Geographic Differences in Event Rates by Model for End-Stage Liver Disease Score

The ability of the model for end-stage liver disease (MELD) score to accurately predict death among liver transplant candidates allows for evaluation of geographic differences in transplant access for patients with similar death risk. Adjusted models of time to transplant and death for adult liver transplant candidates listed between 2002 and 2003 were developed to test for differences in MELD score among Organ Procurement and Transplantation Network (OPTN) regions and Donation Service Areas (DSA). The average MELD and relative risk (RR) of death varied somewhat by region (from 0.82 to 1.28), with only two regions having significant differences in RRs. Greater variability existed in adjusted transplant rates by region; 7 of 11 regions differed significantly from the national average. Simulation results indicate that an allocation system providing regional priority to candidates at MELD scores > or = 15 would increase the median MELD score at transplant and reduce the total number of deaths across DSA quintiles. Simulation results also indicate that increasing priority to higher MELD candidates would reduce the percentage variation among DSAs of transplants to patients with MELD scores > or = 15. The variation decrease was due to increasing the MELD score at time of transplantation in the DSAs with the lowest MELD scores at transplant.     

Assessing Variation in the Costs of Care Among Patients Awaiting Liver Transplantation

Previous economic analyses of liver transplantation have focused on the cost of the transplant and subsequent care. Accurate characterization of the pretransplant costs, indexed to severity of illness, is needed to assess the economic burden of liver disease. A novel data set linking Medicare claims with transplant registry data for 15 710 liver transplant recipients was used to determine average monthly waitlist spending (N = 249 434 waitlist months) using multivariable linear regression models to adjust for recipient characteristics including Model for End‐Stage Liver Disease (MELD) score. Characteristics associated with higher spending included older age, female gender, hepatocellular carcinoma, diabetes, hypertension and increasing MELD score (p < 0.05 for all). Spending increased exponentially with severity of illness: expected monthly spending at a MELD score of 30 was 10 times higher than at MELD of 20 ($22 685 vs. $2030). Monthly spending within MELD strata also varied geographically. For candidates with a MELD score of 35, spending varied from $19 548 (region 10) to $36 099 (region 7). Regional variation in waitlist costs may reflect the impact of longer waiting times on greater pretransplant hospitalization rates among high MELD score patients. Reducing the number of high MELD waitlist patients through improved medical management and novel organ allocation systems could decrease total spending for end‐stage liver care.     

Sex‐Based Disparities in Liver Transplant Rates in the United States

We sought to characterize sex‐based differences in access to deceased donor liver transplantation. Scientific Registry of Transplant Recipients data were used to analyze n = 78 998 adult candidates listed before (8/1997–2/2002) or after (2/2002–2/2007) implementation of Model for End‐Stage Liver Disease (MELD)‐based liver allocation. The primary outcome was deceased donor liver transplantation. Cox regression was used to estimate covariate‐adjusted differences in transplant rates by sex. Females represented 38% of listed patients in the pre‐MELD era and 35% in the MELD era. Females had significantly lower covariate‐adjusted transplant rates in the pre‐MELD era (by 9%; p < 0.0001) and in the MELD era (by 14%; p < 0.0001). In the MELD era, the disparity in transplant rate for females increased as waiting list mortality risk increased, particularly for MELD scores ≥15. Substantial geographic variation in sex‐based differences in transplant rates was observed. Some areas of the United States had more than a 30% lower covariate‐adjusted transplant rate for females compared to males in the MELD era. In conclusion, the disparity in liver transplant rates between females and males has increased in the MELD era. It is especially troubling that the disparity is magnified among patients with high MELD scores and in certain regions of the United States.     

Development and validation of an optimized prediction of mortality for candidates awaiting liver transplantation

Since 2002, the Model for End‐Stage Liver Disease (MELD) has been used to rank liver transplant candidates. However, despite numerous revisions, MELD allocation still does not allow for equitable access to all waitlisted candidates. An optimized prediction of mortality (OPOM) was developed ( http://www.opom.online ) utilizing machine‐learning optimal classification tree models trained to predict a candidate's 3‐month waitlist mortality or removal utilizing the Standard Transplant Analysis and Research (STAR) dataset. The Liver Simulated Allocation Model (LSAM) was then used to compare OPOM to MELD‐based allocation. Out‐of‐sample area under the curve (AUC) was also calculated for candidate groups of increasing disease severity. OPOM allocation, when compared to MELD, reduced mortality on average by 417.96 (406.8‐428.4) deaths every year in LSAM analysis. Improved survival was noted across all candidate demographics, diagnoses, and geographic regions. OPOM delivered a substantially higher AUC across all disease severity groups. OPOM more accurately and objectively prioritizes candidates for liver transplantation based on disease severity, allowing for more equitable allocation of livers with a resultant significant number of additional lives saved every year. These data demonstrate the potential of machine learning technology to help guide clinical practice, and potentially guide national policy.     

The Economic Implications of Broader Sharing of Liver Allografts

Liver transplantation has evolved over the past four decades into the most effective method to treat end‐stage liver failure and one of the most expensive medical technologies available. Accurate understanding of the financial implication of recipient severity of illness is crucial to assessing the economic impact of allocation policies. A novel database of linked clinical data from the Organ Procurement and Transplantation Network with cost accounting data from the University HealthSystem Consortium was used to analyze liver transplant costs for 15 813 liver transplants. This data was then utilized to consider the economic impact of alternative allocation systems designed to increase sharing of liver allografts using simulation results. Transplant costs were strongly associated with recipient severity of illness as assessed by the MELD score (p < 0.0001); however, this relationship was not linear. Simulation analysis of the reallocation of livers from low MELD patients to high MELD using a two‐tiered regional sharing approach (MELD 15/25) resulted in 88 fewer deaths annually at estimated cost of $17 056 per quality‐adjusted life‐year saved. The results suggest that broader sharing of liver allografts offers a cost‐effective strategy to reduce the mortality from end stage liver disease.     

Role of Patient Factors and Practice Patterns in Determining Access to Liver Waitlist

Geographic variability in access to care is a persistent challenge in transplantation. Little is known about how patients with end‐stage liver disease are chosen for referral, evaluation and listing. Utilizing death certificate data from the Centers for Disease Control and Prevention from 2002 to 2009, estimated liver demand (ELD) was measured by aggregating annual deaths from liver disease and liver transplants performed in each donor service area (DSA). In DSAs with higher ELD, more patients per capita were listed for transplantation (p < 0.001). In addition, listing rates per ELD varied fivefold across DSAs, with more patients per ELD being transplanted in DSAs with higher listing rates (p < 0.001). After adjusting for liver donor risk index and MELD at transplant, there was no association between listing rate and posttransplant survival (HR 1.002, p = 0.77). In addition, DSAs with lower listing rates were more likely to export organs (p < 0.001) of lower liver donor risk index (p < 0.001). Listing sicker patients was associated with increased access to the waitlist and transplantation and more efficient organ utilization, but had minimal effect on posttransplant outcomes after adjusting for the resulting organ shortage.     

Use of Population‐based Data to Demonstrate How Waitlist‐based Metrics Overestimate Geographic Disparities in Access to Liver Transplant Care

Liver allocation policies are evaluated by how they impact waitlisted patients, without considering broader outcomes for all patients with end‐stage liver disease (ESLD) not on the waitlist. We conducted a retrospective cohort study using two nationally representative databases: HealthCore (2006–2014) and five‐state Medicaid (California, Florida, New York, Ohio and Pennsylvania; 2002–2009). United Network for Organ Sharing (UNOS) linkages enabled ascertainment of waitlist‐ and transplant‐related outcomes. We included patients aged 18–75 with ESLD (decompensated cirrhosis or hepatocellular carcinoma) using validated International Classification of Diseases, Ninth Revision (ICD‐9)–based algorithms. Among 16 824 ESLD HealthCore patients, 3‐year incidences of waitlisting and transplantation were 15.8% (95% confidence interval [CI] : 15.0–16.6%) and 8.1% (7.5–8.8%), respectively. Among 67 706 ESLD Medicaid patients, 3‐year incidences of waitlisting and transplantation were 10.0% (9.7–10.4%) and 6.7% (6.5–7.0%), respectively. In HealthCore, the absolute ranges in states' waitlist mortality and transplant rates were larger than corresponding ranges among all ESLD patients (waitlist mortality: 13.6–38.5%, ESLD 3‐year mortality: 48.9–62.0%; waitlist transplant rates: 36.3–72.7%, ESLD transplant rates: 4.8–13.4%). States' waitlist mortality and ESLD population mortality were not positively correlated: ρ = ?0.06, p‐value = 0.83 (HealthCore); ρ = ?0.87, p‐value = 0.05 (Medicaid). Waitlist and ESLD transplant rates were weakly positively correlated in Medicaid (ρ = 0.36, p‐value = 0.55) but were positively correlated in HealthCore (ρ = 0.73, p‐value = 0.001). Compared to population‐based metrics, waitlist‐based metrics overestimate geographic disparities in access to liver transplantation.     

Survival Outcomes Following Liver Transplantation (SOFT) Score: A Novel Method to Predict Patient Survival Following Liver Transplantation

It is critical to balance waitlist mortality against posttransplant mortality. Our objective was to devise a scoring system that predicts recipient survival at 3 months following liver transplantation to complement MELD‐predicted waitlist mortality. Univariate and multivariate analysis on 21 673 liver transplant recipients identified independent recipient and donor risk factors for posttransplant mortality. A retrospective analysis conducted on 30 321 waitlisted candidates reevaluated the predictive ability of the Model for End‐Stage Liver Disease (MELD) score. We identified 13 recipient factors, 4 donor factors and 2 operative factors (warm and cold ischemia) as significant predictors of recipient mortality following liver transplantation at 3 months. The Survival Outcomes Following Liver Transplant (SOFT) Score utilized 18 risk factors (excluding warm ischemia) to successfully predict 3‐month recipient survival following liver transplantation. This analysis represents a study of waitlisted candidates and transplant recipients of liver allografts after the MELD score was implemented. Unlike MELD, the SOFT score can accurately predict 3‐month survival following liver transplantation. The most significant risk factors were previous transplantation and life support pretransplant. The SOFT score can help clinicians determine in real time which candidates should be transplanted with which allografts. Combined with MELD, SOFT can better quantify survival benefit for individual transplant procedures.     

Longitudinal assessment of mortality risk among candidates for liver transplantation

Liver allocation policy recently was modified to use the Model for End-Stage Liver Disease (MELD) for patients with chronic liver disease to stratify potential recipients according to risk for waitlist death. In this study, a retrospective cohort of 760 adult patients with chronic liver disease placed on the liver transplant waitlist between January 1995 and March 2001 and followed up for up to 74 months was studied to assess the ability of the MELD to predict mortality among waitlisted candidates and evaluate the prognostic importance of changes in MELD score over time. Serial MELD scores predicted waitlist mortality significantly better than baseline MELD scores or medical urgency status. Each unit of the 40-point MELD score was associated with a 22% increased risk for waitlist death (P < .001), whereas medical urgency status was not a significant independent predictor. For any given MELD score, the magnitude and direction of change in MELD score during the previous 30 days (ΔMELD) was a significant independent mortality predictor. Patients with MELD score increases greater than 5 points over 30 days had a threefold greater waitlist mortality risk than those for whom MELD scores increased more gradually (P < .0001). We conclude that mortality risk on the liver transplant waitlist is predicted more accurately by serial MELD score determinations than by medical urgency status or single MELD measurements. ΔMELD score over time reflects progression of liver disease and conveys important additional prognostic information that should be considered in the further evolution of national liver allocation policy. (Liver Transpl 2003;9:12-18.)     

Geographic disparities in deceased donor liver transplantation within a single UNOS region.

Although the Model for End-Stage Liver Disease (MELD) scoring system has improved the ability to measure medical urgency for transplantation, geographic disparities in the probability of being delisted as a result of complications of end-stage liver disease or death and in the probability of orthotopic liver transplantation (OLT) remain. The purpose of the current study was to identify factors associated with these variations among donor service areas (DSAs) in one United Network for Organ Sharing (UNOS) region. Data for 2,948 candidates listed for OLT within 4 DSAs in UNOS region 4 between February 2002 and November 2005 were obtained from UNOS. Multivariate regression models were used to identify study factors associated with delisting (due to deterioration or death) and likelihood of OLT. After risk adjustment for candidate characteristics, those listed in DSA-3 and DSA-4 were at significantly higher risk of delisting than candidates listed in DSA-2 (hazard ratio, 1.22 and 1.10 vs. 0.87 for DSA-2; P = 0.01 and 0.05, respectively). In addition, the likelihood of OLT was significantly higher for candidates listed in DSA-1 than in DSA-2, DSA-3 or DSA-4 (hazard ratio, 1.00 compared with 0.45, 0.77, and 0.51; P < 0.001 for all pairwise comparisons). Despite the implementation of the MELD system, great geographic disparities exist in the likelihood of delisting and for OLT, suggesting the need for further refinement in regional allocation strategies.     

The effects of Share 35 on the cost of liver transplantation

On June 18, 2013, the United Network for Organ Sharing (UNOS) instituted a change in the liver transplant allocation policy known as “Share 35.” The goal was to decrease waitlist mortality by increasing regional sharing of livers for patients with a model for end‐stage liver disease (MELD) score of 35 or above. Several studies have shown Share 35 successful in reducing waitlist mortality, particularly in patients with high MELD. However, the MELD score at transplant has increased, resulting in sicker patients, more complications, and longer hospital stays. Our study aimed to explore factors, along with Share 35, that may affect the cost of liver transplantation. Our results show Share 35 has come with significantly increased cost to transplant centers across the nation, particularly in regions 2, 5, 10, and 11. Region 5 was the only region with a median MELD above 35 at transplant, and cost was significantly higher than other regions. Several other recipient factors had changes with Share 35 that may significantly affect the cost of liver transplant. While access to transplantation for the sickest patients has improved, it has come at a cost and regional disparities remain. Financial implications with proposed allocation system changes must be considered.     

The Survival Benefit of Liver Transplantation

Demand for liver transplantation continues to exceed donor organ supply. Comparing recipient survival to that of comparable candidates without a transplant can improve understanding of transplant survival benefit. Waiting list and post-transplant mortality was studied among a cohort of 12 996 adult patients placed on the waiting list between 2001 and 2003. Time-dependent Cox regression models were fitted to determine relative mortality rates for candidates and recipients. Overall, deceased donor transplant recipients had a 79% lower mortality risk than candidates (HR = 0.21; p < 0.001). At Model for End-stage Liver Disease (MELD) 18-20, mortality risk was 38% lower (p < 0.01) among recipients compared to candidates. Survival benefit increased with increasing MELD score; at the maximum score of 40, recipient mortality risk was 96% lower than that for candidates (p < 0.001). In contrast, at lower MELD scores, recipient mortality risk during the first post-transplant year was much higher than for candidates (HR = 3.64 at MELD 6-11, HR = 2.35 at MELD 12-14; both p < 0.001). Liver transplant survival benefit at 1 year is concentrated among patients at higher risk of pre-transplant death. Futile transplants among severely ill patients are not identified under current practice. With 1 year post-transplant follow-up, patients at lower risk of pre-transplant death do not have a demonstrable survival benefit from liver transplant.     

Impact of the new MELD‐based allocation system on waiting list and post‐transplant survival—a cohort analysis using the French national CRISTAL database

Concerns related to equity and efficacy of our previous center‐based allocation system have led us to introduce a patient‐based allocation system called the “Liver Score” that incorporates the model for end‐stage liver disease (MELD) score. The main objective of this study was to compare waitlist and post‐transplant survivals before and after implementation of the “Liver Score” using the French transplant registry (period before: 2004–2006 and period after: 2007–2012). Patients transplanted during the second period were sicker and had a higher MELD. One‐year waitlist survival (74% vs. 76%; P = 0.8) and 1‐year post‐transplant survival (86.3% vs. 85.7%; P = 0.5) were similar between the 2 periods. Cirrhotic recipients with MELD > 35 had lower 1‐year post‐transplant survival compared to those with MELD <35 (74.8% vs. 86.3%; P < 0.01), mainly explained by their higher intubation and renal failure rates. The MELD showed a poor discriminative capacity. In cirrhotic recipients with MELD > 35, patients presenting 2 or 3 risk factors (dialysis, intubation, or infection) had a lower 1‐year survival compared to those with none of these risk factors (61.2% vs. 92%; P < 0.01). The implementation of the MELD‐based allocation system has led to transplant sicker patients with no impact on waitlist and post‐transplant survivals. Nevertheless, selection of patients with MELD > 35 should be completed to allow safe transplantation.     

Same quality – higher price? The paradox of allocation: the first national single center analysis after the implementation of the new Swiss transplantation law: the ICU view

This study was undertaken as the first national single-center analysis to assess the impact of the new Swiss transplantation law on patient selection, intensive care unit (ICU) complications, outcome, and, in particular, costs in liver transplant recipients treated in our surgical ICU. The first 35 consecutive liver transplant recipients following the new act were compared with the last 35 liver transplant recipients preceding July 1, 2007. Following execution of the new law, recipients were in poorer condition, reflected by significant higher Model for End-Stage Liver Disease (MELD) scores (12 vs. 22; p = 0.006). Furthermore, the MELD group obtained more renal replacement therapies (40.0% vs. 14.3%; p = 0.015). Cumulative one-yr patient survival was comparable in both groups (91.4% vs. 80.1%, p = 0.22). Finally, the additional costs per single case increased 27 000 Euros after the adoption of the new law. Our data serve as an example that political decisions influence patient's selection, and, in turn, complications, finally leading to higher costs of medical treatment. Liver graft allocation according to the MELD system may save lives at the price of increased intensive care efforts.     

Rules for allocation of livers for transplantation

Previous rules of allocation of livers for transplantation were based mainly on local priorities, with final management left to the local team. This created substantial regional disparities. A prospective survey of waiting list deaths and dropouts due to aggravation of liver disease (2003-2005) validated the MELD (Model for End-stage Liver Disease) score on French data. A new allocation score (Liver Score) for liver transplants, based on specific variables for each liver disease, was introduced in March 2007. An initial evaluation, based on the first 5 months of practice, clearly shows that the Liver Score reduces the rates of deaths, dropouts, and futile transplantations; it also accelerates access to transplantation for the sickest patients. Several points remain unresolved: both the MELD and Liver scores may be improved. The variability of the MELD score related to different laboratory assay methods requires harmonization between laboratories.     

Survival After Adult Liver Transplantation Does Not Correlate with Transplant Center Case Volume in the MELD Era

It has been demonstrated that low-volume orthotopic liver transplant centers have poorer outcomes compared to high-volume centers. In light of the recent significant changes in liver transplantation, we performed an analysis of transplant center procedure volume and mortality with data from the Model for End-stage Liver Disease (MELD) era. We analyzed 9909 adult liver transplants performed in the United States since the beginning of the MELD allocation system. Transplant centers were categorized by volume of transplants performed per year. Multivariate survival models were constructed with raw survival as the primary endpoint for both high- and low-volume centers. Thirty percent of centers were categorized as low volume (< or =20 liver transplants per year) and 8.2% of all transplants were performed at low-volume centers. The unadjusted raw mortality rate at 1-year post-transplant at high-volume centers (9.5%, 95% CI 9.4-9.5) was significantly lower than the rate at low-volume centers (10.9%, 95% CI 10.4-11.4), p < 0.001. However, after adjusting for disease severity and multiple donor and recipient factors, transplant center volume was no longer a significant predictor of post-transplant survival (HR 0.99, 95% CI 0.99-1.00, p = 0.22). We conclude that transplant center case volume is no longer a significant predictor of post-transplant survival in the MELD era and factors which are currently unaccounted for in present survival models should be investigated.     

Hepatocellular Carcinoma Recurrence and Death Following Living and Deceased Donor Liver Transplantation

We examined mortality and recurrence of hepatocellular carcinoma (HCC) among 106 transplant candidates with cirrhosis and HCC who had a potential living donor evaluated between January 1998 and February 2003 at the nine centers participating in the Adult-to-Adult Living Donor Liver Transplantation Cohort Study (A2ALL). Cox regression models were fitted to compare time from donor evaluation and time from transplant to death or HCC recurrence between 58 living donor liver transplant (LDLT) and 34 deceased donor liver transplant (DDLT) recipients. Mean age and calculated Model for End-Stage Liver Disease (MELD) scores at transplant were similar between LDLT and DDLT recipients (age: 55 vs. 52 years, p = 0.21; MELD: 13 vs. 15, p = 0.08). Relative to DDLT recipients, LDLT recipients had a shorter time from listing to transplant (mean 160 vs. 469 days, p < 0.0001) and a higher rate of HCC recurrence within 3 years than DDLT recipients (29% vs. 0%, p = 0.002), but there was no difference in mortality or the combined outcome of mortality or recurrence. LDLT recipients had lower relative mortality risk than patients who did not undergo LDLT after the center had more experience (p = 0.03). Enthusiasm for LDLT as HCC treatment is dampened by higher HCC recurrence compared to DDLT.     

MELD scores do not predict patient morbidity while on the liver transplant waiting list

The goals of this study were to assess waitlist morbidity in terms of the frequency of health care services utilized by patients while on the liver transplant (LTX) waiting list and to determine whether that utilization can be predicted by the Model for End-Stage Liver Disease (MELD). Sixty-three noncomatose subjects were followed from waitlist placement until death, change in status, LTX, or study discontinuance. Health care events included doctor/clinic visits, labs, outpatient/inpatient tests and procedures, and hospital/intensive care unit days. Listing MELD scores and LTX MELD scores were examined against the number of health care event occurrences within 60 days of listing and 60 days of LTX, respectively, as were changes in MELD scores between listing and LTX and differences in the number of occurrences between the two time points. The only significant correlations noted were between LTX MELD scores and number of hospital days near LTX (r = .360, P = .046) and between LTX MELD scores and the sum total number of occurrences near LTX (r = .370, P = .044). These results suggest that MELD scores do not appear to predict morbidity in terms of health care utilization in patients awaiting LTX. Developing a system capable of predicting waitlist morbidity may lead to the implementation of medical interventions aimed at circumventing foreseeable complications and/or crises in patients awaiting LTX.     

Lack of Standardization in Exception Points for Patients With Primary Sclerosing Cholangitis and Bacterial Cholangitis

For conditions that the Model for End‐Stage Liver Disease (MELD) score does not accurately predict waitlist mortality, transplant centers may apply to regional review boards for exception points. For patients with primary sclerosing cholangitis (PSC) suffering from bacterial cholangitis, consensus recommendations published in December 2006 are to grant exception points for recurrent cholangitis with ≥2 episodes of bacteremia or ≥1 episode septic complications. Using data provided by the United Network for Organ Sharing, we evaluated PSC patients who applied for exception points due to bacterial cholangitis from February 27, 2002 to March 14, 2011. Before publication of the recommendations, 66.0% of applications were accepted, compared with 80.1% after (p < 0.001). Focusing on applications after publication of the recommendations, 311 (74.6%) did not meet the recommended criteria, and 250 (80.4%) of these were approved. Of patients with approved applications, those not meeting consensus criteria were more likely to be transplanted, (77.4% vs. 62.8%, p = 0.043), whereas those with denied applications for approved indications were more liked to die/be removed (44.4% vs. 9.5%, p = 0.49). Although data are needed to properly identify those patients at highest risk for waitlist mortality, standardized criteria or a centralized review board should be adopted to ensure consistency in the granting of exception points.     

Use of living donor liver transplantation varies with the availability of deceased donor liver transplantation

The demographics of patients in the United States who undergo living donor liver transplantation (LDLT) versus patients who undergo deceased donor liver transplantation (DDLT) are interesting with respect to the demographics of the donor service areas (DSAs). We examined adult recipients of primary, non-status 1 liver-only transplants from 2003 to 2009. The likelihood of undergoing LDLT was compared to the likelihood of undergoing DDLT by multivariate logistic regression. We examined the adjusted odds ratio (OR) for undergoing LDLT versus DDLT for patients with the same diagnosis and blood type after we stratified the DSAs into quintiles by the median match Model for End-Stage Liver Disease (MELD) scores. LDLT was performed for 1497 of 32,927 liver transplants (4.5%). LDLT decreased in frequency by approximately 30% from 2003 to 2009. In comparison with DDLT recipients, LDLT recipients were younger and had higher albumin levels, lower body mass indices, and lower match MELD scores. Females had increased odds of LDLT in comparison with males (OR = 1.74, P < 0.001). Patients with MELD exception scores were less likely to undergo LDLT (OR = 0.22, P < 0.001). Patients with cholestatic liver disease (adjusted OR = 2.04, P < 0.001) or malignant neoplasms other than hepatocellular carcinoma (adjusted OR = 3.33, P < 0.001) were more likely than patients with hepatitis C virus to undergo LDLT. Other characteristics associated with decreased odds of LDLT were black race (adjusted OR = 0.41, P < 0.001) and government insurance (adjusted OR = 0.51, P < 0.001). LDLT was more frequent in DSAs with high median MELD scores; the adjusted OR for LDLT was 38 for the DSAs in the highest quintile (P < 0.001). In conclusion, there are significant differences associated with race, insurance, sex, MELD exceptions, and DSA MELD scores between patients who undergo LDLT and patients who undergo DDLT. These differences can be hypothesized to be driven in part by the relative availability of LDLT versus DDLT at both the patient level and the DSA level.