A1117
Title: A comparison of methods for externally validating the Kidney Donor Risk Index in the UK kidney transplant population
Authors: Stephanie Riley - University of Plymouth (United Kingdom)
Andrew Connor - University Hospitals Plymouth NHS Trust (United Kingdom)
Wai-yee Tse - University Hospitals Plymouth NHS Trust (United Kingdom)
Yinghui Wei - Plymouth University (United Kingdom) [presenting]
Abstract: Transplantation represents the optimal treatment for many patients with end-stage kidney disease. The Kidney Donor Risk Index (KDRI) was developed to predict graft failure following kidney transplantation. The survival process following transplantation consists of semi-competing events, where recipient death precludes graft failure but not vice-versa. We sought to externally validate the KDRI in the UK kidney transplant population, and assess whether validation under a competing risks framework had an impact on predictive performance. Additionally, we updated the KDRI using data from the United Kingdom to explore whether this improved the predictive performance. Using data from recipients of deceased donor single kidney-only transplants, held by NHS Blood and Transplant, we externally validated the KDRI. Our outcomes of interest were one- and five-year graft failure. Considering the semi-competing events, we modelled the outcome in two ways: censoring the recipient at the time of death, and modelling death as a competing event. Cox proportional hazard models were used to validate the KDRI when censoring for death, and cause-specific Cox models were used to account for death as a competing event. KDRI performance was assessed by discrimination, calibration, and overall accuracy of predictions.
