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MDM Policy Pract. 2018 Jun 17;3(1):2381468318781811. doi: 10.1177/2381468318781811. eCollection 2018 Jan-Jun.

The Lifetime Health Burden of Delayed Graft Function in Kidney Transplant Recipients in the United States.

Author information

1
Precision Health Economics, Oakland, California.
2
Alexion Pharmaceuticals Inc., New Haven, Connecticut.
3
Brigham and Women's Hospital, Boston, Massachusetts.

Abstract

Background. Although delayed graft function (DGF) is associated with an increased risk of acute rejection and decreased graft survival, there are no estimates of the long-term or lifetime health burden of DGF. Objectives. To estimate the long-term and lifetime health burden of DGF, defined as the need for at least one dialysis session within the first week after transplantation, for a cohort representative of patients who had their first kidney transplant in 2014. Methods. Data from the United States Renal Data System (USRDS; 2001-2014) were used to estimate a semi-Markov parametric multi-state model with three disease states. Maximum length of follow-up was 13.7 years, and a microsimulation model was used to extrapolate results over a lifetime. The impact of DGF was assessed by simulating the model for each patient in the cohort with and without DGF. Results. At the end of 13.7 years of follow-up, DGF reduces the probability of having a functioning graft from 52% to 32%, increases the probability of being on dialysis from 10% to 19%, and increases the probability of death from 38% to 50% relative to transplant recipients who do not experience DGF. A typical transplant recipient with DGF (median age = 53) is observed to lose 0.87 quality-adjusted life-years (QALYs). Extrapolated over a lifetime, the same 53-year-old DGF patient is projected to lose 3.01 (95% confidence interval: 2.33, 3.70) QALYs relative to a transplant recipient with the same characteristics who does not experience DGF. Conclusions. The lifetime health burden of DGF is substantial. Understanding these consequences will help health care providers weigh kidney transplant decisions and inform policies for patients in the context of varying risks of DGF.

KEYWORDS:

delayed graft function; graft failure; kidney transplant; microsimulation; semi-Markov multi-state model

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