Year 2018 / Volume 110 / Number 12
Original
Graft survival after liver transplantation: an approach to a new Spanish risk index

782-793

DOI: 10.17235/reed.2018.5473/2018

Juan José Araiz Burdio, María Trinidad Serrano Aulló, Agustín García Gil, Ana Pascual Bielsa, Alberto Lue, Sara Lorente Pérez, Beatriz Villanueva Anadón, Miguel Ángel Suárez Pinilla,

Abstract
Introduction: several indicators are available to assess liver graft survival, including the American DRI and the European ET-DRI. However, there are significant differences between transplant programs of different countries, and the previously mentioned indicators might be not valid in our setting. Objectives: the aim of the study was to describe a new national liver graft risk indicator based on the results obtained from the Registro Español de Trasplante Hepático (RETH) and to validate the DRI and ET-DRI indicators. Methods: the RETH includes a Cox analysis of factors associated with graft survival; the graft risk index (GRI) indicator was defined based on these results. The variables considered are dependent upon the donation conditions (age, cause of death, blood compatibility and cold ischemia time) and the transplant recipient (age, underlying disease, hepatitis C virus, transplant number, UNOS status and surgical technique). A logistic regression curve was obtained and graft survival curves were calculated by stratification. Precision was assessed using the ROC analysis. Results: a GRI of 1 represents a probability of graft loss of 23.25%; each point increase in the GRI score multiplies this probability by 1.33. The best discrimination of GRI was obtained by stratification. The DRI ROC area was 0.54 (95% CI, 0.50-0.59) and the ET-DRI ROC area was 0.56 (95% CI, 0.51-0.61), compared to 0.70 (95% CI, 0.65-0.73) (p < 0.0001) for the GRI. Conclusions: both the DRI and ET-DRI do not seem to be useful in our setting. Hence a national indicator is more desirable. The GRI requires a national study in order to further streamline and assess this indicator.
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References
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Desai NM, Mange KC, Crawford MD, et al. Predicting outcome after liver transplantation: utility of the Model for End-stage Liver Disease and a newly derived discrimination function. Transplantation 2004;77:99-106.
Ioannou GN. Development and Validation of a Model Predicting Graft Survival After Liver Transplantation. Liver Tranpl 2006;12:1594-1606.
Feng S, Goodrich NP, Bragg-Gresham JL, et al. Characteristics associated with liver graft failure: the concept of a Donor Risk Index. Am J Transplant 2006;6:783-790.
Rana A, Hardy MA, Halazun KJ, et al. Survival Outcomes Following Liver Transplantation (SOFT) score: a novel method to predict patient survival following liver transplantation. Am J Transpl 2008;8:2537-2546.
Halldorson JB, Bakthavatsalam R, Fix O, et al. D-MELD, a simple predictor of post liver transplant mortality for optimization of donor/recipient Matching. Am J Transpl 2009;9:318-326.
Dutkowski P, MD, Oberkofler CE, Slankamenac K, et al There Better Guidelines for Allocation in Liver Transplantation?. A Novel Score Targeting Justice and Utility in the Model for End-Stage Liver Disease Era. Ann Surg 2011;254:745-753.
Braat AE, Blok JJ, Putter H, et al. The Eurotransplant Donor Risk Index in Liver Transplantation: ET-DRI. Am J Transpl 2012;12:2789-2796.
Briceño J, Cruz-Ramírez M, Prieto M, et al. Use of artificial intelligence as an innovative donor-recipient matching model for liver transplantation: Results from a multicenter Spanish study. J Hepatology 2014;61:1020-1028.
Lau L, Kankanige Y, Rubinstein B, et al. Machine-Learning algorithms predict graft failure after liver transplantation. Transplantation 2017;101:e125-e132.
Collett D, Friend PJ, Watson CJE. Factors associated with short- and long-term liver graft survival in the United Kingdom: development of a UK Donor Liver Index. Transplantation 2017;101:786-792.
Memoria de Resultados del Registro Español de Trasplante Hepático. Disponible en: http://www.sethepatico.org.
Winter A, Féray C, Audureau E, et al. External validation of the Donor Risk Index and the Eurotransplant Donor Risk Index on the French liver transplantation registry. Liver Int 2017;00:1-10.
Gonzalez FX, Rimola A, Grande L, et al. Predictive factors of early postoperative graft function in human liver transplantation. Hepatology 1994;20:565-573.
Sirivatanauksorn Y, Taweerutchana V, Limsrichamrern S, et al. Analysis of Donor Risk Factors Associated With Graft Outcomes in Orthotopic Liver Transplantation. Transplant Proc 2012;44:320-323.
Al-Freah MAB, McPhail MJW, Dionigi E, et al. Improving the diagnostic criteria for primary liver graft nonfunction in adults utilizing standard and transportable laboratory parameters: an outcome-based analysis. Am J Transplant 2017;17:1255-1266.
Grat M, Wronka KM, Patkowski W, et al. Effects of Donor Age and Cold Ischemia on Liver Transplantation Outcomes According to the Severity of Recipient Status. Dig Dis Sci 2016;61:626-635.
Schlegel A, Linecker M, Kron P, et al. Risk Assessment in High- and Low-MELD Liver Transplantation. Am J Transpl 2017;17:1050-1063.
Schoening W, Helbig M, Buescher N, et al. Eurotransplant donor-risk-index and recipient factors: influence on long-term outcome after liver transplantation – A large single-center experience. Clin Transplant 2016;30:508-517.
Araiz JJ, Serrano MT, Garcia-Gil FA, et al. Intention-to-treat survival analysis of Hepatitis C Virus/Human Immunodeficiency Cirus Coinfected Liver Transplant: Is it the waiting list?. Liver Transpl 2016;22:1187-1196.
Ayllón MD, Ciria R, Cruz-Ramírez M, et al. Validation of artificial neural networks as a methodology for donor recipient matching for liver transplantation. Liver Transpl. 2017. DOI: 10.1002/lt.24870.
Brown RS, Kumar KS, Russo MW, et al. Model for End-Stage Liver Disease and Child-TurcottePugh Score as Predictors of Pretransplantation Disease Severity, Posttransplantation Outcome, and Resource Utilization in United Network for Organ Sharing Status 2A Patients. Liver Transpl 2002;8:278-284.
Desai NM, Mange KC, Crawford MD, et al. Predicting outcome after liver transplantation: utility of the Model for End-stage Liver Disease and a newly derived discrimination function. Transplantation 2004;77:99-106.
Ioannou GN. Development and Validation of a Model Predicting Graft Survival After Liver Transplantation. Liver Tranpl 2006;12:1594-1606.
Feng S, Goodrich NP, Bragg-Gresham JL, et al. Characteristics associated with liver graft failure: the concept of a Donor Risk Index. Am J Transplant 2006;6:783-790.
Rana A, Hardy MA, Halazun KJ, et al. Survival Outcomes Following Liver Transplantation (SOFT) score: a novel method to predict patient survival following liver transplantation. Am J Transpl 2008;8:2537-2546.
Halldorson JB, Bakthavatsalam R, Fix O, et al. D-MELD, a simple predictor of post liver transplant mortality for optimization of donor/recipient Matching. Am J Transpl 2009;9:318-326.
Dutkowski P, MD, Oberkofler CE, Slankamenac K, et al There Better Guidelines for Allocation in Liver Transplantation?. A Novel Score Targeting Justice and Utility in the Model for End-Stage Liver Disease Era. Ann Surg 2011;254:745-753.
Braat AE, Blok JJ, Putter H, et al. The Eurotransplant Donor Risk Index in Liver Transplantation: ET-DRI. Am J Transpl 2012;12:2789-2796.
Briceño J, Cruz-Ramírez M, Prieto M, et al. Use of artificial intelligence as an innovative donor-recipient matching model for liver transplantation: Results from a multicenter Spanish study. J Hepatology 2014;61:1020-1028.
Lau L, Kankanige Y, Rubinstein B, et al. Machine-Learning algorithms predict graft failure after liver transplantation. Transplantation 2017;101:e125-e132.
Collett D, Friend PJ, Watson CJE. Factors associated with short- and long-term liver graft survival in the United Kingdom: development of a UK Donor Liver Index. Transplantation 2017;101:786-792.
Memoria de Resultados del Registro Español de Trasplante Hepático. Disponible en: http://www.sethepatico.org.
Winter A, Féray C, Audureau E, et al. External validation of the Donor Risk Index and the Eurotransplant Donor Risk Index on the French liver transplantation registry. Liver Int 2017;00:1-10.
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Sirivatanauksorn Y, Taweerutchana V, Limsrichamrern S, et al. Analysis of Donor Risk Factors Associated With Graft Outcomes in Orthotopic Liver Transplantation. Transplant Proc 2012;44:320-323.
Al-Freah MAB, McPhail MJW, Dionigi E, et al. Improving the diagnostic criteria for primary liver graft nonfunction in adults utilizing standard and transportable laboratory parameters: an outcome-based analysis. Am J Transplant 2017;17:1255-1266.
Grat M, Wronka KM, Patkowski W, et al. Effects of Donor Age and Cold Ischemia on Liver Transplantation Outcomes According to the Severity of Recipient Status. Dig Dis Sci 2016;61:626-635.
Schlegel A, Linecker M, Kron P, et al. Risk Assessment in High- and Low-MELD Liver Transplantation. Am J Transpl 2017;17:1050-1063.
Schoening W, Helbig M, Buescher N, et al. Eurotransplant donor-risk-index and recipient factors: influence on long-term outcome after liver transplantation – A large single-center experience. Clin Transplant 2016;30:508-517.
Araiz JJ, Serrano MT, Garcia-Gil FA, et al. Intention-to-treat survival analysis of Hepatitis C Virus/Human Immunodeficiency Cirus Coinfected Liver Transplant: Is it the waiting list?. Liver Transpl 2016;22:1187-1196.
Ayllón MD, Ciria R, Cruz-Ramírez M, et al. Validation of artificial neural networks as a methodology for donor recipient matching for liver transplantation. Liver Transpl. 2017. DOI: 10.1002/lt.24870.
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Araiz Burdio J, Serrano Aulló M, García Gil A, Pascual Bielsa A, Lue A, Lorente Pérez S, et all. Graft survival after liver transplantation: an approach to a new Spanish risk index. 5473/2018


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Publication history

Received: 16/01/2018

Accepted: 23/05/2018

Online First: 03/09/2018

Published: 03/12/2018

Article revision time: 121 days

Article Online First time: 230 days

Article editing time: 321 days


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