Liver transplantation: expectation with MELD score for liver allocation in Brazil

Liver transplantation represents the most effective therapy for patients suffering from chronic end-stage liver disease. Until very recently, in Brazil, liver allocation was based on the Child-Turcotte-Pugh score and the waiting list followed a chronological criterion. In February 2002 the Model for End-stage Liver Disease (MELD) score was adopted for the allocation of donor livers in the US. After that change, an increased number of patients with more severe liver disease was observed, although there was no difference in 1-year patient and graft survival. A reduction in waiting-list mortality was also observed. In Brazil, the MELD score was adopted on May 31st, 2006. Good results are expected regarding the new criterion for allocation.     

Potential predictive value of the MELD score for short-term mortality after liver transplantation

In the last years, a model for end-stage liver disease (MELD) was suggested as a disease severity score for patients with end-stage liver disease awaiting liver transplantation. In the early 2002, United Network for Organ Sharing (UNOS) has proposed to replace the current status 2A, 2B, and 3 by a modified version of the original MELD score based upon patient risk for 3-month mortality on the waiting list. In this study UNOS status and MELD score were evaluated retrospectively for postoperative 3-month mortality in patients who underwent liver transplantation from 2000 to 2001. Liver recipients were stratified for UNOS status 2A, 2B, and 3, and the corresponding MELD score was calculated for each patient. A receiver operating characteristic (ROC) analysis was performed for both conventional UNOS status and MELD score by fitting patient deaths within 3 months after liver transplantation. The MELD score revealed a better prediction rate for 3-month mortality after the first LT than conventional UNOS status, although no statistical significance was evident by ROC curve comparison. This preliminary study seems to suggest a potentially better predictive rate for the MELD score than conventional UNOS status concerning short-term mortality after liver transplantation.     

Characteristics of waitlisted patients for liver transplantation at a liver transplantation unit in the city of Ribeirão Preto, São Paulo, Brazil, especially considering Child and Model for End Stage Liver Disease (MELD) scores

Liver transplantation represents the most effective therapy for patients suffering from chronic end-stage liver disease. Until recently, in Brazil liver allocation was based on the Child-Turcotte-Pugh score and the waiting list followed a chronological criterion. The aim of this study was to show the clinical and laboratory patterns of our patients awaiting a liver transplantation. Seventy-nine medical records were reviewed in January 2005 to classify patients according to their age, sex, cause of cirrhosis, and Child and Model for End Stage Liver Disease (MELD) scores. The mean age of patients was 47 years; 70% were men. The main diagnosis was liver cirrhosis (97%): 27% alcoholic, 26% viral hepatitis, 20% alcoholic plus viral hepatitis, 13% cryptogenic, and 11% other causes. Sixty-three patients (80%) were Child B or C. The average MELD, scores for Child A, B, and C were 10 +/- 5, 13 +/- 3.4, and 21 +/- 4.3, respectively. Nine deaths (11%) on the waiting list occurred in 2005. Among these, 1 patient was Child B with MELD 10, while the others were Child C, with mean MELD scores of 21 +/- 3.8. Twelve patients (15%) received cadaveric orthotopic liver transplantation. Thus, in this small series, the higher MELD scores corresponded to Child C class and mortality on the waiting list.     

The new liver allocation system: Moving toward evidence-based transplantation policy

In 1999, the Institute of Medicine suggested that instituting a continuous disease severity score that de-emphasizes waiting time could improve the allocation of cadaveric livers for transplantation. This report describes the development and initial implementation of this new plan. The goal was to develop a continuous disease severity scale that uses objective, readily available variables to predict mortality risk in patients with end-stage liver disease and reduce the emphasis on waiting time. Mechanisms were also developed for inclusion of good transplant candidates who do not have high risk of death but for whom transplantation may be urgent. The Model for End-Stage Liver Disease (MELD) and Pediatric End-Stage Liver Disease (PELD) scores were selected as the basis for the new allocation policy because of their high degree of accuracy for predicting death in patients having a variety of liver disease etiologies and across a broad spectrum of liver disease severity. Except for the most urgent patients, all patients will be ranked continuously under the new policy by their MELD/PELD score. Waiting time is used only to prioritize patients with identical MELD/PELD scores. Patients who are not well served by the MELD/PELD scores can be prioritized through a regionalized peer review system. This new liver allocation plan is based on more objective, verifiable measures of disease severity with minimal emphasis on waiting time. Application of such risk models provides an evidenced-based approach on which to base further refinements and improve the model. (Liver Transpl 2002;8:851-858.)     

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.     

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.)     

Model for End-Stage Liver Disease (MELD) score system to evaluate patients with viral hepatitis on the waiting list: better than the Child-Turcotte-Pugh (CTP) system?

BACKGROUND: The Model for End-Stage Liver Disease (MELD), based on creatinine, bilirubin, and International normalized ratio (INR), has been shown to be superior to the Child-Turcotte-Pugh (CTP) score in predicting 3-month mortality among patients on the transplant waiting list due to end-stage liver disease (ESLD). An additional advantage of MELD is the possibility to add "adjustment points" for exceptional patients at risk for death because of liver disease not identified by changes in the used parameters, as occurs in the case of hepatocellular carcinoma (HCC). Although it is useful, MELD has some important limitations: There are no differences for patients with or without ascites, and for the absence of other laboratory parameters involved in the etiology of disease. In this study, we evaluated dropouts of patients on the waiting list for orthotopic liver transplantation (OLT) based upon the characteristics of these subjects before and after introduction of the MELD score. METHODS: All patients on the OLT waiting list from June 1, 2006 to June 30, 2007 were enrolled in the MELD group (A) and evaluated with CHILD and MELD score, while those listed from January 1, 2004 to May 31, 2005 were enrolled in pre-MELD group (B) to be evaluated with CHILD. In these subjects we assessed the drop out frequency and waiting time and we compared the results to assess possible differences (U Mann-Whitney Test; P<.05). RESULTS: The total number of patients included in this study was 176: 116 patients in Group A and 60 in Group B. We had a drop-out frequency of 21% with a median of 9+/-6 S.E. months in Group A, while 9% with a median of 15+/-8 months S.E. in Group B. The dropout frequencies were as follows: Group A--16 deaths (1 HCC--15 disease complications) while in Group B we had 13 drop outs, 10 exitus (4 HCC and 6 disease complications) and three exclusions for nonmedical reasons. In Group A we had a higher number of deaths due to disease complications than in group B (P<.05). Further, we had 32 OLTx in Group A and 45 in Group B. Survival rate did not show any differences between the two groups while number needed to harm was 11. CONCLUSIONS: The use of MELD score in this group of patients produced an advantage for HCC, but seemed to cutoff patients with viral hepatitis complications during the waiting time. Particularly, about one in every 11 patients may receive an harm using this score system. Other parameters should be introduced as adjustment points to make the MELD score suitable also for patients with infectious liver diseases.     

Model for End Stage Liver Disease and hepatocellular carcinoma: a moving target

The institution of the Model for End Stage Liver Disease (MELD) score has been a successful refinement to the allocation for cadaveric liver allografts. Likewise, transplantation for patients with hepatocellular carcinoma (HCC) within defined criteria (Milan) has been shown to be very efficacious. The placement of patients with HCC in the allocation scheme with a MELD exception score has been an ongoing process of adjustments. The most recent data would suggest that patients with HCC continue to benefit from enhanced access to transplantation compared with patients without HCC. Development of a continuous HCC score, similar to the MELD score, maybe a more consistent and impartial way to equate access to cadaveric liver allografts for candidates with HCC and those without HCC.     

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.     

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.     

Impact of the MELD score on waiting time and disease severity in liver transplantation in United States veterans.

Organ allocation for liver transplantation (LT) in the United States is based on the Model for End-Stage Liver Disease (MELD) score. The MELD score prioritizes organ distribution to sicker patients. There is limited data on the effect of this policy on transplantation in the Veterans Affairs (VA) healthcare system. The aim of this study was to determine the impact of the MELD score on U.S. veteran patients undergoing LT. Comparison of MELD scores and waiting time of LT recipients before and after the introduction of the MELD system was done. A total of 192 LT recipients were analyzed. Blood type, diagnosis, listing MELD score, and Child-Turcotte-Pugh (CTP) score at transplant did not differ although MELD era recipients were older (mean 54.3 vs. 51.3 yr, P = 0.009). Mean waiting time decreased from 461 days (pre-MELD) to 252 days (MELD era) (P = 0.004). Mean MELD score at LT increased from 23.4 (MELD era) compared to 20.3 (pre-MELD) (P = 0.01). In conclusion, waiting time for LT in U.S. veterans has decreased significantly in the MELD era. The MELD score of patients transplanted in the MELD era is significantly higher and patients are still being listed at a high MELD score. The MELD system has lead to sicker veterans being transplanted with shorter waiting times.     

Model for end-stage liver disease

In December 2006 the allocation of livers from deceased donors in Germany and several other Eurotransplant countries was reset. The previous allocation system relied on CTP score to assess the need of transplantation, but it also assigned to waiting time a prominent role in prioritization. That system was replaced by the primarily urgency-oriented model of end-stage liver disease (MELD) allocation system. First experience with this classification in the U.S.A. shows that MELD scores are able to identify the urgency of liver transplantation correctly in most types of liver disease. Due to the MELD-based allocation, the growing waiting time and waiting-list mortality could be counteracted. At the same time it became evident however that MELD scores do not reflect mortality on the waiting list or thus the urgency for all types of liver diseases. Therefore the new allocation system introduced in the Eurotransplant countries contains standardized and flexible exceptions for these diseases. In addition the new allocation rules were created as a learning system. Repeated "fine tuning" of the allocation process based on continuous monitoring of daily allocation practice and clinical studies aim at just and effective distribution of the precious and limited supply of donor organs.     

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.     

Liver transplant recipient selection: MELD vs. clinical judgment.

Minimization of death while waiting for liver transplantation involves accurate prioritization according to clinical status and appropriate allocation of donor livers. Clinical judgment in the Liver Transplant Unit Victoria (LTUV) was compared with Model for End-Stage Liver Disease (MELD) in a retrospective analysis of the LTUV database over the 2-year period August 1, 2002, through July 31, 2004. A total of 1,118 prioritization decisions occurred. Decisions were concordant in 758 (68%), comparing priorities assigned by clinical judgment with those assigned by MELD, P < 0.01. A total of 263 allocation decisions occurred. Decisions were concordant in 190 (72%) and 203 (77%) of the cases, comparing donor liver allocation with prioritization by MELD and clinical judgment, respectively. Of the 52 patients allocated a liver, only 23 would have been allocated on the basis of MELD while 29 had been prioritized on the waiting list in the week prior to transplantation. A total of 10 patients died on the waiting list in the 2-year period (annual adult waiting list mortality is 9.3%). Patients who subsequently died waiting were 3 times as likely to be prioritized by MELD as clinical judgment (29% vs. 9%, respectively). One half (3 of 6) of the patients who could have received a donor liver but who died waiting would have been allocated the organ on the basis of MELD. In conclusion, an allocation process based on MELD rather than clinical judgment would significantly alter organ allocation in Australia and may reduce waiting list mortality.     

Addressing Geographic Disparities in Liver Transplantation Through Redistricting

Severe geographic disparities exist in liver transplantation; for patients with comparable disease severity, 90‐day transplant rates range from 18% to 86% and death rates range from 14% to 82% across donation service areas (DSAs). Broader sharing has been proposed to resolve geographic inequity; however, we hypothesized that the efficacy of broader sharing depends on the geographic partitions used. To determine the potential impact of redistricting on geographic disparity in disease severity at transplantation, we combined existing DSAs into novel regions using mathematical redistricting optimization. Optimized maps and current maps were evaluated using the Liver Simulated Allocation Model. Primary analysis was based on 6700 deceased donors, 28 063 liver transplant candidates, and 242 727 Model of End‐Stage Liver Disease (MELD) changes in 2010. Fully regional sharing within the current regional map would paradoxically worsen geographic disparity (variance in MELD at transplantation increases from 11.2 to 13.5, p = 0.021), although it would decrease waitlist deaths (from 1368 to 1329, p = 0.002). In contrast, regional sharing within an optimized map would significantly reduce geographic disparity (to 7.0, p = 0.002) while achieving a larger decrease in waitlist deaths (to 1307, p = 0.002). Redistricting optimization, but not broader sharing alone, would reduce geographic disparity in allocation of livers for transplant across the United States.     

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.     

Predictive models in cirrhosis: correlation with the final results and costs of liver transplantation in Chile

Medical scores for predicting survival are essential to stratify patients with end-stage liver disease (ESLD) for prioritization for liver transplantation (OLT). Recently the UNOS has adopted the Mayo Model for End-stage Liver Disease (MELD) score as the basis for liver allocation in the United States. We retrospectively evaluated and assessed the prognostic impact, the length of stay (LOS), and hospital charges for OLT using two severity scores (Child-Turcotte-Pugh [CTP] versus MELD) to stratify cirrhotic patients before OLT. Twenty-six consecutive adult cirrhotic patients (11 women, mean age 46 years) underwent LT between 2000 and 2002. The main causes for transplantation were alcohol and primary biliary cirrhosis. The mean CTP and MELD scores at the moment of listing for OLT were 8.9 and 16.3 points, respectively. The best discriminative values with prognostic impact in terms of outcome and costs of OLT were a Child Pugh score >/=11 points or a MELD score >/=20 points. Patients in these strata showed a significant increase in LOS in the hospital (from a mean of 12 to 22 days) and intensive care stay (from a mean of 4 to 14 days) post-OLT when compared with patients with a lower CTP or MELD score (P <.05). There was also a trend toward higher hospital charges (P =.06). Organ allocation by MELD score will probably adversely affect the LOS and hospital charges of patients being transplanted due to ESLD.     

Model for end-stage liver disease score versus simplified acute physiology score criteria in acute renal failure after liver transplantation

Hepatic function and renal failure are closely related among patients with end-stage liver disease (ESLD) due to splanchnic hemodynamic mechanisms that characterize advanced decompensated cirrhosis. Acute renal failure (ARF) is a frequent complication that occurs immediately post-orthotopic liver transplantation (OLT). The Model for End-stage Liver Disease (MELD) score describes the survival of patients with ESLD awaiting OLT related to the severity of liver disease. The Simplified Acute Physiology Score (SAPS II) is a mortality prediction model that scores the severity of illness among intensive care unit patients. In a previous study we observed an association between ARF post-OLT and a higher MELD score, but it was not clear whether this association depends on the grade of ESLD or on the critical condition of liver transplant patients. The aim of this study was to evaluate the association of ARF with MELD score and/or SAPS II criteria among liver transplant patients. We analyzed 46 patients with ESLD who underwent deceased donor OLT. All patients were evaluated at baseline and in the first 7 days post-OLT. According to the RIFLE classification, the incidence of the worst grade of ARF post-OLT was 19.2%. These patients showed significantly higher MELD scores, while there was no association with systemic parameters related to the critical patient's condition or with the mortality score as evaluated by SAPS II criteria. We confirmed the association between renal failure and hepatic function among liver transplant patients. A more severe degree of hepatic dysfunction before OLT was associated with a greater incidence of ARF that can adversely affect patient survival.     

Survival Benefit-Based Deceased-Donor Liver Allocation

Currently, patients awaiting deceased-donor liver transplantation are prioritized by medical urgency. Specifically, wait-listed chronic liver failure patients are sequenced in decreasing order of Model for End-stage Liver Disease (MELD) score. To maximize lifetime gained through liver transplantation, posttransplant survival should be considered in prioritizing liver waiting list candidates. We evaluate a survival benefit based system for allocating deceased-donor livers to chronic liver failure patients. Under the proposed system, at the time of offer, the transplant survival benefit score would be computed for each patient active on the waiting list. The proposed score is based on the difference in 5-year mean lifetime (with vs. without a liver transplant) and accounts for patient and donor characteristics. The rank correlation between benefit score and MELD score is 0.67. There is great overlap in the distribution of benefit scores across MELD categories, since waiting list mortality is significantly affected by several factors. Simulation results indicate that over 2000 life-years would be saved per year if benefit-based allocation was implemented. The shortage of donor livers increases the need to maximize the life-saving capacity of procured livers. Allocation of deceased-donor livers to chronic liver failure patients would be improved by prioritizing patients by transplant survival benefit.