Liver Simulated Allocation Modeling: Were the Predictions Accurate for Share 35?

Aparna Goel, W. Ray Kim, Joshua Pyke, David P. Schladt, Bertram L. Kasiske, Jon J. Snyder, John R. Lake, Ajay K. Israni

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Background The liver simulated allocation model (LSAM) can be used to study likely effects of liver transplant allocation policy changes on organ offers, acceptance, waitlist survival, and posttransplant survival. Implementation of Share 35 in June 2013 allowed for testing how well LSAM predicted actual changes. Methods LSAM projections for 1 year of liver transplants before and after the Share 35 policy change were compared with observed data during the same period. Numbers of organs recovered, organ sharing, transplant rates, and waitlist mortality rates (per 100 waitlist years) were evaluated by LSAM and compared with observed data. Results Candidate, recipient, and donor characteristics in the LSAM cohorts were similar to those in the observed population before and after Share 35. LSAM correctly predicted more accepted organs and fewer discarded organs with Share 35. LSAM also predicted increased regional and national sharing, consistent with observed data, although the magnitude was overestimated. Transplant rates were correctly projected to increase and waitlist death rates to decrease. Conclusions Although the absolute number of transplants was underestimated and waitlist deaths overestimated, the direction of change was consistent with observed data. LSAM correctly predicted change in discarded organs, regional and national sharing, waitlist mortality, and transplants after Share 35 implementation.

Original languageEnglish (US)
Pages (from-to)769-774
Number of pages6
JournalTransplantation
Volume102
Issue number5
DOIs
StatePublished - May 1 2018

Bibliographical note

Funding Information:
This work was conducted under the support of the Minneapolis Medical Research Foundation, contractor for SRTR, as a deliverable under contract no. HHSH250201500009C (US Department of Health and Human Services, Health Resources and Services Administration, Healthcare Systems Bureau, Division of Transplantation). As a US government-sponsored work, there are no restrictions on its use. The views expressed herein are those of the authors and not necessarily those of the US Government. W.R.K. was partially supported by DK 34238/9 and AKI was partially supported by R01 HS 24527.

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