[Editorial Comments by Dr. Ann M. O'Hare, pp 151–153]
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Clinical Investigations
Candidacy for Kidney Transplantation of Older Adults
Article first published online: 12 JAN 2012
DOI: 10.1111/j.1532-5415.2011.03652.x
© 2012, Copyright the Authors Journal compilation © 2012, The American Geriatrics Society
Additional Information
How to Cite
Grams, M. E., Kucirka, L. M., Hanrahan, C. F., Montgomery, R. A., Massie, A. B. and Segev, D. L. (2012), Candidacy for Kidney Transplantation of Older Adults. Journal of the American Geriatrics Society, 60: 1–7. doi: 10.1111/j.1532-5415.2011.03652.x
Publication History
- Issue published online: 12 JAN 2012
- Article first published online: 12 JAN 2012
Funded by
- National Institutes of Health. Grant Number: T32 DK 007732–15
- NIH. Grant Number: K23AG032885
- American Federation of Aging Research. Grant Number: R21DK085409
- Abstract
- Article
- References
- Cited By
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.