Factors that affect deceased donor liver transplantation rates in the United States in addition to the Model for End-stage Liver Disease score

Abstract

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.

Figure 1. Effect of allocation MELD, per single level change, on DDLT rate

MELD score-specific hazard ratios (HR) are estimated from a model which stratified by DSA, blood type and intestine-listing policy. Each score is compared to the reference, MELD=15 (HR=1).

Figure 2. MELD score-specific box-whisker plots of the DDLT hazard ratios (HR)

The HR’s are estimated using a model stratified by MELD, DSA, blood type and intestine-listing policy. Candidate-specific HRs estimated using all remaining covariates and scaled by their MELD score specific means such that they average to 1. Within each MELD score, the box represents the 75th and 25th percentiles, while the whiskers denote the 95th and 5th percentile. The line in the middle of the box denotes the median, which tends to be very close to 1 since the HRs within each MELD score were scaled such that they average to 1. If MELD score was the only factor (other than DSA, blood type and liver/intestine policy) to affect DDLT rates, then there would be no distribution of HRs; within a given MELD score, each candidate would have the same predicted DDLT rate which, after scaling, would equal 1. The whiskers within each MELD score-specific distribution of HRs reflects the systematic heterogeneity in DDLT rates due to various candidate factors.