A model for dropout assessment of candidates with or without hepatocellular carcinoma on a common liver transplant waiting list

Hepatology. 2012 Jul;56(1):149-56. doi: 10.1002/hep.25603. Epub 2012 Jun 18.


In many countries, the allocation of liver grafts is based on the Model of End-stage Liver Disease (MELD) score and the use of exception points for patients with hepatocellular carcinoma (HCC). With this strategy, HCC patients have easier access to transplantation than non-HCC ones. In addition, this system does not allow for a dynamic assessment, which would be required to picture the current use of local tumor treatment. This study was based on the Scientific Registry of Transplant Recipients and included 5,498 adult candidates of a liver transplantation for HCC and 43,528 for non-HCC diagnoses. A proportional hazard competitive risk model was used. The risk of dropout of HCC patients was independently predicted by MELD score, HCC size, HCC number, and alpha-fetoprotein. When combined in a model with age and diagnosis, these factors allowed for the extrapolation of the risk of dropout. Because this model and MELD did not share compatible scales, a correlation between both models was computed according to the predicted risk of dropout, and drop-out equivalent MELD (deMELD) points were calculated.

Conclusion: The proposed model, with the allocation of deMELD, has the potential to allow for a dynamic and combined comparison of opportunities to receive a graft for HCC and non-HCC patients on a common waiting list.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Analysis of Variance
  • Carcinoma, Hepatocellular / pathology
  • Carcinoma, Hepatocellular / surgery*
  • Female
  • Humans
  • Incidence
  • Kaplan-Meier Estimate
  • Liver Failure / pathology
  • Liver Failure / surgery*
  • Liver Neoplasms / pathology
  • Liver Neoplasms / surgery*
  • Liver Transplantation / methods
  • Liver Transplantation / statistics & numerical data*
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Patient Dropouts / statistics & numerical data*
  • Patient Selection
  • Predictive Value of Tests
  • Proportional Hazards Models
  • Registries
  • Retrospective Studies
  • Risk Assessment
  • Switzerland
  • Tissue and Organ Procurement
  • Waiting Lists*