Share this article on:

Geographic Disparity in Liver Allocation: Time to Act or Have Others Act for Us

Massie, Allan B. PhD, MHS1,2; Roberts, John Paul MD3

doi: 10.1097/TP.0000000000001993

The authors challenge the proposal for concentric neighborhoods for distribution of donated livers as yet another delaying tactic in the process of relieving disparity in access for liver transplantation.

1 Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD.

2 Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD.

3 Department of Surgery, University of California, San Francisco, CA.

Received 16 September 2017. Revision received 17 October 2017.

Accepted 20 October 2017.

The authors declare no funding or conflicts of interest.

A. Massie and J. Roberts both participated in manuscript writing and revision.

Correspondence: John P. Roberts, MD, Box 0780, 505 Parnassus, San Francisco, CA 94143. (

The Final Rule, implemented in 2000, directs the Organ Procurement and Transplantation Network to “distribute organs over as broad a geographic area as feasible” and to ensure that allocation priority “shall not be based on a candidate's place of listing.”1 However, substantial geographic disparity in access to liver transplantation among waitlisted patients indicates that the transplant community has failed to comply with this directive.2,3

In a new article, Mehrotra and colleagues4 propose a suite of potential modifications to the existing allocation regime, with the goal of alleviating this geographic disparity. The proposed framework (called “concentric neighborhoods”) features broader sharing at low model of end-stage liver disease (MELD) scores (replacing the current MELD-15 threshold with MELD-18 or MELD-20) and places each donor service area (DSA) within a “concentric neighborhood” of adjacent and nearby DSAs within a specified radius. In some variants, “proximity points” grant local candidates higher allocation priority than nonlocal candidates in the same DSA or region.

Several previous proposals have been made by the same research group and others.5,6 A notable feature of the “concentric neighborhoods” framework is its flexibility: various tunable parameters (eg, size of the neighborhood, value of proximity points) create a system through which policymakers could, in principle, balance trade-offs (eg, reduced geographic disparity vs the shock of sudden volume loss to centers, which currently benefit from that disparity) with a high degree of precision.

However, some caution is warranted. The authors use a simulation tool (LivSim) of their own design, different from the Scientific Registry of Transplant Recipients–produced kidney/pancreas-simulated allocation model and liver-simulated allocation model, which have been the basis for previous allocation changes. The authors are to be commended for making LivSim open-source, meaning that other researchers will be able to study the tool, to understand its strengths and weaknesses to a greater degree than possible from the manuscript alone, and potentially to improve it. However, as with all simulation studies, there is no guarantee that reality will match the assumptions of the underlying model.7 The concentric neighborhoods framework carefully balances a “yang” of broader sharing (moving from Share-15 to Share-18 or 20, incorporating multiple organ procurement organization (OPO) neighborhoods) with a “yin” of mechanisms specifically designed to attenuate sharing (proximity boosts). If the proximity-boost mechanism turns out to have greater impact than predicted, then some permutations of concentric neighborhoods could actually increase geographic disparity.

Regardless, there is one indisputable finding in all the models tested to date: to decrease geographic disparity, more organs need to move beyond the current geographic boundaries. This finding is what drives the heated passions which split the transplant community. To understand the temperature of the passion, if one considers some measures of the fairness of access to organs, there will be a median at which half of the centers and their patients have better access while the other half has not. The further from the median, the hotter the passion. The current model caters to moderating this passion by the novel metric, “maximum loss of transplant volumes by DSA,” which is a measure of the shift of organs across geographic boundaries. The goal then is to minimize the “maximum loss of transplant volumes” while maximizing the change in fairness to allow acceptance by the community. Although this may bring peace to the 75th percentile, the remaining 25% who have the most to lose will continue pouring oil from the ramparts.

As the overall goal is to make the system fairer for patients, a noble desire, those who oppose change have a fundamental problem, opposition to a fair system, therefore need to rely a standard disinformation strategy: fear, uncertainty, and doubt (FUD) to cloud the argument. The overall goal of the FUD is to delay by asking for completion of Herculean tasks: further study, additional models, and the like. Although the list of FUD is lengthy, currently sowing FUD about relative OPO performance is popular. It is proposed that poor OPO performance is the cause of the geographic disparity and somehow is the fault of the patients without access to transplant. Although improvement in OPO performance is a worthy goal and tens of millions of dollars and tremendous societal effort has been expended to improve performance, relying on improved OPO performance alone is not reasonable. Opponents warn against “rewarding poor-performing OPOs.” But by failing to act, the transplant community punishes not OPOs themselves but dying patients who have the misfortune to live in the wrong place.

Opponents also sow FUD through concerns about impact of change on certain classes of disadvantaged patients. But patients from marginalized groups exist in all parts of the country, and the current system condemns many such patients to the additional burden of geographic disparity. Another argument is that waitlist-based metrics of disparity fail to account for barriers to waitlisting. But the way to help patients not on the waitlist is to list them—not to privilege other more fortunate patients who happen to live in the same DSA.

This is not the first time that the community has focused on the disparity in access to liver transplantation. In the 1990s, the same topic triggered the “liver wars.”8 During the mayhem, 2 states basically withdrew from the liver allocation system and decreed that there would be local use to satisfy the needs of their residents. Because of the controversy surrounding the Final Rule issued by US Department of Health and Human Services, Congress declared a 1-year moratorium on the institution of the regulations and commissioned an Institute of Medicine report9 so that a neutral party could examine the controversy and evaluate the proposed changes in organ allocation.

It is our opinion that the transplant community will once again need a neutral arbitrator of the controversy. If the transplant community is unable to agree on a solution, the degree of passion may lead us once again to a fight that ends up in Congress, perhaps resulting in change that the community could not bring to itself.

Back to Top | Article Outline


1. Axelrod DA, Vagefi PA, Roberts JP. The evolution of organ allocation for liver transplantation. Tackling geographic disparity through broader sharing. Ann Surg. 2015;262:224–227.
2. Yeh H, Smoot E, Schoenfeld DA, et al. Geographic inequity in access to livers for transplantation. Transplantation. 2011;91:479–486.
3. Massie AB, Caffo B, Gentry SE, et al. MELD exceptions and rates of waiting list outcomes. Am J Transplant. 2011;11:2362–2371.
4. Mehrotra R, Kliambi V, Bui K, et al. A concentric-neighborhoods solution to disparity in liver access based that contains current UNOS districts. Transplatation. 2018;102:263–286.
5. Kilambi V, Mehrotra S. Improving liver allocation using optimized neighborhoods. Transplantation. 2017;101:350–359.
6. Gentry SE, Massie AB, Cheek SW, et al. Addressing geographic disparities in liver transplantation through redistricting. Am J Transplant. 2013;13:2052–2058.
7. Massie AB, Chow EK, Segev DL. Virtual populations, real decisions: making sense of stochastic simulation studies. Transplantation. 2015;99:901–902.
8. Changing the US transplant system. Lancet. 1998;352:79.
9. Institute of Medicine (US) Committee on Organ Procurement and Transplantation Policy. Organ Procurement and Transplantation: Assessing Current Policies and the Potential Impact of the DHHS Final Rule. Washington, DC: National Academies Press (US); 1999.
Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.