Liver Transplant Outcomes in the United States : Effect of Preservation Solution
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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

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


Recent retrospective database reviews

Recent Retrospective Database Reviews

Theme of 3 studies: These results suggest that the increasing use of HTK for abdominal organ preservation should be reexamined


Liver preservation

Liver Preservation


Liver preservation1

Liver Preservation

Indiana University, 2001 to 2008

All adult, deceased donor

n=1013

HTK 632, UW 381

Simultaneous, retrospective


Liver preservation2

Liver Preservation

Indiana University, 2001 to 2008

All adult, deceased donor

Simultaneous, retrospective

n=1013HTK 632 UW 381

Serum ALT

Serum Bilirubin


Using the srtr database

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)


Statistical analysis

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


Bootstrapping

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


John fung md phd cleveland clinic

Adjusting for Multiple Tests

Use p = 0.05 / no. of tests


Results

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


John fung md phd cleveland clinic

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 


John fung md phd cleveland clinic

Unadjusted Patient and Graft Survival - HTK vs UW

Adult LTX from 2002-2008: By DRI - 2.5

7,883 UW10,484 UW

1,826 HTK 2,314 HTK

DRI < 2.5 p = 0.20 log rank test DRI >2.5: p = 0.20 


John fung md phd cleveland clinic

Unadjusted Patient and Graft Survival - HTK vs UW

Adult LTX from 2002-2008: By CIT - 8 hrs (non-DCD)

14,053 UW6,119 UW

3,279 HTK 1,177 HTK

CIT < 8 hr p = 0.70 log rank test CIT >8 hr: p = 0.50 


John fung md phd cleveland clinic

Unadjusted Patient and Graft Survival - HTK vs UW

Adult LTX from 2002-2008: By CIT - 12 hrs (non-DCD)

19,082 UW1,090 UW

4,253 HTK 203 HTK

CIT < 12 hr p = 0.80 log rank test CIT >12 hr: p = 0.60 


Risk factors for graft failure early phase

Risk Factors for Graft Failure - Early Phase


Risk factors for graft failure constant phase

Risk Factors for Graft Failure - Constant Phase


Limitations of the hopkins unos analysis

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 


Unadjusted 1 year graft survival rates by year of transplant

Unadjusted 1-year Graft Survival Rates by Year of Transplant


Liver transplant graft survival

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


Liver transplant patient survival

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


Comparing htk users 2010 unos report addlt

Comparing HTK Users - 2010 UNOS Report - ADDLT


Comparing uw users 2010 unos report addlt

Comparing UW Users – 2010 UNOS Report - ADDLT


Conclusions

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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