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Keywords:

  • kidney transplantation;
  • older adults;
  • risk prediction;
  • transplant outcomes

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.