Secondary Logo

The Importance of Outcome Metrics in Allocation Policy

Karp, Seth J., MD1

doi: 10.1097/TP.0000000000002342

1 Vanderbilt University Medical Center, Nashville, TN.

Received 21 May 2018.

Accepted 20 June 2018.

The authors declare no funding or conflicts of interest.

Correspondence: Seth Karp, MD, Division of Hepatobiliary Surgery and Liver Transplantation, Department of Surgery, Vanderbilt University, Nashville, TN. (

Subsection §121.8 (Allocation of organs) of the “final rule” states:

The Board of Directors (of the OPTN) … shall develop… policies for the equitable allocation of deceased organs among potential recipients. Such allocation policies: (2) Shall seek to achieve the best use of donated organs.

Current allocation of livers for transplantation relies primarily on the Model for End-Stage Liver Disease score. Implemented in 2002, it was designed to prioritize patients based on the risk of 3-month mortality.1 This model provides an objective measure of patient status and has been validated and refined over time,2-5 but poorly predicts posttransplant mortality.6

Use of a waiting list mortality metric to allocate organs represents a de facto determination by the OPTN that placing livers in patients with the highest short-term risk of mortality constitutes “best use of organs.” In terms of moral principles, this interpretation prioritizes fairness over utility. Importantly, no meaningful national discussion of the ethics of prioritization has been held, and it could be argued that the current algorithm produces some decisions that would not only be considered suboptimal, but perhaps even as egregious errors. For example, does “best use of organs” really prioritize a 75-year-old with well compensated hepatocellular cancer expected to gain a few years of life from a transplant over a 25-year-old with PSC who might gain 30 or more years of benefit?

The article by Bitterman and Goldberg7 in this issue of Transplantation is an important contribution to begin the discussion of placing liver allocation on a platform that incorporates utility as an essential component. They demonstrate that placing younger livers into younger recipients confers a survival advantage compared with using older donors. Conversely, placing younger donors into older recipients does not provide the same advantage. This critical observation carries profound implications for organ allocation, suggesting that “best use of organs” would involve placing younger livers into younger recipients to improve aggregate outcomes without sacrificing fairness. It will be important to further study this question to ensure a selection bias for placing older livers into younger donors does not explain the results. How these younger patients fare over a longer time period will also be of tremendous interest—the suspicion would be the mortality differences would be even more pronounced.

The transplant community has been slow to adopt principles of utility that are common practice in other fields, for example in the military and after mass casualty. These realms share a critical common theme with transplantation: the limited availability of a life-saving resource. In these other fields, the idea that the sickest should be treated first is subordinate to doing the greatest good for the greatest number. Inherent in this approach is directly grappling with the simple though uncomfortable fact that not everyone is going to survive and resources must be apportioned for aggregate benefit.

The 20th century philosopher John Rawls, in “A Theory of Justice,” sets out a system for social justice that relies on a “veil of ignorance” as a fair framework on which to decide resource allocation.8 In his analysis, distributive rules are decided on before anyone knowing their place or position in society. In this way, the likelihood of developing a fair and optimized system is maximized. Under this approach, it is clear that doing the greatest good for the greatest number would take precedence over a sickest first approach, because the chance of any individual (who does not know their ultimate position in society) doing well improves as the aggregate outcomes improve.

The concept of donor-recipient matching for livers is not a new one,9 and renal allocation reform incorporates this principle to maximize utility. Bitterman and Goldberg provide strong evidence that the liver community needs to incorporate utility into allocation decisions to satisfy the mandates of both common sense and the final rule.

Back to Top | Article Outline


1. Freeman RB Jr, Wiesner RH, Harper A, et al. The new liver allocation system: moving toward evidence-based transplantation policy. Liver Transpl. 2002;8:851–858.
2. Kamath PS, Kim WR. Advanced Liver Disease Study Group. The model for end-stage liver disease (MELD). Hepatology. 2007;45:797–805.
3. Said A, Williams J, Holden J, et al. Model for end stage liver disease score predicts mortality across a broad spectrum of liver disease. J Hepatol. 2004;40:897–903.
4. Luca A, Angermayr B, Bertolini G, et al. An integrated MELD model including serum sodium and age improves the prediction of early mortality in patients with cirrhosis. Liver Transpl. 2007;13:1174–1180.
5. Ioannou GN, Perkins JD, Carithers RL Jr. Liver transplantation for hepatocellular carcinoma: impact of the MELD allocation system and predictors of survival. Gastroenterology. 2008;134:1342–1351.
6. 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 Transplant. 2008;8:2537–2546.
7. Bitterman T, Goldberg DS. Quantifying the effect of transplanting older donor livers into younger recipients: the need for donor-recipient age matching. Transplantation. 2018;102:2033–2037.
8. Rawls J. A Theory of Justice. Cambridge, Massachusetts: Belknap Press; 1971.
9. Briceño J, Ciria R, de la Mata M. Donor-recipient matching: myths and realities. J Hepatol. 2013;58:811–820.
Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.