Development and validation of a model predicting graft survival after liver transplantation


  • George N. Ioannou

    Corresponding author
    1. Division of Gastroenterology, Department of Medicine, Hepatitis C Resource Center, Health Services Research and Development, Seattle, WA
    2. Research Enhancement Award Program, Veterans Affairs Puget Sound Health Care System, Seattle, WA
    3. Division of Gastroenterology, Department of Medicine, University of Washington, Seattle, WA
    • Veterans Affairs Puget Sound Health Care System, Gastroenterology, S-111-Gastro, 1660 S. Columbian Way, Seattle, WA 98108
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  • This research was based on data derived from the United Network for Organ Sharing on October 6, 2003. The content is the responsibility of the author alone and does not necessarily reflect the views or policies of the Department of Health and Human Services.


This study aimed to develop and validate a comprehensive model that predicts survival after liver transplantation based on pretransplant donor and recipient characteristics. Complete data were available from the United Network for Organ Sharing for 20,301 persons who underwent liver transplantation in the United States between 1994 and 2003. Proportional-hazards regression was used to identify the donor and recipient characteristics that best predicted survival and incorporate these characteristics in a multivariate model. A data-splitting approach was used to compare survival predicted by the model to the observed survival in samples not used in the derivation of the model. A model was derived using 4 donor characteristics (age, cold ischemia time, gender, and race/ethnicity) and 9 recipient characteristics (age, body max index, model for end-stage liver disease score, United Network for Organ Sharing priority status, gender, race/ethnicity, diabetes mellitus, cause of liver disease, and serum albumin) that adequately predicted survival after liver transplantation in patients without hepatitis C virus, and a slightly different model was used for patients with hepatitis C virus. The models illustrate that variations in both pretransplant donor and recipient characteristics have a large effect on posttransplant survival. In conclusion, the models presented here can be used to derive scores that are proportional to the excess risk of graft loss after liver transplantation for potential donors, recipients, or donor/recipient combinations. The models may be used to inform liver transplant candidates and their doctors what posttransplant survival would be expected when a given donor is offered and may be particularly helpful for marginal or high-risk donors. Liver Transpl, 2006. © 2006 AASLD.