Literature DB >> 27490411

Predicting Outcomes on the Liver Transplant Waiting List in the United States: Accounting for Large Regional Variation in Organ Availability and Priority Allocation Points.

Allyson Hart1, David P Schladt, Jessica Zeglin, Joshua Pyke, W Ray Kim, John R Lake, John P Roberts, Ryutaro Hirose, David C Mulligan, Bertram L Kasiske, Jon J Snyder, Ajay K Israni.   

Abstract

BACKGROUND: The probability of liver transplant and death on the waiting list in the United States varies greatly by donation service area (DSA) due to geographic differences in availability of organs and allocation of priority points, making it difficult for providers to predict likely outcomes after listing. We aimed to develop an online calculator to report outcomes by region and patient characteristics.
METHODS: Using the Scientific Registry of Transplant Recipients database, we included all prevalent US adults aged 18 years or older waitlisted for liver transplant, examined on 24 days at least 30 days apart over a 2-year period. Outcomes were determined at intervals of 30 to 365 days. Outcomes are reported by transplant program, DSA, region, and the nation for comparison, and can be shown by allocation or by laboratory model for end-stage liver disease (MELD) score (6-14, 15-24, 25-29, 30-34, 35-40), age, and blood type.
RESULTS: Outcomes varied greatly by DSA; for candidates with allocation MELD 25-29, the 25th and 75th percentiles of liver transplant probability were 30% and 67%, respectively, at 90 days. Corresponding percentiles for death or becoming too sick to undergo transplant were 5% and 9%. Outcomes also varied greatly for candidates with and without MELD exception points.
CONCLUSIONS: The waitlist outcome calculator highlights ongoing disparities in access to liver transplant and may assist providers in understanding and counseling their patients about likely outcomes on the waiting list.

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Year:  2016        PMID: 27490411      PMCID: PMC5369025          DOI: 10.1097/TP.0000000000001384

Source DB:  PubMed          Journal:  Transplantation        ISSN: 0041-1337            Impact factor:   4.939


  24 in total

1.  Organ Procurement and Transplantation Network--HRSA. Final rule with comment period.

Authors: 
Journal:  Fed Regist       Date:  1998-04-02

2.  OPTN/SRTR 2013 Annual Data Report: liver.

Authors:  W R Kim; J R Lake; J M Smith; M A Skeans; D P Schladt; E B Edwards; A M Harper; J L Wainright; J J Snyder; A K Israni; B L Kasiske
Journal:  Am J Transplant       Date:  2015-01       Impact factor: 8.086

Review 3.  Scientific Registry of Transplant Recipients: collecting, analyzing, and reporting data on transplantation in the United States.

Authors:  Susan Leppke; Tabitha Leighton; David Zaun; Shu-Cheng Chen; Melissa Skeans; Ajay K Israni; Jon J Snyder; Bertram L Kasiske
Journal:  Transplant Rev (Orlando)       Date:  2013-03-06       Impact factor: 3.943

Review 4.  Evidence-based risk communication: a systematic review.

Authors:  Daniella A Zipkin; Craig A Umscheid; Nancy L Keating; Elizabeth Allen; KoKo Aung; Rebecca Beyth; Scott Kaatz; Devin M Mann; Jeremy B Sussman; Deborah Korenstein; Connie Schardt; Avishek Nagi; Richard Sloane; David A Feldstein
Journal:  Ann Intern Med       Date:  2014-08-19       Impact factor: 25.391

5.  Early changes in liver distribution following implementation of Share 35.

Authors:  A B Massie; E K H Chow; C E Wickliffe; X Luo; S E Gentry; D C Mulligan; D L Segev
Journal:  Am J Transplant       Date:  2015-03       Impact factor: 8.086

6.  A comparison of liver transplantation outcomes in the pre- vs. post-MELD eras.

Authors:  F Kanwal; G S Dulai; B M R Spiegel; H F Yee; I M Gralnek
Journal:  Aliment Pharmacol Ther       Date:  2005-01-15       Impact factor: 8.171

Review 7.  Patient selection in an era of donor liver shortage: current US policy.

Authors:  Russell H Wiesner
Journal:  Nat Clin Pract Gastroenterol Hepatol       Date:  2005-01

Review 8.  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

9.  Following the organ supply: assessing the benefit of inter-DSA travel in liver transplantation.

Authors:  Nino Dzebisashvili; Allan B Massie; Krista L Lentine; Mark A Schnitzler; Dorry Segev; Janet Tuttle-Newhall; Sommer Gentry; Richard Freeman; David A Axelrod
Journal:  Transplantation       Date:  2013-01-27       Impact factor: 4.939

10.  Differences in access to liver transplantation: disease severity, waiting time, and transplantation center volume.

Authors:  Jawad Ahmad; Cindy L Bryce; Thomas Cacciarelli; Mark S Roberts
Journal:  Ann Intern Med       Date:  2007-05-15       Impact factor: 25.391

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  11 in total

1.  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

2.  Tool to Aid Patients in Selecting a Liver Transplant Center.

Authors:  Cory R Schaffhausen; Marilyn J Bruin; Sauman Chu; Helen Fu; Warren T McKinney; David Schladt; Jon J Snyder; W Ray Kim; Jack R Lake; Bertram L Kasiske; Ajay K Israni
Journal:  Liver Transpl       Date:  2020-03       Impact factor: 5.799

3.  What patients and members of their support networks ask about transplant program data.

Authors:  Cory R Schaffhausen; Marilyn J Bruin; Daryl Chesley; Maureen McBride; Jon J Snyder; Bertram L Kasiske; Ajay K Israni
Journal:  Clin Transplant       Date:  2017-10-23       Impact factor: 2.863

4.  Ethnic and Age Disparities in Outcomes Among Liver Transplant Waitlist Candidates.

Authors:  Margaux N Mustian; Brittany A Shelton; Paul A MacLennan; Rhiannon D Reed; Jared A White; Devin E Eckhoff; Jayme E Locke; Richard M Allman; Stephen H Gray
Journal:  Transplantation       Date:  2019-07       Impact factor: 4.939

5.  Impact of Payer Status on Delisting Among Liver Transplant Candidates in the United States.

Authors:  Krystal L Karunungan; Yas Sanaiha; Roland A Hernandez; Holly Wilhalme; Sarah Rudasill; Joseph Hadaya; Joseph DiNorcia; Peyman Benharash
Journal:  Liver Transpl       Date:  2020-12-31       Impact factor: 5.799

6.  Predicting chance of liver transplantation for pediatric wait-list candidates.

Authors:  Xun Luo; Douglas B Mogul; Allan B Massie; Tanveen Ishaque; John F P Bridges; Dorry L Segev
Journal:  Pediatr Transplant       Date:  2019-07-16

7.  Engineered Liver Tissue Culture in an In Vitro Tubular Perfusion System.

Authors:  Guang Yang; Bhushan Mahadik; Trevor Mollot; Julia Pinsky; Athenia Jones; Alexis Robinson; Daniel Najafali; Daniel Rivkin; Jenny Katsnelson; Charlotte Piard; John P Fisher
Journal:  Tissue Eng Part A       Date:  2020-11-24       Impact factor: 3.845

8.  Use of Telehealth Expedites Evaluation and Listing of Patients Referred for Liver Transplantation.

Authors:  Binu V John; Eleanor Love; Bassam Dahman; Nargiza Kurbanova; Venkata Rajesh Konjeti; Latha Thankam Sundaram; Yangyang Deng; Sean Aubuchon; Douglas Heuman; Jasmohan S Bajaj; Hochong Gilles; Michael Chang; Rehan Qayyum; Mohammad S Siddiqui
Journal:  Clin Gastroenterol Hepatol       Date:  2019-12-27       Impact factor: 11.382

9.  Comparing Pretransplant and Posttransplant Outcomes When Choosing a Transplant Center: Focus Groups and a Randomized Survey.

Authors:  Cory R Schaffhausen; Marilyn J Bruin; Sauman Chu; Andrew Wey; Warren T McKinney; Jon J Snyder; Jack R Lake; Arthur J Matas; Bertram L Kasiske; Ajay K Israni
Journal:  Transplantation       Date:  2020-01       Impact factor: 5.385

10.  Evaluation Within 30 Days of Referral for Liver Transplantation is Associated with Reduced Mortality: A Multicenter Analysis of Patients Referred Within the VA Health System.

Authors:  Binu V John; Kaley Schwartz; Andrew R Scheinberg; Bassam Dahman; Seth Spector; Yangyang Deng; David Goldberg; Paul Martin; Tamar H Taddei; David E Kaplan
Journal:  Transplantation       Date:  2022-01-01       Impact factor: 5.385

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