The Eurotransplant Donor Risk Index in Liver Transplantation: ET-DRI

Braat, Andries E.; Blok, Joris J.; Putter, Hein; Adam, René; Burroughs, Andrew K.; Rahmel, Axel; Porte, Robert J.; Rogiers, Xavier; Ringers, J.

doi:10.1111/j.1600-6143.2012.04195.x

Cited by 258 publications

(285 citation statements)

References 19 publications

(25 reference statements)

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“…Matching criteria limits were extended when no suitable matches were identified. Ten donor livers were within standard criteria and the other 10 donor livers were specifically selected as high-risk, using criteria based on the Eurotransplant Donor Risk Index (16).…”

Section: Matchingmentioning

confidence: 99%

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Liver Transplantation After Ex Vivo Normothermic Machine Preservation: A Phase 1 (First-in-Man) Clinical Trial

Ravikumar

Jassem

Mergental

et al. 2016

American Journal of Transplantation

397

410

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Joint first authors. ISRCTN 14355416.The number of donor organs suitable for liver transplantation is restricted by cold preservation and ischemia-reperfusion injury. We present the first patients transplanted using a normothermic machine perfusion (NMP) device that transports and stores an organ in a fully functioning state at 37°C. In this Phase 1 trial, organs were retrieved using standard techniques, attached to the perfusion device at the donor hospital, and transported to the implanting center in a functioning state. NMP livers were matched 1:2 to cold-stored livers. Twenty patients underwent liver transplantation after NMP. Median NMP time was 9.3 (3.5-18.5) h versus median cold ischaemia time of 8.9 (4.2-11.4) h. Thirty-day graft survival was similar (100% NMP vs. 97.5% control, p = 1.00). Median peak aspartate aminotransferase in the first 7 days was significantly lower in the NMP group ) versus , p = 0.03). This first report of liver transplantation using NMP-preserved livers demonstrates the safety and feasibility of using this technology from retrieval to transplantation, including transportation. NMP may be valuable in increasing the number of donor livers and improving the function of transplantable organs.Abbreviations: AST, aspartate transaminase; DBD, donation after brain death; DCD, donation after circulatory death; IRI, ischemia-reperfusion injury; IVC, inferior vena cava; MELD, model for end-stage liver disease; NHSBT, National Health Service Blood and Transplant; NMP, normothermic machine perfusion

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Section: Matchingmentioning

confidence: 99%

“…Matched control patients were identified as described above; to find two matched controls, preset criteria were extended in some cases, MELD was 12 in NMP versus 14 (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25) in matched controls (p = 0.55).…”

Section: Donor and Recipient Characteristicsmentioning

confidence: 99%

Liver Transplantation After Ex Vivo Normothermic Machine Preservation: A Phase 1 (First-in-Man) Clinical Trial

Ravikumar

Jassem

Mergental

et al. 2016

American Journal of Transplantation

397

410

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“…We would like to thank Avolio et al (1) for the comments on our article on the Eurotransplant Donor Risk Index (ET-DRI) (2). The Authors address an important issue: the practical incorporation of donor risk into liver allocation algorithms.…”

Section: To the Editormentioning

confidence: 99%

Incorporation of Donor Risk Into Liver Allocation Algorithms

Braat

Blok

Rahmel

et al. 2013

American Journal of Transplantation

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We would like to thank Avolio et al. (1) for the comments on our article on the Eurotransplant Donor Risk Index (ET-DRI) (2). The Authors address an important issue: the practical incorporation of donor risk into liver allocation algorithms. It is suggested that the ET-DRI should first be compared to existing donor-to-recipient-matching (D2Rm)-models, such as D-MELD (3), BAR (4) or SOFT (5), for applicability and accuracy before using it in liver allocation.We fully agree that transplantation outcome depends on donor, transplant and recipient risk factors. Of course, combining all these factors would lead to the best assessment of pretransplant risk and therefore best estimation of posttransplant results (note that all risk models are from observational studies, and have never been tested prospectively to confirm predictive value). The first step is to look into donor and transplant factors, as did Feng et al. (6) for the UNOS region. In our current study we describe all significant donor-and transplant risk factors within the Eurotransplant-region, and combine these into one number/score-the ET-DRI. The scores mentioned by Avolio et al. only include some of these factors or factors that were not significant in our study; D-MELD only includes donor age, BAR includes donor age and cold ischemia time (CIT), and SOFT includes donor age, cause of death, creatinine, allocation and CIT. The interesting thing about the ET-DRI (and DRI) is that it is the strongest risk indicator when looking at donor and transplant factors, and it is a continuous and validated score. It provides one number that represents the hazard ratio (HR) of that specific liver allograft, including the transplant factors allocation and CIT.Step 2 will be to investigate significant risk factor in recipients. Ultimately, research will be needed to see how to best integrate both (donor/transplant and recipient) scores to develop a D2R model, as stated by Avolio et al.Scores like D-MELD, BAR and SOFT do not take the strongest donor factors into account: split-liver (HR1.67) and donation after cardiac death (DCD) (HR1.71). Although such allografts are scarce for the total Eurotransplant region (6.5%), they account for almost 25% in, for example, the Netherlands, and in our opinion should therefore be incorporated in donor risk stratification.Clearly, further research is needed, especially for recipient risk factors. The ET-DRI (DRI) gives a validated specific HR for every single allograft, which is necessary to correct for in such research. Currently the only factor used in allocation is the extended criteria donor (ECD). We showed the superiority of ET-DRI over ECD for use within the Eurotransplant region. Further steps to be taken are development of a (validated) recipient risk index and the incorporation of donor and recipient risk scores into a risk stratifying model.Finally we agree that scores may be helpful for allocation, but cannot replace individual assessment and decision making of the transplantation team. In addition, the socioethical choi...

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“…In the near past, several scores to assess the individual risk of early graft failure have been developed. [1][2][3][4] One of these was suggested by Braat and associates to best fit the donor characteristics and resulting risks in the European transplant region. 1 In addition to various factors that were found to be significant predictors of graft outcome, some studies have revealed that donor-recipient sex mismatch (in particular female donor-male recipient) negatively affects graft survival.…”

Section: Introductionmentioning

confidence: 99%

“…[1][2][3][4] One of these was suggested by Braat and associates to best fit the donor characteristics and resulting risks in the European transplant region. 1 In addition to various factors that were found to be significant predictors of graft outcome, some studies have revealed that donor-recipient sex mismatch (in particular female donor-male recipient) negatively affects graft survival. [5][6][7] However, other studies have reported either that male-female mismatch had no effect or attributed the outcome difference to other donor factors.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2016

Exp Clin Transplant

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Objectives: The influence of donor-recipient sex mismatches on long-term graft survival after liver transplant is controversial. In this study, our aim was to characterize the differences in long-term graft outcome after liver transplant in more than 2000 cases with special regard to sex match and mismatch. Materials and Methods: In this retrospective, single center study of 2144 adult primary liver transplant recipients (median follow-up of 92 months), we analyzed specific long-term graft survival and the effect of different donor and recipient sex combinations (KaplanMeier, multivariate regression). Results: In the 15-year follow-up, female recipients (58.6%) had significantly better graft survival than male recipients did (51.6%, P = .031). Matched and mismatched male-female combinations revealed significant differences (P = .003): a male donor-female recipient combination showed the best 15-year graft survival (61.1%), and a female donor-male recipient combination showed the worst graft survival (48.6%), whereas male-male (53.3%) and female-female combinations (55.6%) were not significantly different (P = .967). Donor age (P < .0001), body mass index (P = .021), female sex (P = .015), Eurotransplant Donor Risk Index > 1.4 (P < .001), recipients' age (P < .0001), indication for liver transplant (P < .0001), and kidney function (P = .003) significantly affected graft survival. In the multivariate analysis model, a Eurotransplant Donor Risk Index > 1.4 and impaired kidney function at liver transplant again emerged as significant negative predictors. Female donors and male recipients showed significantly more unfavorable characteristics concerning long-term graft survival. Conclusions:The impressive long-term graft survival benefit of male donor-female recipient versus female donor-male recipient and of male donor-female recipient versus matched groups (male-male, femalefemale) in liver transplant may be caused by significant differences in donor quality and recipient charac teristics and may not be related to sex itself.

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The Eurotransplant Donor Risk Index in Liver Transplantation: ET-DRI

Cited by 258 publications

References 19 publications

Liver Transplantation After Ex Vivo Normothermic Machine Preservation: A Phase 1 (First-in-Man) Clinical Trial

Liver Transplantation After Ex Vivo Normothermic Machine Preservation: A Phase 1 (First-in-Man) Clinical Trial

Incorporation of Donor Risk Into Liver Allocation Algorithms

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