New Organ Allocation Policy in Liver Transplantation in the United States

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1 REVIEW New Organ Allocation Policy in Liver Transplantation in the United States David A. Goldberg, M.D., M.S.C.E.,*,, Richard Gilroy, and Michael Charlton, MD., F.R.C.P. The number of potential recipients who would benefit from being able to undergo liver transplantation is much greater than the supply of donated organs. Eight people die every day waiting for a liver transplant in the United States. The current organ allocation system, which prioritizes patients primarily according to Model for End-Stage Liver Disease (MELD) score, is intended to direct organs to the sickest patients first. Wide geographic variations in availability of donor organs, the burden of liver disease, and population served, each of which has a multifactorial basis, have resulted in similarly wide variations in MELD score at transplant and likelihood of dying while waiting for a liver transplant. New allocation and distribution policies are under development that will reduce the geographic disparity in access to liver transplantation. CURRENT DONOR LIVER ORGAN ALLOCATION SYSTEM The increasingly excellent outcomes and the increasing number of patients who might benefit from liver transplantation has produced a chronic shortage of donor organs for liver transplantation, with approximately one in six patients dying on the waitlist per year. Allocating Abbreviations: DSA, donor service area; MELD, Model for End-Stage Liver Disease; OPO, Organ Procurement Organization; OPTN, Organ Procurement and Transplant Network; PELD, Pediatric End-Stage Liver Disease; UNOS, United Network for Organ Sharing. From the *Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, and Intermountain Transplant and Regenerative Medicine Institute, Intermountain Medical Center, Murray, UT. The content is the responsibility of the authors alone and does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Potential conflict of interest: Nothing to report. Received 6 July 2016; accepted 2 August 2016 Contract grant sponsor: National Institutes of Health; contract grant number: K08 DK A1 (to D.A.G.). Contract grant sponsor: Health Resources and Services Administration; contract grant number: C. View this article online at wileyonlinelibrary.com VC 2016 by the American Association for the Study of Liver Diseases 108 CLINICAL LIVER DISEASE, VOL 8, NO 4, OCTOBER 2016 An Official Learning Resource of AASLD

2 organs for liver transplantation in a manner that maximizes their impact while ensuring equitable access has been a challenge since the passage of National Organ Transplant Act and the creation of the Organ Procurement and Transplant Network (OPTN), the contract for which is and has always been held by the United Network for Organ Sharing (UNOS). The OPTN in the United States is currently divided into geographic donor service areas (DSAs), each of which is served by a federally designated organization termed an Organ Procurement Organization (OPO). It is the charge of the OPO to identify and medically manage donors within the DSA, to organize the recovery of the organs, and to allocate them according to the priorities of the waitlist. DSAs vary in size and population and are aggregated into larger areas defined by the 11 OPTN regions. The populations of the DSAs vary from 1.4 to 19.6 million. 1 The geographic boundaries of the DSAs are generally a historical legacy and may represent one county, an entire state, or groups of states. All the candidates awaiting transplantation belonging to one or more transplant centers within the DSA are considered local and traditionally have been awarded priority over patients from other DSAs and OPTN regions. The current allocation system for livers is intended to allocate organs on the principle of sickest first and prioritizes organ allocation primarily on the basis of MELD score, a numerical scale, ranging from 6 to 40, used for liver transplant candidates aged 12 years or older. MELD scores are calculated using a formula that incorporates three routine laboratory values: bilirubin, international normalized ratio (derived from prothrombin time), and serum creatinine. 2 MELD scores (currently adjusted for serum sodium levels, MELD-Na) have been shown to be an accurate means of ranking patients on the transplant waiting list in order of their short-term risk for death. When a deceased liver donor has been identified, after excluding transplant candidates who are not compatible with a particular donor (e.g., based on blood type, height, and weight), the donated organ is offered to potential recipients on a match run in which candidates are prioritized according to: (1) the donor s age, (2) medical urgency, and (3) recipient s geographical proximity to the donor. Geographical priority is greatest for local waitlisted patients, defined by the OPO s service area, followed by regional and then national waitlisted candidates. The rationale for local priority is to limit costs and logistics associated with transportation, to limit ischemic times for the donated organs, and to create incentives for local communities to support organ donation. Livers from adult donors are allocated first to the most urgent candidates located in the same region as the donor (candidates with sudden catastrophic liver failure: Status 1A for adults and 1B for children), followed by candidates within the same blood type in order of MELD score. MELD scores can be derived either entirely from laboratory values or assigned through exceptions. MELD exception scores are used when patients have liver diseases or related conditions that are believed to confer a risk for mortality or other basis of medical urgency that is not reflected in MELD scores derived from laboratory values; examples include hepatocellular carcinoma, hepatopulmonary syndrome, and polycystic liver disease. There were 13,116 requests for MELD exceptions in 2014, most commonly (60%) for hepatocellular carcinoma. In 2013 the allocation sequence was changed to provide broader access to patients with MELD scores 35 through a sharing mandate. In this system, after regional Status 1 candidates, livers are offered to, in order of priority: Candidates with MELD/Pediatric End-Stage Liver Disease (PELD) scores 35 within the donor s region, with offers first made locally, then regionally (i.e., local 40, regional 40, local 39, regional 39, etc.). Local candidates with scores greater than 15. Regional candidates with scores greater than 15. National candidates in Status 1. National candidates with scores greater than 15. Candidates with scores less than 15 locally, regionally, then nationally. Although achieving modest success in some regards (e.g. increasing access to organs for patients with MELD scores 35), this system exacerbated the interregional variations in MELD score at the time of organ allocation, increased travel costs, and produced only a small decrease in waiting list mortality. 3,4 CHALLENGES IN ORGAN ALLOCATION There are several important ongoing challenges and limitations to current organ allocation and distribution policy. These include: 1. Geographic disparity in donor organ supply. 2. Limitations of MELD/MELD-Na (e.g., relative insensitivity of serum creatinine, and thus MELD score, to deteriorating 109 CLINICAL LIVER DISEASE, VOL 8, NO 4, OCTOBER 2016 An Official Learning Resource of AASLD

3 FIG 1 (A) Variation by UNOS region in median allocation MELD score (average MELD scores at time of transplantation regardless of whether laboratory value based or assigned through exception points) at transplant for all adult deceased-donor liver transplant recipients, (B) Variation by UNOS region in median laboratory MELD score (average based solely on MELD scores derived from serum total bilirubin, international normalized ratio, and creatinine) at transplant for all adult deceased-donor liver transplant recipients, (C) Variation by UNOS region in percentage of liver transplant recipients with exception points at transplant for all adult deceased-donor liver transplant recipients, renal function in women; lack of reflection of rate of change in MELD score; lack of predictivity for utility). 3. Inconsistent and high frequency of assignment of MELD scores that are not based on laboratory values, both as standard (e.g., hepatocellular carcinoma) and nonstandard (e.g., because of severe ascites or persistent gastrointestinal blood loss) exception MELD points. 4. Wide variations in center-specific practices (e.g., utilization of donation after cardiac death and elderly donors). 5. Balancing efficacy with utility and cost. Variations in size and demographics between DSAs create disparities in supply and demand that can be substantial between neighboring OPOs and are discernible between UNOS regions (Fig. 1). Minimization in geographic variations in access to liver (and other organ) transplantation is an ongoing priority for the Health Resources and Services Administration, which funds and oversees UNOS. Because the MELD score required to receive a transplant varies dramatically across the United States, 5 UNOS is considering proposals to redraw organ distribution maps to normalize MELD scores at transplantation. 6 Waitlist data reporting geographic differences in waitlist mortality and transplant rates cite variability in organ availability as the root cause, 5 with average MELD score at the time of transplantation serving as a surrogate for organ supply-demand mismatch. 110 CLINICAL LIVER DISEASE, VOL 8, NO 4, OCTOBER 2016 An Official Learning Resource of AASLD

4 FIG 2 (A) Variation by UNOS region in percentage of adult patients on the liver transplant waitlist removed for death or clinical deterioration, (B) Age-adjusted cause of death data from on people 15 to 74 years of age dying of disease of liver or liver cell carcinoma. Data are from the Compressed Mortality File Series 20, No. 2S, 2014, as compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. 10 Although reducing geographic variation in MELD score at the time of organ allocation is a high priority, geography is only one factor determining access to transplantation, albeit theoretically relatively modifiable by adaptations in allocation and distribution policy. Geographical variation in access to liver transplantation is derived from geographic variation in the prevalence of liver disease, population size, the number of potential organ donors (which is driven substantially by the frequency of preventable deaths), and the conversion rate of eligible organ donors to actual organ donors. In addition to geography, patients with identical types and degrees of liver disease can wait disparate amounts of time according to an array of factors that are variably outside of their control, including the number of regional transplant centers, blood type, age (e.g., child versus adult), indication for transplantation (e.g., liver cancer versus other indications), wealth, and possibly, celebrity. One of the biggest challenges in reducing geographic variations/disparity in access to liver transplantation is the identification of the optimal metric for which geographic variation is to be reduced. The median allocation MELD score at transplantation (the higher of the laboratory and exception scores) across the 11 UNOS regions varies dramatically, signifying substantial differences in the severity of illness at transplantation across the United States (Fig. 1A). However, geographic variation among the 11 UNOS regions in laboratory value based MELD scores (MELD scores calculated solely on the basis of recipient laboratory values at the time of transplantation; Fig. 1B) is markedly different from a map illustrating variation in allocation MELD scores (average MELD scores at time of transplantation regardless of whether laboratory value based or assigned through exception points; Fig. 1B). Whereas patients with the highest average laboratory MELD score at transplantation are in regions 5 and 7, the regions with the lowest laboratory MELD scores of transplant recipients include the Northeast (UNOS regions 1 and 9; Fig. 1B). The differences in apparent areas of greatest geographic disparity are caused by profound differences between transplant centers and UNOS regions in the number of patients allocated MELD scores as exceptions rather than MELD scores calculated from laboratory values (Fig. 1C). Patients with exception points have markedly higher transplant rates and lower waitlist mortality rates compared with nonexception patients with similar laboratory value based MELD scores. 7,8 Thus, exception MELD scores overestimate the risk for death in these patients. 7 MELD exception points have been identified as largely responsible for the steadily increasing MELD scores at transplant independent of geography. 7 Recent data suggest that more than 60% of US transplant recipients with hepatocellular carcinoma derive a net negative (loss of life) survival benefit with transplant over a 5-year time horizon, with an additional 20% gaining 0.24 life-year over this same period CLINICAL LIVER DISEASE, VOL 8, NO 4, OCTOBER 2016 An Official Learning Resource of AASLD

5 In addition to average MELD score at transplantation, other metrics of access to liver transplantation include waitlisting rates, transplantation rates, waitlist mortality, and severity of illness (laboratory value based MELD score) at transplant. Each of these objective metrics is determined by distinct sets of factors that are variably affected by geography. Mortality from liver disease, possibly one of the most meaningful measures of access to liver transplantation, is misaligned with geographic disparity in waitlist metrics, 9 with the risk for dying of chronic liver disease or dying on the waitlist higher in the Southwest and West and dramatically lower in the Northeast and Central regions of the United States (Fig. 2). These data largely mirror other broader measures of access to health care, including those published by the Dartmouth Atlas ( FUTURE OF ORGAN ALLOCATION Current OPTN regions represent arbitrary boundaries that were never optimized for organ donation. 6 Using mathematical modeling, Gentry et al. 6 have proposed optimized districts that would reduce disparities. The transplant community is currently considering a new allocation system that will obviate DSA boundaries and, instead, use fluid zones around each donor, prioritizing potential recipients at centers within a 150-mile radius of the donor. The current recommendation by the UNOS Liver and Intestine Committee proposes the following changes: 1. Eight districts (replacing 11 UNOS regions). 2. In-district proximity circle centered around donors, with three MELD/PELD proximity points for potential recipients within a 150-mile radius of a donor (DSA boundaries no longer considered for organ allocation/recipient prioritization). 3. District-wide sharing of adult deceased donor livers for all MELDs 29 before introducing local (DSA) priority. 4. Full district-wide sharing for pediatric donors. 5. Status 1A and 1B do not receive proximity points. SUMMARY Allocation of liver donor organs in the United States is a complex and evolving process. Access to donor organs varies greatly on a geographic basis. The development of optimal systems of distribution depends on consensus on the goals of the transplant system. Although the MELD score system is based on the premise of allocation to the sickest first, the unequal distribution of donor organs and the variable utilization of MELD score exceptions has reduced the effectiveness of the MELD score to identify patients in greatest need. New allocation/distribution systems are in development that attempt to more accurately allocate organs to the sickest patients first while limiting excess travel for organ procurement. The ideal way to ensure fairness and at what cost remains unclear. CORRESPONDENCE Michael Charlton, M.D., F.R.C.P., Director, Intermountain Transplant and Regenerative Medicine Institute, Intermountain Medical Center, 5169 South Cottonwood Street, Suite 320, Salt Lake City, UT michael.charlton@imail.org REFERENCES 1) Scientific Registry of Transplant Recipients. OPO Specific Reports. Published Accessed March 1, ) Wiesner R, Edwards E, Freeman R, Harper A, Kim R, Kamath P, et al. Model for end-stage liver disease (MELD) and allocation of donor livers. Gastroenterology 2003;124: ) Massie AB, Chow EK, Wickliffe CE, Luo X, Gentry SE, Mulligan DC, Segev DL. Early changes in liver distribution following implementation of Share 35. Am J Transplant 2015;15: ) Fernandez H, Weber J, Barnes K, Wright L, Levy M. Financial impact of liver sharing and Organ Procurement Organizations experience with Share 35: implications for national broader sharing. Am J Transplant 2016;16: ) Yeh H, Smoot E, Schoenfeld DA, Markmann JF. Geographic inequity in access to livers for transplantation. Transplantation 2011;91: ) Gentry SE, Massie AB, Cheek SW, Lentine KL, Chow EH, Wickliffe CE, et al. Addressing geographic disparities in liver transplantation through redistricting. Am J Transplant 2013;13: ) Northup PG, Intagliata NM, Shah NL, Pelletier SJ, Berg CL, Argo CK. Excess mortality on the liver transplant waiting list: unintended policy consequences and Model for End-Stage Liver Disease (MELD) inflation. Hepatology 2015;61: ) Berry K, Ioannou GN. Comparison of liver transplant-related survival benefit in patients with versus without hepatocellular carcinoma in the United States. Gastroenterology 2015;149: ) Centers for Disease Control and Prevention, National Center for Health Statistics. Compressed Mortality File on CDC WONDER Online Database, released October Data are from the Compressed Mortality File Series 20 No. 2S, 2014, as compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. Publication Accessed March 1, ) Centers for Disease Control and Prevention, National Center for Health Statistics. About compressed mortality, CDC WONDER Online Database. Published October Accessed March 1, CLINICAL LIVER DISEASE, VOL 8, NO 4, OCTOBER 2016 An Official Learning Resource of AASLD