Abstract

See Articles On Pages 478 and 488 Potential conflict of interest: Nothing to report. “Man must cease attributing his problems to his environment, and learn again to exercise his will – his personal responsibility in the realm of faith and morals.”—Albert Schweitzer As the dust and acrimonious dialogue settles on the latest contentious iteration of policy expanding geographic sharing of liver allografts, we are reminded of the quotation above from the noted philosopher and physician Albert Schweitzer. Unfortunately, instead of more constructive discussion about potential solutions, we have been guilty of too much discourse over ours versus theirs and assignment of blame. The debate in its most basic form has centered on supply and demand: addressing the geographic mismatch of donors and recipients within the local environment, so that patients with similar degrees of illness have access to a liver, whether they live in Tennessee or New York or Nebraska. This reported disparity, and much of the controversy, has been based on the metric of Model for End‐Stage Liver Disease (MELD) score at transplant, or allocation Model for End‐Stage Liver Disease (aMELD) score. However, just as ecosystems have unique characteristics, interregional and intraregional variations in supply and demand also have specific attributes, such as population death rate and burden of liver disease, uneven granting of exception scores, organ procurement organization (OPO) efficiency and performance, center behavior, and competition among local transplant centers.1 Within this context, the transplant center stands as a recognized but relatively ignored and inadequately characterized component of the environment. It serves several roles, and each role has the potential to greatly affect the metric of aMELD that is stoking the fire. The first role of the transplant center is as gatekeeper for candidates on the waiting list to determine who gains access to potential offers. To the extent that patients have access to an organ ultimately reflects a center's second role: willingness to accept an organ offer. That decision is complicated by numerous variables including candidate disease severity, organ supply, level of experience of the transplant program, and activity of competing centers. That center practice varies widely, even within the same donation service area (DSA), is well recognized as illustrated by the description of the aggressive center phenotype.4 How this phenotype impacts individual candidates is relatively unknown, although recent data demonstrate that there is wide variability among centers accepting livers for their sickest patients, ranging from 15.7% to 58.1% and that center‐level decisions to decline an organ substantially increased a patient's odds of dying without a transplant.6 How center‐level variability in accepting a liver may impact patients with less severe degrees of illness has not been quantified. Another, maybe more important, question is how this practice variability between centers impacts the metrics we use to determine allocation policy. The current issue of Liver Transplantation includes 2 articles that may enhance our understanding of the role of center behavior on both access to an organ and the implications of center practice on aMELD at the center, DSA, and regional level. Using skew and kurtosis as descriptors of the distribution of aMELD to 2 recent years of national data, Croome et al. argue that these measures, whether viewed from the perspective of region, DSA, or center, provide a more informative and nuanced view of access to transplantation than just median aMELD.7 It may be presumed that centers within the same DSA would have a similar aMELD score distribution, given access to the same local donor pool. However, some DSAs had large variations with some centers transplanting patients over a wide range of MELD scores, and others with a very negatively skewed distribution. This could be interpreted in a variety of ways, but the likely explanation is that the larger, more competitive programs are more disposed to use higher‐risk organs in the lower MELD score patients resulting in a “normal” distribution, whereas the programs that are more conservative in their donor choices end up transplanting predominantly higher MELD patients. The article focuses only on aMELD and does not provide posttransplant outcomes or data on resource utilization, so we cannot fairly judge if one approach is better than the other, only that the more “aggressive” centers transplanted at a wider range of MELD scores, presumably allowing their listed patients greater access to transplantation. The second article by Wey et al. is an analysis of United Network for Organ Sharing (UNOS) data from 2016, which investigates how offer acceptance practices play a role in geographic variability in aMELD at transplant and if this magnified the effect of donor supply and demand on aMELD variability.8 The authors found that offer acceptance and donor‐to‐candidate ratios were independent contributors to geographic variability in aMELD at transplant. Importantly, the average squared difference in median MELD at transplant across DSAs was 24.6, which was reduced by approximately 15% to 20.9 after the observed variability in program‐level offer acceptance was removed. In contrast, the average squared difference in median aMELD at transplant was reduced by approximately 33% to 16.4 after the observed variability in donor‐to‐candidate ratios was removed. This analysis is notable in its emphasis on the role of transplant center and OPO in contributing to aMELD variability. We cannot forget that the “supply” part of the equation depends on the efficiency and aggressiveness of the OPO and that it is the activity of both the OPO and the center that results in a measured acceptance rate. The authors demonstrate that an increased number of donors led to lower MELD at transplant—despite center behavior, and although not indicative of causality, an increased acceptance rate and increased donor‐to‐candidate ratio was moderately associated with lower median MELD. The article challenges the prevailing presumption that geographic variability in deceased donor liver supply and demand is the underlying driver of variability in median aMELD at transplant, when in fact center‐level behavior and OPO performance must also be considered. How should these 2 articles be viewed in improving patient access to transplantation, reducing disparity, and future adjustment of organ allocation. Both reports illustrate the impact of center and OPO culture. Centers are currently judged on their 1‐year posttransplant outcomes, a very important but myopic metric which ignores the complexity and responsibility of a transplant center for the entire population it serves. Because 1‐year survival continues to improve and is relatively similar among centers, a patient's greatest risk of mortality is not posttransplant survival but in access to an organ. The Scientific Registry of Transplant Recipients (SRTR) currently provides center‐specific data on wait‐list mortality, mean MELD at transplant, and time to transplant9 but not data regarding acceptance practices. Similarly, for OPOs, the SRTR provides data on donation rates and organ yield,10 but these metrics, based on “eligible deaths,” have been criticized as not providing an accurate estimate of deceased donor potential within a DSA.3 Defining metrics of organ acceptance and turndown rates, distribution of aMELD at the center and DSA level, and expanding OPO metrics that go beyond “eligible death” criteria would be an important step in transparency. These data are important not only to patients, but useful for educating centers and OPOs about their own practice and how they compare with peers. One would think that the availability of these data will drive changes at both transplant centers and OPOs, perpetuating best practices and resulting in more organs and higher utilization, and thereby affecting not just MELD at transplant, but the number of patients receiving transplants. However, the issue is much more complex than just reporting more metrics. The size and composition of the waiting list is also subject to center practices and market incentives, which further obfuscates the landscape of the wait‐list population.5 There may be valid reasons for differences in acceptance practices, such as experience of the team, center competition, or concern for outcomes. One must be careful about how these metrics are collected, analyzed, reported, and interpreted. These 2 articles underscore the fact that we must not continue to blame only our environment or geographic location, but examine the center's and OPO's responsibility to all patients, emphasizing that the impact of center acceptance practice on aMELD in addition to donor potential and OPO performance should be considered prior to any future engagement in another round of adjustments to liver allocation policy. However, the success of an OPO in realizing donor potential relies on the willingness of their partner transplant centers to consider and retrieve those organs. Each plays an important and interconnected role and cannot operate alone. As Aristotle stated, “the whole is greater than the sum of its parts.” Ultimately, we all need to be responsible for the entire population of patients with end‐stage liver disease, a complex issue that requires significant additional consideration. The Organ Procurement and Transplantation Network/UNOS has recognized the importance of these concerns and has assembled 2 groups to address these concerns: the Ad Hoc Group for Geographic Principles and another workgroup to bring together experts to examine systems performance. We believe this is a positive step forward to better understanding the complexities of allocation across all organs. The availability of data regarding organ acceptance and donor potential will provide an important additional perspective to future organ allocation discussions and would be an essential component to enlightening practitioners and the patients who have entrusted their future to us.

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