Literature DB >> 16012126

Development of the allocation system for deceased donor liver transplantation.

John M Coombes1, James F Trotter.   

Abstract

As the number of pre- and post-transplant solid organ recipients continues to grow, it becomes important for all physicians to have an understanding of the process of organ procurement and allocation. In the United States, the current system for allocation and transplantation of human solid organs has been heavily influenced by the experience in deceased donor liver transplantation (DDLT). This review highlights the significant changes that have occurred over the past 10 years in DDLT, with specific attention to the impact of the Model for Endstage Liver Disease (MELD) score on organ allocation and pre- and post-transplant survival. DDLT is managed by the United Network for Organ Sharing (UNOS) which oversees organ procurement and allocation across geographically defined Organ Procurement Organizations (OPOs). For many years, deceased donor livers were allocated to waiting list patients based on subjective parameters of disease severity and accrued waiting time. In addition, organs have traditionally been retained within the OPO where they are procured contributing to geographic disparities in disease severity at the time of transplantation among deceased donor recipients. In response to a perceived unfairness in organ allocation, Congress issued its "Final Rule" in 1998. The Rule called for a more objective ranking of waiting list patients and more parity in disease severity among transplant recipients across OPOs. To date, little progress has been made in eliminating geographic inequities. Patients in the smallest OPOs continue to receive liver transplants at a lower level of disease severity. However, strides have been made to standardize assessments of disease severity and better prioritize waiting list patients. The MELD score has emerged as an excellent predictor of short-term mortality in patients with advanced liver disease, and patients listed for liver transplantation are now ranked based on their respective MELD scores. This has improved organ access to the most severely ill patients without compromising waiting list mortality or post-transplant survival. The current system for DDLT remains imperfect but has improved significantly in the past decade. As the number of patients in need of DDLT grows, the system will continue to evolve to meet this increasing demand.

Entities:  

Mesh:

Year:  2005        PMID: 16012126      PMCID: PMC1183438          DOI: 10.3121/cmr.3.2.87

Source DB:  PubMed          Journal:  Clin Med Res        ISSN: 1539-4182


  12 in total

1.  MELD: the answer or just more questions?

Authors:  Gregory T Everson
Journal:  Gastroenterology       Date:  2003-01       Impact factor: 22.682

2.  HOMOTRANSPLANTATION OF THE LIVER IN HUMANS.

Authors:  T E STARZL; T L MARCHIORO; K N VONKAULLA; G HERMANN; R S BRITTAIN; W R WADDELL
Journal:  Surg Gynecol Obstet       Date:  1963-12

3.  A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts.

Authors:  M Malinchoc; P S Kamath; F D Gordon; C J Peine; J Rank; P C ter Borg
Journal:  Hepatology       Date:  2000-04       Impact factor: 17.425

Review 4.  A model to predict survival in patients with end-stage liver disease.

Authors:  P S Kamath; R H Wiesner; M Malinchoc; W Kremers; T M Therneau; C L Kosberg; G D'Amico; E R Dickson; W R Kim
Journal:  Hepatology       Date:  2001-02       Impact factor: 17.425

5.  The survival benefit of liver transplantation.

Authors:  Robert M Merion; Douglas E Schaubel; Dawn M Dykstra; Richard B Freeman; Friedrich K Port; Robert A Wolfe
Journal:  Am J Transplant       Date:  2005-02       Impact factor: 8.086

6.  MELD scores of liver transplant recipients according to size of waiting list: impact of organ allocation and patient outcomes.

Authors:  James F Trotter; Michael J Osgood
Journal:  JAMA       Date:  2004-04-21       Impact factor: 56.272

7.  Redrawing organ distribution boundaries: results of a computer-simulated analysis for liver transplantation.

Authors:  Richard B Freeman; Ann M Harper; Erick B Edwards
Journal:  Liver Transpl       Date:  2002-08       Impact factor: 5.799

8.  Specific laboratory methodologies achieve higher model for endstage liver disease (MELD) scores for patients listed for liver transplantation.

Authors:  James F Trotter; Brad Brimhall; Russ Arjal; Charles Phillips
Journal:  Liver Transpl       Date:  2004-08       Impact factor: 5.799

9.  Results of the first year of the new liver allocation plan.

Authors:  Richard B Freeman; Russell H Wiesner; Erick Edwards; Ann Harper; Robert Merion; Robert Wolfe
Journal:  Liver Transpl       Date:  2004-01       Impact factor: 5.799

10.  Model for end-stage liver disease (MELD) and allocation of donor livers.

Authors:  Russell Wiesner; Erick Edwards; Richard Freeman; Ann Harper; Ray Kim; Patrick Kamath; Walter Kremers; John Lake; Todd Howard; Robert M Merion; Robert A Wolfe; Ruud Krom
Journal:  Gastroenterology       Date:  2003-01       Impact factor: 22.682

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  16 in total

1.  Non-parametric estimation of a time-dependent predictive accuracy curve.

Authors:  P Saha-Chaudhuri; P J Heagerty
Journal:  Biostatistics       Date:  2012-06-25       Impact factor: 5.899

2.  Impact of donor and recipient race on survival after hepatitis C-related liver transplantation.

Authors:  Jennifer E Layden; Scott J Cotler; Shellee A Grim; Michael J Fischer; Michael R Lucey; Nina M Clark
Journal:  Transplantation       Date:  2012-02-27       Impact factor: 4.939

3.  Who should undergo liver transplantation for hepatocellular carcinoma? Ablate, wait … and see!

Authors:  Willscott E Naugler; Barry Schlansky; Susan L Orloff
Journal:  Hepat Oncol       Date:  2014-03-20

4.  Clinical usefulness of international normalized ratio calibration of prothrombin time in patients with chronic liver disease.

Authors:  Jun Hyung Lee; Oh Joo Kweon; Mi-Kyung Lee; Hyun Woong Lee; Hyung Joon Kim; Hye Ryoun Kim
Journal:  Int J Hematol       Date:  2015-06-12       Impact factor: 2.490

Review 5.  Liver Allocation Policies in the USA: Past, Present, and the Future.

Authors:  Anjana Pillai; Thomas Couri; Michael Charlton
Journal:  Dig Dis Sci       Date:  2019-04       Impact factor: 3.199

Review 6.  Liver transplantation organ allocation between Child and MELD.

Authors:  Ivo Graziadei
Journal:  Wien Med Wochenschr       Date:  2006-07

Review 7.  Liver Transplantation in India: At the Crossroads.

Authors:  Sanjay Nagral; Aditya Nanavati; Aabha Nagral
Journal:  J Clin Exp Hepatol       Date:  2015-11-12

8.  D-MELD risk capping improves post-transplant and overall mortality under markov microsimulation.

Authors:  Jeffrey B Halldorson; Robert L Carithers; Renuka Bhattacharya; Ramasamy Bakthavatsalam; Iris W Liou; Andre A Dick; Jorge D Reyes; James D Perkins
Journal:  World J Transplant       Date:  2014-09-24

Review 9.  A Tutorial on Evaluating the Time-Varying Discrimination Accuracy of Survival Models Used in Dynamic Decision Making.

Authors:  Aasthaa Bansal; Patrick J Heagerty
Journal:  Med Decis Making       Date:  2018-10-14       Impact factor: 2.583

10.  Impact of estimated liver volume and liver weight on gender disparity in liver transplantation.

Authors:  Ayse L Mindikoglu; Sukru H Emre; Laurence S Magder
Journal:  Liver Transpl       Date:  2012-12-12       Impact factor: 5.799

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