable alternative vascular conduits for renal retransplantation after prior kidney and pancreas transplants.
Predicting which renal allografts will fail and the likely cause of failure is important in clinical trial design to either enrich patient populations to be or as surrogate efficacy endpoints for trials aimed at improving long-term graft survival. This study tests our previous Birmingham-Mayo model (termed the BirMay Predictor) developed in a lowrisk kidney transplant population in order to predict the outcome of patients with donor specific alloantibody (DSA) at the time of transplantation and identify new factors to improve graft loss prediction in DSA+ patients. We wanted define ways to enrich the population for future therapeutic intervention trials. The discovery set included 147 patients from Mayo Cohort and the validation set included 111 patients from the Paris Cohort-all of whom had DSA at the time of transplantation. The BirMay predictor performed well predicting 5-year outcome well in DSA+ patients (Mayo C statistic = 0.784 and Paris C statistic = 0.860). Developing a new model did not improve on this performance. A high negative predictive value of greater than 90% in both cohorts excluded allografts not destined to fail within 5 years. We conclude that graft-survival models including histology predict graft loss well, both in DSA+ cohorts as well as DSA-patients. K E Y W O R D S alloantibody, clinical research/practice, kidney (allograft) function/dysfunction, kidney transplantation/nephrology, pathology/histopathology, protocol biopsy, risk assessment/risk stratification 1 | INTRODUC TI ON Predicting which renal allografts will fail and the likely cause of failure is important in clinical trial design to either enrich patient populations to be treated (eg, studies design to treat antibody-mediated rejection [ABMR]) or as surrogate efficacy endpoints for trials aimed at improving long-term graft survival. Several studies have demonstrated that kidney transplant recipients who have DSA at the time of transplantation have inferior outcomes to those without DSA. 1-3 Clearly, new therapy is needed to overcome the immunologic hurdle of preformed
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