Presented by

Grace Diehl & JJ Trout

February 25, 2013

Mathur, A.K., Heimbach, J., Steffick, D.E., Sonnenday, C.J., Goodrich, N.P. & Merion, R.M. (2010). Donation after cardiac death liver transplantation: Predictors of outcome. American Journal of Transplantation, 10, 2512-2519. doi: 10.1111/j.1600-6143.2010.03292.x

Donation after Cardiac Death Donation after Cardiac Death Liver Transplantation: Liver Transplantation: Predictors of OutcomePredictors of Outcome

http://www.guardian.co.uk/science/2011/oct/12/skin-liver-cells-inherited-disease

Presentation Outline

• Background Information• Purpose & Goals of the Study• Materials and Methods• Results• Conclusions• Significance and Future Directions of the Research

Background Information• Scientific Registry of Transplant Recipients (1987) (SRTR)

• National database of transplant statistics

• Evaluation/Research/Policy of solid organ transplants

• Collect: OPTN (Organ Procurement and Transplantation Network) & OPOs (Organ Procurement Organizations)

• 2011 Report: 5,805 adult liver transplants (OPTN/SRTR)• 5,531 brain dead; 266 DCD; 188 live

• Waitlist: ~14,000

• Disease: • Cholestatic (bile cannot flow)• Metabolic/Malignancy…

Background Information ContinuedSurgical Plan (University Health Network, 2012)• The liver would be transected with a plane that divides the intrahepatic left hepatic vein.

• Parenchymal transection would be performed until the intrahepatic left hepatic vein is reached.

• A standard IV tubing would be inserted into the main portal vein, and the hepatic artery and portal vein would be clamped.

• The vena cava would then be cross-clamped above and below the liver.

• While the left hepatic vein is divided, ice cold HTK solution would be perfused through the IV tubing. Sterile ice would also be placed around the liver remnant.

• The confluence of the middle/left hepatic vein would be divided at the cava, and then anastomosed to the divided left hepatic vein.

• A Roux-en-Y hepatico-jejunostomy will be performed to reconstruct the biliary circulation.

http://pie.med.utoronto.ca/TVASurg/TVASurg_content/surg/TL_coldPerfusion.html

Background Information Continued• Terms:

• Ischemic cholangiopathy/ischemic biliary strictures• Damage to bile ducts caused by inadequate blood flow, specific narrowing

• Cold Ischemia Time (CIT)• Time from devascularization in donor to repurfusion in recipient (Furukawa

et al., 1991).• Donor Warm Ischemia Time (DWIT):

• Time of cross clamping until cold perfusion is started (Halazun, Al-Mukhtar, Aldouri, Willis, & Ahmad, 2007).

• Model for End-Stage Liver Disease (MELD):• Predictor of death & used for waitlist priority• Based on INR (international normalized ratio for prothrombin time, bilirubin,

creatinine (Weisner et. al, 2003).• 40 or more — 71.3% mortality • 30–39 — 52.6% mortality • 20–29 — 19.6% mortality • 10–19 — 6.0% mortality • <9 — 1.9% mortality

• Known factors of Ischemic cholangiopathy and graft failure from single center studies:

• Donor weight• Donor age• Cold Ischemia time (CIT)

6

Purpose and Goals of the Study• Investigating: Donors after Cardiac Death (DCD) Liver

Transplantation

• Using the Scientific Registry of Transplant Recipients (SRTR) determine risk factors in:• Donor• Recipient• Transplant

• Better understand post-transplant outcomes including:• Graft Failure• Re-transplantation• Patient Mortality Rates

• Hypothesis: Factors demonstrated in prior single-center studies associated with ischemic cholangiopathy including donor weight, donor age, and cold ischemia time (CIT) would also be associated with graft failure and posttransplant mortality. **Cannot calculate ischemic cholangiopathy due to definition/time of onset not uniformly reported

Materials and Methods

• Used SRTR to construct retrospective cohort to determine risk of failure• DCD liver transplant recipients• Liver-only grafts• September 1, 2001 to April 30, 2009 (~7.5 years)• 80% greater than 1 year follow up: minimum 182 days• Data from Organ Procurement and Transplantation Network

(OPTN)• Cross reference for validation with the Social Security Death

Master File and other data sources for donor and recipient mortality

• Cross validation is good – increased strength of the study

• Data on: candidate, recipient, donor demographics, comorbidities, disease progression, clinical risk factors, post-transplant outcomes with graft failure and recipient death

Materials and Methods Continued

• Cumulative Incidence: measure of disease frequency during a period of time

• Find the competing risk rate of post-DCD transplant outcomes over time

• Multivariable Cox proportional hazard models• Estimate the treatment effect on survival time of an individual after an

adjustment for explanatory variables (XLSTAT, 2013)

• Good model for the study: accounts for death which is heavily censored • Determine donor, recipient, transplant predictors of inferior DCD outcomes

• Separate models for graft failure and posttransplant mortality• (1) Graft failure: re-transplantation event or death (the earlier)• (2) Mortality: live or die

• Time-varying covariate: allow for flexibility in the model when re-transplant occurs• Time? Was re-transplant necessary because of the graft or something else?

• Combined individual covariate effects that had the most clinical impact were tested in both models to create interaction terms

• All patients had 6 months of follow up: don’t want to include those who died right away, indicator of comorbidity

Materials and Methods Continued

Donor Variables

Age

Race

BMI

Weight

Cause of Death

Recipient Characteristics

Age

Race

Sex

Medical Condition

Prior liver transplant

DiagnosisPre-existing malignancy

DiabetesPrior Abdominal Surgery

Portal Vein Thrombosis

Transplant Characteristics

Local vs. Shared Donor

Partial or Split Liver

ABO compatibility

DWIT*

CIT*

*: each form determined by lowess plots of marginale residuals and statistical significance of the covariates in the failure model

• Fewer than 10% of total data across all variables were missing and indicators were used for missing data

Results: Table 1Demographic & Clinical Characteristics of DCD Transplant

Recipient Data of Note:•5% previous liver transplant•20% hospitalized at time of transplant•5% Status 1

Results: Table 1Demographic & Clinical Characteristics of DCD Transplant

Donor Data of Note:•Average age 35.2 years•2/3 male•Average weight 77.3 Kg•Traumatic Injury = Cause of Death•2.5% Uncontrolled

Transplant Data of Note:•Mean CIT 7.5 hours•Mean DWIT 16 minutes•60% local

Results: Figure 1Cumulative Incidence of Post-DCD Liver Transplant Outcomes

• Highest rate of death is during the first year

• Relisting occurred in 19.9%, median of 73.5 days following transplantation

• MELD at relisting was 21 (16-29)

• Majority of retransplants occurred in the first few months following DCD transplantation

Results: Table 2Predictors of Graft Failure Following DCD Liver TransplantRecipient Data of Note:•AGE: Recipients >55 26% higher failure than 18-55; <18 = lower graft failure•GENDER: Female protective•RACE: African Am 38% higher failure vs white•DISEASE: Metabolic 2x higher failure than noncholestatic

Recipient Data of Note:•PRIOR TRANSPLANT: 45% higher failure•MELD: MELD > 35 46% higher failure than MELD 15-25•HOSPITALIZATION & LIFE SUPPORT also signficiant indicators•Not Status 1

Results: Table 2Predictors of Graft Failure Following DCD Liver Transplant

Donor Data of Note:•AGE: >50 39-88% higher risk vs 18-50•WEIGHT: >100 56% higher risk than <100•Cause of Death NOT associated

Transplant Data of Note:•DWIT & CIT independently significant•Continuously: each hour = 6% increase fail•Categorically: even 6-10h had 64% higher fail vs <6; 2x risk >10h; 4x risk at 13h.•Missing = proxy for longer

Results: Figure 2DWIT Distribution Among 1567 DCD Liver Transplant Recipients

• 3.8% grafts implanted with warm ischemia times >35 minutes

• DWIT “threshold effect” at 35 minutes: significantly increased graft failure rates

Results: Figure 3Effect of DWIT on Graft Failure Following DCD Liver Transplant

Data of Note:•Multivariate COX Regression approach•DWIT has significant effect on graft failure (retransplant or death).•DWIT of 35 minutes or greater = threshold; 1.8 times higher graft loss vs less than 15 min•No sig difference <15 vs 15-35

Results: Table 3Predictors of Mortality Following DCD Liver Transplantation• Older Recipient age (>55): 60% higher

mortality rate• Retransplantation: 2.4 times higher

mortality rate than those with functional grafts

• Hospitalization: 48% higher risk of dying vs. ambulatory recipients

• Higher MELD scores not associated with post-transplant mortality

• Status 1 Medical Emergency not predictive of post-transplant mortality

Conclusions• Hypothesis was partially supported: predictive

indicators of ischemic cholangiopathy on longer term graft failure/mortality in comprehensive study:• Donor age, weight, and CIT significant for failure• Donor age and CIT significant for mortality (not weight)• But no significant interactions

• Further Conclusions:• >1/3 DCD transplants die, or require another transplant 3

years after• MELD >35 significant for failure; not mortality• Retransplants had higher mortality rate• Recipient Race/Disease/Gender/Hospitalization/Age/Life

Support/MELD all significant indicators

Significance of the Research

• Possible improved informed consent process of risks associated with specific DCD transplants

• Transplant surgeons can create better DCD acceptance protocols

• Provided framework to judge clinical risk of DCD transplants

• Assist providers in recommendations of DCD transplants to patients based on their individual characteristics, needs and organ availability• Selective utilization of DCD liver transplants: grafts from older,

heavier donors with long CIT to be used with caution

• Study is limited: depth and quality of SRTR (OPTN) data• Confounding factor – inability to account for variations from DCD

liver procurement practices, reducing applicability

Future Directions

• Collection of additional data • serial hemodynamic measurements• other physiological parameters

• Identify clinical tools to decrease risk of biliary injury in DCD grafts

• Modify allocation rules to increase access to retransplantation after failed DCD liver transplants

• Refine understanding of risk factors of DCD liver transplants

http://thinkingfutures.net/wp-content/uploads/2010/10/future-direction-sign.jpg

References

Furukawa, H., Todo, S., Imventarza, O., Wu, Y.M., Scotti, C., Day, R., & Starzl, T.E. (1991). Cold ischemia time vs outcome of human liver transplantation using UW solution. Transplant Procedures, 23(1.2), 1550-1551.

Halazun, K.J., Al-Mukhtar, A., Aldouri, A., Willis, S., & Ahmad, N. (2007). Warm ischemia in transplantation: search for a consensus definition. Transplant Procedures, 39(5), 1329-1331.

OPTN/SRTR (n.d.). OPTN/SRTR 2011 annual data report: Liver. In U.S. Department of Health and Human Services. Retrieved February 20, 2013 from http://srtr.transplant.hrsa.gov/annual_reports/2011/pdf/03_%20liver_12.pdf

Sample, I. (2011, October 12). Skin transformed into liver cells to treat an inherited disease. The Guardian. Retrieved from http://www.guardian.co.uk/science/2011/oct/12/skin-liver-cells-inherited-disease

SRTR (n.d.). About the SRTR. In SRTR. Retrieved February 20, 2013 from http://www.srtr.org/who.aspx

University Health Network (n.d.). In-situ cold perfusion. In Toronto Video Atlas of Liver, Pancreas, and Transplant Surgery. Retrieved February 20, 2013 from http://pie.med.utoronto.ca/TVASurg/TVASurg_content/surg/TL_coldPerfusion.html

Wiesner, R., Edwards, E., Freeman, R., Harper, A., Kim, R., Kamath, P., Kremers, W.,…Krom, R. (2003). Model for end-stage liver disease (MELD) and allocation of donor livers. Gastroenterology, 124(1), 91-96.

XLSTAT (n.d.) Cox proportional hazards models. Retrieved February 11, 2013 from http://www.xlstat.com/en/products-solutions/feature/cox-proportional-hazards-models.html

Questions?