Abstract
OBJECTIVES: To develop a prediction model for kidney transplantation (KT) outcomes specific to older adults with end-stage renal disease (ESRD) and to use this model to estimate the number of excellent older KT candidates who lack access to KT. DESIGN: Secondary analysis of data collected by the United Network for Organ Sharing and U.S. Renal Disease System. SETTING: Retrospective analysis of national registry data. PARTICIPANTS: Model development: Medicare-primary older recipients (aged ≥ 65) of a first KT between 1999 and 2006 (N = 6,988). Model application: incident Medicare-primary older adults with ESRD between 1999 and 2006 without an absolute or relative contraindication to transplantation (N = 128,850). MEASUREMENTS: Comorbid conditions were extracted from U.S. Renal Disease System Form 2728 data and Medicare claims. RESULTS: The prediction model used 19 variables to estimate post-KT outcome and showed good calibration (Hosmer-Lemeshow P = .44) and better prediction than previous population-average models (P < .001). Application of the model to the population with incident ESRD identified 11,756 excellent older transplant candidates (defined as >87% predicted 3-year post-KT survival, corresponding to the top 20% of transplanted older adults used in model development), of whom 76.3% (n = 8,966) lacked access. It was estimated that 11% of these candidates would have identified a suitable live donor had they been referred for KT. CONCLUSION: A risk-prediction model specific to older adults can identify excellent KT candidates. Appropriate referral could result in significantly greater rates of KT in older adults.