Literature DB >> 21920019

MELD Exceptions and Rates of Waiting List Outcomes.

A B Massie1, B Caffo, S E Gentry, E C Hall, D A Axelrod, K L Lentine, M A Schnitzler, A Gheorghian, P R Salvalaggio, D L Segev.   

Abstract

Model for End-stage Liver Disease (MELD)-based allocation of deceased donor livers allows exceptions for patients whose score may not reflect their true mortality risk. We hypothesized that organ procurement organizations (OPOs) may differ in exception practices, use of exceptions may be increasing over time, and exception patients may be advantaged relative to other patients. We analyzed longitudinal MELD score, exception and outcome in 88 981 adult liver candidates as reported to the United Network for Organ Sharing from 2002 to 2010. Proportion of patients receiving an HCC exception was 0-21.4% at the OPO-level and 11.9-18.8% at the region level; proportion receiving an exception for other conditions was 0.0%-13.1% (OPO-level) and 3.7-9.5 (region-level). Hepatocellular carcinoma (HCC) exceptions rose over time (10.5% in 2002 vs. 15.5% in 2008, HR = 1.09 per year, p<0.001) as did other exceptions (7.0% in 2002 vs. 13.5% in 2008, HR = 1.11, p<0.001). In the most recent era of HCC point assignment (since April 2005), both HCC and other exceptions were associated with decreased risk of waitlist mortality compared to nonexception patients with equivalent listing priority (multinomial logistic regression odds ratio [OR] = 0.47 for HCC, OR = 0.43 for other, p<0.001) and increased odds of transplant (OR = 1.65 for HCC, OR = 1.33 for other, p<0.001). Policy advantages patients with MELD exceptions; differing rates of exceptions by OPO may create, or reflect, geographic inequity. ©2011 The Authors Journal compilation
© 2011 The American Society of Transplantation and the American Society of Transplant Surgeons.

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Year:  2011        PMID: 21920019      PMCID: PMC3229963          DOI: 10.1111/j.1600-6143.2011.03735.x

Source DB:  PubMed          Journal:  Am J Transplant        ISSN: 1600-6135            Impact factor:   8.086


  19 in total

1.  Improving distribution efficiency of hard-to-place deceased donor kidneys: Predicting probability of discard or delay.

Authors:  A B Massie; N M Desai; R A Montgomery; A L Singer; D L Segev
Journal:  Am J Transplant       Date:  2010-07       Impact factor: 8.086

2.  Model for end-stage liver disease (MELD) exception guidelines: results and recommendations from the MELD Exception Study Group and Conference (MESSAGE) for the approval of patients who need liver transplantation with diseases not considered by the standard MELD formula.

Authors:  Richard B Freeman; Robert G Gish; Ann Harper; Gary L Davis; John Vierling; Leslie Lieblein; Goran Klintmalm; Jamie Blazek; Robert Hunter; Jeffrey Punch
Journal:  Liver Transpl       Date:  2006-12       Impact factor: 5.799

3.  Tutorial in biostatistics: competing risks and multi-state models.

Authors:  H Putter; M Fiocco; R B Geskus
Journal:  Stat Med       Date:  2007-05-20       Impact factor: 2.373

4.  Liver transplantation for hepatopulmonary syndrome (HPS): what is the MESSAGE?

Authors:  M J Krowka; M B Fallon
Journal:  Am J Transplant       Date:  2008-03-04       Impact factor: 8.086

5.  Effective communication of standard errors and confidence intervals.

Authors:  Thomas A Louis; Scott L Zeger
Journal:  Biostatistics       Date:  2008-06-10       Impact factor: 5.899

6.  OPTN policy regarding prioritization of patients with hepatopulmonary syndrome: does it provide equitable organ allocation?

Authors:  B M Sulieman; L G Hunsicker; D A Katz; M D Voigt
Journal:  Am J Transplant       Date:  2008-05       Impact factor: 8.086

Review 7.  Model for End Stage Liver Disease and hepatocellular carcinoma: a moving target.

Authors:  Kenneth Washburn
Journal:  Transplant Rev (Orlando)       Date:  2010-01       Impact factor: 3.943

8.  Liver transplantation in the United States, 1999-2008.

Authors:  P J Thuluvath; M K Guidinger; J J Fung; L B Johnson; S C Rayhill; S J Pelletier
Journal:  Am J Transplant       Date:  2010-04       Impact factor: 8.086

9.  The effects of DonorNet 2007 on kidney distribution equity and efficiency.

Authors:  A B Massie; S L Zeger; R A Montgomery; D L Segev
Journal:  Am J Transplant       Date:  2009-05-20       Impact factor: 8.086

Review 10.  Allocation policy for hepatocellular carcinoma in the MELD era: room for improvement?

Authors:  Kayvan Roayaie; Sandy Feng
Journal:  Liver Transpl       Date:  2007-11       Impact factor: 5.799

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  57 in total

1.  Increasing disparity in waitlist mortality rates with increased model for end-stage liver disease scores for candidates with hepatocellular carcinoma versus candidates without hepatocellular carcinoma.

Authors:  David Goldberg; Benjamin French; Peter Abt; Sandy Feng; Andrew M Cameron
Journal:  Liver Transpl       Date:  2012-04       Impact factor: 5.799

2.  Cost Effectiveness of Pre- vs Post-Liver Transplant Hepatitis C Treatment With Direct-Acting Antivirals.

Authors:  Sumeyye Samur; Brian Kues; Turgay Ayer; Mark S Roberts; Fasiha Kanwal; Chin Hur; Drew Michael S Donnell; Raymond T Chung; Jagpreet Chhatwal
Journal:  Clin Gastroenterol Hepatol       Date:  2017-06-17       Impact factor: 11.382

Review 3.  Management of hepatocellular carcinoma.

Authors:  P Fitzmorris; M Shoreibah; B S Anand; A K Singal
Journal:  J Cancer Res Clin Oncol       Date:  2014-08-27       Impact factor: 4.553

4.  Geographic Disparity in Deceased Donor Liver Transplant Rates Following Share 35.

Authors:  Mary G Bowring; Sheng Zhou; Eric K H Chow; Allan B Massie; Dorry L Segev; Sommer E Gentry
Journal:  Transplantation       Date:  2019-10       Impact factor: 4.939

5.  Reduced Access to Liver Transplantation in Women: Role of Height, MELD Exception Scores, and Renal Function Underestimation.

Authors:  Alina M Allen; Julie K Heimbach; Joseph J Larson; Kristin C Mara; W Ray Kim; Patrick S Kamath; Terry M Therneau
Journal:  Transplantation       Date:  2018-10       Impact factor: 4.939

6.  Delayed hepatocellular carcinoma model for end-stage liver disease exception score improves disparity in access to liver transplant in the United States.

Authors:  Julie K Heimbach; Ryutaro Hirose; Peter G Stock; David P Schladt; Hui Xiong; Jiannong Liu; Kim M Olthoff; Ann Harper; Jon J Snyder; Ajay K Israni; Bertram L Kasiske; W Ray Kim
Journal:  Hepatology       Date:  2015-02-24       Impact factor: 17.425

Review 7.  Are geographic differences in transplantation inherently wrong?

Authors:  Keren Ladin; Douglas W Hanto
Journal:  Curr Opin Organ Transplant       Date:  2017-04       Impact factor: 2.640

8.  Geographic disparities in liver supply/demand ratio within fixed-distance and fixed-population circles.

Authors:  Christine E Haugen; Tanveen Ishaque; Abel Sapirstein; Alexander Cauneac; Dorry L Segev; Sommer Gentry
Journal:  Am J Transplant       Date:  2019-03-18       Impact factor: 8.086

9.  Postoperative resource utilization and survival among liver transplant recipients with Model for End-stage Liver Disease score ≥ 40: A retrospective cohort study.

Authors:  Filipe S Cardoso; Constantine J Karvellas; Norman M Kneteman; Glenda Meeberg; Pedro Fidalgo; Sean M Bagshaw
Journal:  Can J Gastroenterol Hepatol       Date:  2015-05

10.  Identification of liver transplant candidates with hepatocellular carcinoma and a very low dropout risk: implications for the current organ allocation policy.

Authors:  Neil Mehta; Jennifer L Dodge; Aparna Goel; John Paul Roberts; Ryutaro Hirose; Francis Y Yao
Journal:  Liver Transpl       Date:  2013-12       Impact factor: 5.799

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