Factors that affect deceased donor liver transplantation rates in the United States in addition to the model for end-stage liver disease score§


  • This research was presented in part as a poster of excellence at the 2010 American Transplant Congress in San Diego, CA.

  • This study was approved by the Scientific Registry of Transplant Recipients project officer of the Health Resources and Services Administration. The Health Resources and Services Administration has determined that this study satisfies the criteria for an institutional review board exemption described in the public benefit or service program provisions of 45 CFR 46.101(b)(5) and in Health Resources and Services Administration circular 03.

  • §

    Pratima Sharma was supported by grant KO8 DK-088946 from the National Institutes of Health and by a research award from the American College of Gastroenterology. The development of the statistical methodology and the analysis for this investigation were supported in part by grant 5R01 DK-70869 from the National Institutes of Health (to Douglas E. Schaubel). The Scientific Registry of Transplant Recipients is funded by contract 231-00-0116 from the Health Resources and Services Administration (US Department of Health and Human Services). The views expressed herein are those of the authors and not necessarily those of the US Government.


Under an ideal implementation of Model for End-Stage Liver Disease (MELD)–based liver allocation, the only factors that would predict deceased donor liver transplantation (DDLT) rates would be the MELD score, blood type, and donation service area (DSA). We aimed to determine whether additional factors are associated with DDLT rates in actual practice. Data from the Scientific Registry of Transplant Recipients for all adult candidates wait-listed between March 1, 2002 and December 31, 2008 (n = 57,503) were analyzed. Status 1 candidates were excluded. Cox regression was used to model covariate-adjusted DDLT rates, which were stratified by the DSA, blood type, liver-intestine policy, and allocation MELD score. Inactive time on the wait list was not modeled, so the computed DDLT hazard ratios (HRs) were interpreted as active wait-list candidates. Many factors, including the candidate's age, sex, diagnosis, hospitalization status, and height, prior DDLT, and combined listing for liver-kidney or liver-intestine transplantation, were significantly associated with DDLT rates. Factors associated with significantly lower covariate-adjusted DDLT rates were a higher serum creatinine level (HR = 0.92, P < 0.001), a higher bilirubin level (HR = 0.99, P = 0.001), and the receipt of dialysis (HR = 0.83, P < 0.001). Mild ascites (HR = 1.15, P < 0.001) and hepatic encephalopathy (grade 1 or 2, HR = 1.05, P = 0.02; grade 3 or 4, HR = 1.10, P = 0.01) were associated with significantly higher adjusted DDLT rates. In conclusion, adjusted DDLT rates for actively listed candidates are affected by many factors aside from those integral to the allocation system; these factors include the components of the MELD score itself as well as candidate factors that were considered but were deliberately omitted from the MELD score in order to keep it objective. These results raise the question whether additional candidate characteristics should be explicitly incorporated into the prioritization of wait-list candidates because such factors are already systematically affecting DDLT rates under the current allocation system. Liver Transpl, 2012. © 2012 AASLD.