Currently the OPTN and CMS use 1-year patient and graft survival as metrics to flag transplant programs.1 Waitlist and longer-term posttransplant outcomes are publicly reported and have been suggested as regulatory metrics, but both involve factors outside the transplant center. We tested how well the current survival metrics capture these other dimensions.
We evaluated transplant programs between 2011-2016 using hierarchical regression based on 2017 SRTR risk adjustment models.2,3 We used mixed-effect Poisson regression with center and DSA-level random intercepts for waitlist metrics and center-level shared frailty Cox regression for posttransplant metrics. We ranked centers’ risk-adjusted performance from 1 (best) to N (worst) based on center-level random effects from these models and correlated 1-year posttransplant outcomes with 3-year posttransplant outcomes, deceased donor kidney transplant (DDKT) rates, and waitlist mortality.
1-year and 3-year graft loss were moderately correlated (r=0.75), as were 1-year and 3-year patient mortality (r=0.74) (Figure). However, 1-year graft loss and mortality correlated poorly with DDKT rate (r=0.02, 0.14), and waitlist mortality (r=−0.23, −0.11) (Figure).
Figure. Correlations between rankings of center-level effects (representing average expected outcome at a given center) for adult kidney transplant outcome metrics.
1-year posttransplant metrics calculated using adult recipients 1/1/2014-6/30/2016 (N=28,847), waitlist metrics include adult waitlist registrants 1/1/2014-6/30/2016 (N=187,407), and 3-year metrics include adult recipients 7/1/2011-12/31/2013 (N=26,167). Centers that performed less than 25 transplants during the 2.5-year study periods were excluded (N=190 for 1-year metrics, N=188 for 3-year metrics). Center-level effects based on mixed-effect Poisson regressions (random intercepts) and Cox regressions (shared-frailty) ranked from 1 (best) to N (worst). This study used data from the SRTR.
The high correlation between 1-year and 3-year posttransplant outcomes suggests that regulation based on 1-year metrics is also representative of the longer-term patient experience. In contrast, the independence between posttransplant outcomes versus transplant rates and waitlist outcomes suggests that the underlying mechanisms are different, including the possibility that factors such as geographic organ availability affect transplant rates and waitlist outcomes. If these domains are to be regulated, the risk/benefit of using these metrics will require careful evaluation.
Acknowledgments
FUNDING
This work was supported by the John and Laura Arnold Foundation, an American College of Surgeons Resident Research Scholarship (Holscher), grant K01AG041763 (Nicholas) from the National Institute of Aging, and grants number F32DK109662 (Holscher) and K24DK101828 (Segev) from the National Institute of Diabetes and Digestive and Kidney Diseases. The analyses described here are the responsibility of the authors alone and do not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the U.S. Government.
The data reported here have been supplied by the Minneapolis Medical Research Foundation (MMRF) as the contractor for the Scientific Registry of Transplant Recipients (SRTR). The interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an official policy of or interpretation by the SRTR or the U.S. Government.
ABBREVIATIONS
- CMS
Centers for Medicare and Medicaid Services
- DDKT
Deceased Donor Kidney Transplantation
- DSA
Donor Service Area
- OPTN
Organ Procurement and Transplant Network
- SRTR
Scientific Registry of Transplant Recipient
Footnotes
Dr Allan B. Massie, Dr. Dorry L. Segev, Dr. Lauren H. Nicholas participated in research design. Dr. Sheng Zhou, Dr. Courtenay M. Holscher, Dr. Allan B. Massie, Dr. Dorry L. Segev, and Dr. Lauren H. Nicholas participated in the writing of the paper. Dr. Sheng Zhou participated in data analysis.
DISCLOSURE
The authors declare no conflicts of interest.
References
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