Transition probabilities between changing sensitization levels, waitlist activity status and competing-risk kidney transplant outcomes using multi-state modeling
Sanjay Kulkarni,
Isaac Hall,
Richard Formica,
Carrie Thiessen,
Darren Stewart,
Geliang Gan,
Erich Greene and
Yanhong Deng
PLOS ONE, 2017, vol. 12, issue 12, 1-14
Abstract:
Background: Sensitization and activity status are associated with kidney transplant waitlist mortality. Unknown is how changes in these covariates after listing impact transplant outcomes. Methods: Two cohorts were created from the OPTN (Organ Procurement and Transplantation Network) database, one pre-KAS (new kidney allocation system) (10/01/2009-12/04/2013, n = 97,793) and one post-KAS (12/04/2014-06/17/2015, n = 13,113). Multi-state modeling provides transition probabilities between intermediate states (CPRA category/activity status combinations) and competing-risk outcomes: transplant (living), transplant (deceased), death, or other/well. Results: Transition probabilities show chances of converting between intermediate states prior to a competing-risk outcome. One year transplant probabilities for post-KAS candidates with a CPRA of 0%(P, 0.123[95% CI, 0.117,0.129]), 1–79%(P, 0.125 [95% CI, 0.112,0.139]), 95–98%(P, 0.242[95% CI, 0.188, 0.295]) and 99–100%(P, 0.252 [95% CI, 0.195, 0.308]) were significantly higher than the pre-KAS cohort; they were lower for CPRA 80–89%(P, 0.152 [95% CI, 0.116,0.189]) and not statistically different for CPRA 90–94%(P, 0.180 [95% CI, 0.137,0.223]) candidates. Post-KAS, Whites had a statistically higher transplant probability only at a CPRA of 99–100%. Conclusion: Multi-state modeling provides transition probabilities between CPRA/activity status combinations, giving estimates on how changing patient characteristic’s after listing impact outcomes. Preliminarily, across most CPRA categories, there was no statistical difference in transplant probabilities between Whites, Blacks and Hispanics following KAS implementation, however, this finding requires longer follow-up for validation.
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0190277
DOI: 10.1371/journal.pone.0190277
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