Modeling graft loss in patients with donor‐specific antibody at baseline using the Birmingham‐Mayo (BirMay) predictor: Implications for clinical trials. Issue 8 (13th March 2019)

• Record Type: Journal Article
• Authors: Bentall, Andrew; Smith, Byron H.; Gonzales, Manuel Moreno; Bonner, Keisha; Park, Walter D.; Cornell, Lynn D.; Dean, Patrick G.; Schinstock, Carrie A.; Borrows, Richard; Lefaucheur, Carmen; Loupy, Alexandre; Stegall, Mark D.
• Is Part Of: American journal of transplantation. Volume 19:Issue 8(2019)
• Page Start: 2274
• Page End: 2283
• Publication Date: 2019-03-13
• Subjects: alloantibody -- clinical research/practice -- kidney (allograft) function/dysfunction -- kidney transplantation/nephrology -- pathology/histopathology -- protocol biopsy -- risk assessment/risk stratification; Transplantation of organs, tissues, etc -- Periodicals; 617.95
• DOI: 10.1111/ajt.15312
• Languages: English
• ISSNs: 1600-6135

Abstract

Abstract : 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 low‐risk 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. Abstract : Modeling kidney graft loss in patients with donor‐specific antibody at baseline improves identification of higher risk patients and has significant implications for recruitment to clinical trials to improve efficacy.