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John Fung, MD, PhD Cleveland Clinic

Liver Transplant Outcomes in the United States : Effect of Preservation Solution DKFC Symposium July 16, 2012. John Fung, MD, PhD Cleveland Clinic. Disclosure: I have been a past consultant for both Dupont and Odyssey. Recent Retrospective Database Reviews.

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John Fung, MD, PhD Cleveland Clinic

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  1. Liver Transplant Outcomes in the United States : Effect of Preservation SolutionDKFC SymposiumJuly 16, 2012 John Fung, MD, PhD Cleveland Clinic Disclosure: I have been a past consultant for both Dupont and Odyssey

  2. Recent Retrospective Database Reviews Theme of 3 studies: These results suggest that the increasing use of HTK for abdominal organ preservation should be reexamined

  3. Liver Preservation

  4. Liver Preservation Indiana University, 2001 to 2008 All adult, deceased donor n=1013 HTK 632, UW 381 Simultaneous, retrospective

  5. Liver Preservation Indiana University, 2001 to 2008 All adult, deceased donor Simultaneous, retrospective n=1013 HTK 632 UW 381 Serum ALT Serum Bilirubin

  6. Using the SRTR Database • Only adult first liver-only transplants from 2002-2008 were included and only for those whom flush and storage solutions were the same • All patients had minimum one year follow up • 25,616 patients, 20,901 (82%) with UW and 4,715 (18%) with HTK • Mean follow-up: 2.7 ± 1.7 years (2.9 ± 1.7 for UW and 1.8 ± 1.1 for HTK)

  7. Statistical Analysis • Three comparisons: • Unadjusted graft survival • Bootstrapping hazard modeling using risk factors for graft survival determined using non-proportional, multiphase, multivariable hazard methodology with >100 clinically relevant recipient, donor, and procedure variables • Propensity-matched comparison for 50 most important variables

  8. Bootstrapping • A random sample of patients is drawn from the original data - patients are drawn one at a time, with replacement, until a new dataset of the same size has been created • When the new dataset has been created, the stepwise regression technique is run again to see what significant predictors it finds and the process is repeated multiple times • The bootstrap percentage is the percent of runs in which the variable appeared, so the higher the percentage, the more certain is the impact of that variable - those appearing in >50% of runs were considered reliably statistically significant at p<0.001

  9. Adjusting for Multiple Tests Use p = 0.05 / no. of tests

  10. Results • Validation of reported significant recipient factors of graft failure in the early and later phases after DDLT • OPS did not appear as a statistically significant predictor of graft failure • hospital death, re-transplant rates and relisting rates were not different

  11. Unadjusted Patient and Graft Survival - HTK vs UW Adult LTX from 2002-2008 UW n = 20,901 HTK n = 4,715 PS: p = 0.90 log rank test GS: p = 0.60 

  12. Unadjusted Patient and Graft Survival - HTK vs UW Adult LTX from 2002-2008: By DRI - 2.5 7,883 UW 10,484 UW 1,826 HTK 2,314 HTK DRI < 2.5 p = 0.20 log rank test DRI >2.5: p = 0.20 

  13. Unadjusted Patient and Graft Survival - HTK vs UW Adult LTX from 2002-2008: By CIT - 8 hrs (non-DCD) 14,053 UW 6,119 UW 3,279 HTK 1,177 HTK CIT < 8 hr p = 0.70 log rank test CIT >8 hr: p = 0.50 

  14. Unadjusted Patient and Graft Survival - HTK vs UW Adult LTX from 2002-2008: By CIT - 12 hrs (non-DCD) 19,082 UW 1,090 UW 4,253 HTK 203 HTK CIT < 12 hr p = 0.80 log rank test CIT >12 hr: p = 0.60 

  15. Risk Factors for Graft Failure - Early Phase

  16. Risk Factors for Graft Failure - Constant Phase

  17. Limitations of the Hopkins UNOS Analysis • Used case-wise deletion of missing data, i.e. used only patients for whom all variables were reported - the actual number of cases deleted not provided • Last case included was 2/28/08 - the paper was submitted on 7/17/08.  Allowing a minimum of 45 days to analyze and write the paper, the latest data cutoff was 6/1/08. Using UNOS timelines for a 6/1/08 cutoff, there would only have been data for transplants performed before 11/1/07 

  18. Unadjusted 1-year Graft Survival Rates by Year of Transplant

  19. SRTR Data, 2000-2010, N=55110, Age 18+ By Years and Preservation Solution: 2001-2005 vs 2006-2010 and UW vs HTK HTK 2006-10 Liver Transplant Graft Survival UW 2006-10 HTK 2000-5 UW 2000-5 SRTR Data, 2000-2010, N=55110, Age 18+ By Years and Preservation Solution: 2001-2005 vs 2006-2010 and UW vs HTK

  20. SRTR Data, 2000-2010, N=55110, Age 18+ By Years and Preservation Solution: 2001-2005 vs 2006-2010 and UW vs HTK HTK 2006-10 Liver Transplant Patient Survival UW 2006-10 HTK 2000-5 UW 2000-5 SRTR Data, 2000-2010, N=55110, Age 18+ By Years and Preservation Solution: 2001-2005 vs 2006-2010 and UW vs HTK

  21. Comparing HTK Users - 2010 UNOS Report - ADDLT

  22. Comparing UW Users – 2010 UNOS Report - ADDLT

  23. Conclusions • Discrepancies between published reports and clinical experience: • Flawed analysis • Learning curve • Changing practices • Excellent outcomes can be obtained with either solution

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