Organ Allocation In Liver Transplantation Research Articles

Mind the gaps: reframing patient selection and organ allocation in liver transplantation.

Mind the gaps: reframing patient selection and organ allocation in liver transplantation.

MELD or MELD-Na as a Predictive Model for Mortality Following Transjugular Intrahepatic Portosystemic Shunt Placement.

The model for end-stage liver disease (MELD) was originally developed to predict survival after transjugular intrahepatic portosystemic shunt (TIPS). The MELD-sodium (MELD-Na) score has replaced MELD for organ allocation for liver transplantation. However, there are limited studies to compare the MELD with MELD-Na to predict mortality after TIPS. We performed a retrospective chart review of patients who underwent TIPS placement between 2006 and 2016 at our institution. The primary outcome was mortality, and the secondary outcomes sought to assess which variables could provide prognostic information for mortality after TIPS placement. We performed receiver operating characteristic (ROC) curve analysis to assess the performance of MELD and MELD-Na. There were 186 eligible patients in the analysis. The mean pre-TIPS MELD and MELD-Na were 13 and 15, respectively. Overall, mortality after TIPS was 15% at 30 days and 16.7% at 90 days. In a comparison of the areas under the ROCs for MELD and MELD-Na, MELD was superior to MELD-Na for 30-day (0.762 vs. 0.709) and 90-day (0.780 vs. 0.730) mortality after TIPS. The optimal cutoff score for 30-day mortality was 15 (0.676-0.848) for MELD and 17 (0.610-0.808) for MELD-Na, whereas the optimal cutoff score for 90-day mortality was 16 (95% CI: 0.705-0.855) for MELD and 17 (95% CI: 0.643-0.817) for MELD-Na. There were 24 patients with high MELD-Na ≥17, but with low MELD <15, and 90-day mortality in this group was 8.3%. Although MELD-Na is a superior prognostic tool to MELD for predicting overall mortality in cirrhotic patients, MELD tended to outperform MELD-Na to predict mortality after TIPS.

Model for end-stage liver disease underestimates mortality of patients with acute-on-chronic liver failure waiting for liver transplantation.

Patients with acute-on-chronic liver failure (ACLF) show excess mortality in MELD-Na based organ allocation for liver transplantation (LT). Whether MELD-based allocation in the Eurotransplant region similarly underprioritizes ACLF patients is unknown. 428 patients listed for LT from 01/2010 to 02/2021 at a tertiary center in Germany were screened and 209 patients included as derivation (n=123) and validation cohort (n=86). Competing risk analysis for waitlist mortality and LT as competing events was performed. 90-day waitlist mortality for patients with MELD < and ≥ 25 at baseline was 9% vs. 33%, respectively (p=0.009). Competing risk analysis shows significantly higher 90-day waitlist mortality in patients listed with ACLF compared to those without ACLF (p=0.021) in the low MELD stratum. Probability of LT was similar between the two groups (p=0.91). In the high MELD group, 90-day waitlist mortality and rates of LT were not significantly different between patients with and without ACLF (31% vs. 20%, p=0.55 and 59% vs. 60%, p=0.72, respectively). Post-transplant survival was similar between patients with and without ACLF. This result was confirmed in the validation cohort. MELD-based organ allocation in the Eurotransplant region underestimates waitlist mortality in patients with ACLF in lower MELD ranges.

The Impact of Primary Liver Disease and Social Determinants in a Mixed Donor Liver Transplant Program: A Single-Center Analysis.

Organ allocation in liver transplantation (LT) remains imperfect. Periodic center reviews ensure programs transparently evaluate the impact of practice on access to transplantation, reflecting, in particular, patient (primary disease, social determinants) and program (deceased versus live donation) factors. Adult Ontario residents waitlisted for first LT at Toronto General Hospital from November 2012 to May 2019 were reviewed. Analyses were performed between distance to transplant center, income, education level, population density and primary liver disease, with LT, deceased donor liver transplant (DDLT), living donor liver transplant (LDLT), and delisting. Of 1735 listed patients, 549 were delisted (32%), while 1071 were transplanted (62%), with 819 DDLT recipients (76%) and 252 LDLT recipients (24%), while 115 (7%) remained actively listed at data census. On univariate analysis, DDLT recipients lived 30% closer (median 39.7 versus 60.6km; P<0.001), lived in more populous areas (median 8501.0 versus 6868.5 people in a 1-km radius; P<0.001), and resided in households that annually earned 10% less (median $92,643.17 versus $102,820.89 Canadian dollars; P<0.001) compared with LDLT recipients. These findings with population density and income differences between DDLT versus LDLT receival remained significant on multivariate modeling even when accounting for primary liver disease. Primary liver disease was a statistically significant factor on multivariate analyses in LT receival (P=0.001) as well as DDLT versus LDLT receival (P<0.001). Of patients listed for end-stage liver disease, more patients with autoimmune cholestatic liver diseases received LDLT (34%-41%) than DDLT (27%-30%); this contrasted with patients with noncholestatic diseases LDLT (8%-19%) versus DDLT (37%-59%) receival (P<0.001). Review of transplant allocation in a large mixed-donor North American liver transplant program demonstrates how patient social determinants and primary liver disease etiology continue to be significantly associated with ultimate transplantation.

A novel prognostic model to predict outcome of artificial liver support system treatment

The prognosis of Artificial liver support system (ALSS) for hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is hard to be expected, which results in multiple operations of ALSS and excessive consumption of plasma, increase in clinical cost. A total of 375 HBV-ACLF patients receiving ALSS treatment were randomly divided a train set and an independent test set. Logistic regression analysis was conducted and a decision tree was built based on 3-month survival as outcome. The ratio of total bilirubin before and after the first time of ALSS treatment was the most significant prognostic factor, we named it RPTB. Further, a decision tree based on the multivariate logistic regression model using CTP score and the RPTB was built, dividing patients into 3 main groups such as favorable prognosis group, moderate prognosis group and poor prognosis group. A clearly-presented and easily-understood decision tree was built with a good predictive value of prognosis in HBV-related ACLF patients after first-time ALSS treatment. It will help maximal the therapeutic value of ALSS treatment and may play an important role in organ allocation for liver transplantation in the future.

Editorial introductions.

Editorial introductions.

Assessing the Prediction Effect of Various Prognosis Model for 28-Day Mortality in Acute-on-Chronic Liver Failure Patients.

BackgroundAcute-on-chronic liver failure (ACLF) is an extremely clinical entity associated with short-term high mortality. The CLIF-SOFA score measures both hepatic and extrahepatic organ dysfunction and can discriminate significantly better between survivors and nonsurvivors compared to other methods. The MELD score is widely used for organ allocation in liver transplantation. Recent reports indicate that the PWR is a potential biomarker for predicting clinical outcomes. The ALBI score is a new score model for evaluating the severity of liver dysfunction. We aimed to compare these prognosis models to predict short-term mortality in ACLF patients.MethodsA retrospective analysis of 89 ACLF patients between 2015 and 2018 was performed. The receiver operating characteristic (ROC) curve was used to assess the power of four prognosis models for predicting 28-day mortality in patients with ACLF.ResultsThe ALBI score, MELD score and CLIF-SOFA score were significantly higher, and the PWR was slightly lower in nonsurviving ACLF patients than in surviving patients. The MELD score and ALBI score were positively correlated with the CLIF-SOFA score, while the PWR was inversely related to the CLIF-SOFA score. The area under the ROC curves (AUROCS) of the CLIF-SOFA score, PWR, ALBI score and MELD score were 0.804, 0.759, 0.710 and 0.670, respectively.ConclusionThe CLIF-SOFA score, PWR and ALBI score can better predict 28-day mortality in ACLF patients, but the MELD score has worse predictability. The CLIF-SOFA score is the best prognosis model among these models. PWR may be a simple and useful tool that can predict 28-day outcome.

Analysis of the organ allocation system for liver transplantation in Chile

In Chile, organ allocation for liver transplantation (LT) in adults is prioritized according to the MELD-Na score. Exceptions such as Hepatocellular Carcinoma (HCC) and other non-HCC exceptions receive a score called Operational MELD score. To evaluate the effectiveness of the MELD-Na score and the operational MELD score as a prioritization system for LT in Chile. Retrospective analysis of the waiting list (WL) of adult candidates (≥ 15 years) for elective LT in Chile from 2011 to 2017. The probability of leaving the WL, defined by death or contraindication for LT was compared in three groups: 1) Cirrhotic patients prioritized according to their real MELD-Na score (CPM), 2) HCC and 3) other non-HCC exceptions. We analyzed 730 candidates for LT, with a median age of 57 years, 431 (56%) were men. In the study period, 352 LT were performed (48%). The annual exit rate was significantly higher in the CPM group (45.5%) compared to HCC (33.1%) and non-HCC (29.3%), (p < 0.001). Post LT survival was 86% at 1 year and 85% at 5 years, without significant differences between groups. In the CPM group, post-transplant survival was significantly lower (p < 0.05) in patients with MELD-Na ≥ 30 at transplant (81% per year) compared to patients with patients with MELD-Na < 30 (91% per year). MELD-Na score can discriminate very well patients who have a higher risk of death in the short and medium term. However, the assignment of operational scores for situations of exception produces inequities in the allocation of organs for LT and must therefore be carefully adjusted.

The trials and tribulations of liver allocation

Allocation policies are necessary to ensure a fair distribution of a scarce resource. The goal of any liver transplant allocation policy is to achieve the best possible outcomes for the waiting list population, irrespective of the indication for transplant, whilst maximizing organ utilization. Organ allocation for liver transplantation has evolved from simple centre-based approaches driven by local issues, to complex, evidence-based algorithm prioritizing according to need. Despite the rapid evolution of allocation policies, there remain a number of challenges and new approaches are required to ensure transparency and equity on the decision-making process and the best possible outcomes for patients on the waiting list. New ways of modelling, together with novel outcome criteria, will be required to enable a dynamic adaptability of the allocation policies to the ever changing demographics of the donor population and the changing landscape of indications for transplantation.

Role of Molecular Biomarkers in Liver Transplantation for Hepatocellular Carcinoma.

Patient selection and organ allocation for liver transplantation (LT) in patients with hepatocellular carcinoma (HCC) relies predominantly on clinical parameters, such as tumor burden (ie, radiological imaging). Patients transplanted within Milan criteria have outstanding outcomes with a 5- and 10-year survival of 70% and 55%, respectively. Tumor recurrence after transplantion is rare in these patients (10%); however, treatment options upon recurrence are generally limited, and outcomes are poor. There are also several studies showing how a subgroup of patients with tumors outside the Milan criteria might achieve comparable outcomes to patients within Milan criteria. In other words, the size and number of tumor nodules does not always reflect tumor biology, which could be better captured using molecular proxies for cancer aggressiveness. Over the last decade, we have significantly improved our understanding of the molecular landscape of early stage HCC. This includes the development of molecular classification, identification of prognostic and mutational signatures, and potential mechanisms of hepatocarcinogenesis. Some molecular markers have already proven useful to predict tumor-related outcomes in HCC patients after LT. Most of these analyses are limited to tissue-derived biomarkers, which limits their implementation in clinical practice because tissue biopsy is not required for HCC diagnosis. Minimally invasive alternative tools, such as liquid biopsy, are being increasingly explored and could help to individualize risk stratification for patients with HCC who will benefit from LT despite being outside the accepted clinical criteria.

From the Editor’s desk…: May 2019

From the Editor’s desk…: May 2019

New organ allocation criteria in liver transplantation.

The organ allocation modality in the liver transplant represents a fundamental step for the correct success of the transplantation procedure. The practical effects deriving from the adoption of the organ allocation models do not imply only clinical repercussions but also concern important ethical aspects. Alongside the general principles of fairness, justice and transparency, the organ allocation models should be aimed at providing for each patient who waits for an organ, the possibility of accessing it, preserving and maximizing the outcome of the transplant in terms of survival and quality of life. Balancing successfully the clinical and ethical aspects in an allocation model is particularly difficult and probably not completely feasible. In this brief review, the general principles governing the different models of organ allocation in liver transplantation are addressed. A particular description of the decision-making process that led to the sharing in Italy of a new allocation model based on the concept of the transplant benefit is illustrated. In this model we have tried to combine the two fundamental principles that for many years have guided the choice of allocation models, respectively based on the criteria of urgency and utility.

Ethical Issues in Patients with Cirrhosis

To briefly summarize topical ethical issues in patients with cirrhosis. The “four quadrants” framework is ideally suited to address ethical issues in patients with cirrhosis. The presence of hepatic encephalopathy complicates any ethical analysis and stresses the importance of advanced directives and end of life planning, both of which appear to be poorly applied. Organ allocation in liver transplantation (LT) based on survival benefit, a “not unreasonable standard” to assess live donor LT (LDLT) in patients removed from the wait list, LT in patients with acute alcoholic hepatitis, and LT in undocumented immigrants are supported by sound ethical principles. Significant ethical issues remain challenging and unresolved for patients with cirrhosis. Further research must be done to assess how frequently ethical problems occur in individual patients. Clear, detailed policies, based on strong ethical platforms, must be developed to further address these significant ethical challenges.

Increased Level of Interleukin 6 Associates With Increased 90-Day and 1-Year Mortality in Patients With End-Stage Liver Disease

Organ allocation for liver transplantation is based on prognosis, using the model for end-stage liver disease (MELD) or MELD including serum sodium (MELD-Na) score. These scores do notconsider systemic inflammation and septic complications. Blood level of C-reactive protein(CRP), in addition to the MELD score, associates with mortality in patients with end-stage liver disease, whereas levels of interleukin 6 (IL6) have not been systematically studied. We performed a retrospective observational cohort study of 474 patients with end-stage liver disease (63.5% male; median age, 56.9 years), evaluated for liver transplantation in Germany, with at least 1 year of follow up. Data were collected on blood levels of CRP, IL6, and white blood cell count (WBC). Findings were analyzed in relation to mortality and compared with patients' MELD scores and MELD-Na scores. For survival analysis, the cohort was divided into quartiles of IL6, CRP, and WBC levels, as well as MELD scores. Log-rank test and the Cox proportional hazards regression model were used to compare the groups, and area under the receiver operating characteristic (AUROC) values were calculated. Blood levels of IL6 and MELD scores associated with mortality: none of the patients with levels of IL6 below the first quartile (below 5.3 pg/mL) died within 1 year. In contrast, 67.7% of the patients in the highest quartile of IL6 level (37.0 pg/mL or more) died within 1 year. MELD score also correlated with mortality: among patients with MELD scores below 8.7, 0.9% died within 1year, whereas in patients with MELD scores of 18.0 or more, 67.4% died within 1 year. The predictive value of level of IL6 (AUROC, 0.940) was higher than level of CRP (AUROC, 0.866) (P = .009) or WBC (AUROC, 0.773) (P < .001) for 90-day mortality. MELD scores associated with 90-day mortality (AUROC, 0.933) (P = .756) as did MELD-Na score (AUROC, 0.946) (P = .771). Level of IL6 associated with 1-year mortality (AUROC, 0.916) to a greater extent than liver synthesis or detoxification markers international normalized ratio (AUROC, 0.839) (P = .007) or bilirubin (AUROC 0.846) (P = .007). Level of IL6 was an independent, significant risk factor for mortality after adjustment for MELD score, MELD-Na score, level of CRP, or WBC. In a retrospective analysis, we found high blood levels of IL6 to associate with 90-day and 1-year mortality in patients with end-stage liver disease; its predictive value was comparable to that of MELD or MELD-Na score, and was higher than that of level of CRP or WBC. Further studies should be performed to confirm the results in different cohorts.

Dynamically weighted evolutionary ordinal neural network for solving an imbalanced liver transplantation problem.

Create an efficient decision-support model to assist medical experts in the process of organ allocation in liver transplantation. The mathematical model proposed here uses different sources of information to predict the probability of organ survival at different thresholds for each donor-recipient pair considered. Currently, this decision is mainly based on the Model for End-stage Liver Disease, which depends only on the severity of the recipient and obviates donor-recipient compatibility. We therefore propose to use information concerning the donor, the recipient and the surgery, with the objective of allocating the organ correctly. The database consists of information concerning transplants conducted in 7 different Spanish hospitals and the King's College Hospital (United Kingdom). The state of the patients is followed up for 12 months. We propose to treat the problem as an ordinal classification one, where we predict the organ survival at different thresholds: less than 15 days, between 15 and 90 days, between 90 and 365 days and more than 365 days. This discretization is intended to produce finer-grain survival information (compared with the common binary approach). However, it results in a highly imbalanced dataset in which more than 85% of cases belong to the last class. To solve this, we combine two approaches, a cost-sensitive evolutionary ordinal artificial neural network (ANN) (in which we propose to incorporate dynamic weights to make more emphasis on the worst classified classes) and an ordinal over-sampling technique (which adds virtual patterns to the minority classes and thus alleviates the imbalanced nature of the dataset). The results obtained by our proposal are promising and satisfactory, considering the overall accuracy, the ordering of the classes and the sensitivity of minority classes. In this sense, both the dynamic costs and the over-sampling technique improve the base results of the considered ANN-based method. Comparing our model with other state-of-the-art techniques in ordinal classification, competitive results can also be appreciated. The results achieved with this proposal improve the ones obtained by other state-of-the-art models: we were able to correctly predict more than 73% of the transplantation results, with a geometric mean of the sensitivities of 31.46%, which is much higher than the one obtained by other models. The combination of the proposed cost-sensitive evolutionary algorithm together with the application of an over-sampling technique improves the predictive capability of our model in a significant way (especially for minority classes), which can help the surgeons make more informed decisions about the most appropriate recipient for an specific donor organ, in order to maximize the probability of survival after the transplantation and therefore the fairness principle.

Impact of Inter-Laboratory Variability on Model of End-Stage Liver Disease (MELD) Score Calculation.

BACKGROUND The model for end-stage liver disease (MELD) is a laboratory-based scoring system for assessing the severity of liver disease. Since 16 December 2006, MELD-based organ allocation for liver transplantation (LT) has been established in Germany to prioritize the sickest patients. The present study was designed to evaluate the effect of using different laboratories on the calculated MELD score, despite the use of mandatory round-robin testing for comparable of inter-laboratory results. MATERIAL AND METHODS Blood samples were taken from 10 patients with liver disease. Bilirubin, creatinine, and INR were measured in 6 different laboratories. The patients' MELD scores were calculated and the inter-laboratory variability was compared. RESULTS The highest discrepancy between the laboratories was 5 MELD score points and the highest inter-laboratory difference for bilirubin, INR, and creatinine was 4.6, 1.2, and 0.99 mg/dl, respectively. Pairwise comparison of the laboratory values showed a significant inter-laboratory difference (p<0.05). CONCLUSIONS Results clearly demonstrate, for the first time, that liver allocation for LT in Germany is based on nationwide noncomparable laboratory readouts for the MELD score.

Organ allocation for liver transplantation: One size does not fill all.

See Article on Page 743 In response to a donor pool that is persistently insufficient for demand and broadening of indications for liver transplantation, European countries have developed different approaches to organ allocation, taking into account local legislation, organ donation rates, and indications for liver transplantation.1 In their article in Liver Transplantation, Schrem et al.2 reported on the development and validation of a new prognostic model for the prediction of 90‐day mortality after liver transplantation. Developed in a German transplant center, it was validated in Germany and the United Kingdom. The model performed well in the German cohort, with strong predictive ability, but it failed validation in the English cohort. The results of this study confirm the common disappointment within the transplant community on the impossibility of applying the same prognostic model for liver transplantation in different countries, with different health care systems and allocation policies. Therefore, it is not surprising that the model developed in Germany was not able to predict the mortality rate in the United Kingdom. The liver allocation system is radically different in Germany from that in the United Kingdom: Germany is part of Eurotransplant, where allocation is governed by the Eurotransplant Liver Allocation System. This international collaboration is based on medical and logistical criteria with modifications according to the different national laws.3 In Germany, as well as in the other 3 countries of Eurotransplant (Belgium, the Netherlands, and Luxembourg), allocation is patient‐oriented and based on urgency, using the Model for End‐Stage Liver Disease score to prioritize patients on the waiting list. Conversely, in the United Kingdom, liver allocation is center‐based with a national allocation scheme and with donor areas allocated to each center based on the number of new registrations of prospective candidates; and within each center, the priority is based on United Kingdom Model for End‐Stage Liver Disease4 scores and on the decision of the transplant professionals involved.5 The development of the new German prognostic model would have decreased the 90‐day survival benefit if applied to the United Kingdom, whereas it would have had a beneficial effect in German transplant centers. When developing allocation algorithms, a crucial step should be matching donor and recipient risk factors in order to maximize the benefit and to avoid matching with negative impact on posttransplant outcomes. Therefore, if profound differences exist between 2 countries in terms of donor characteristics and candidate clinical severity, it is clear that a model created in one setting will not fit when applied to another one. The importance of uniformity of clinical variables when applying allocation scores to other countries is reflected2 in that only 2 out of the 10 clinical variables used for the new liver allocation score had a significant influence on 90‐day mortality in the United Kingdom cohort, whereas all 10 variables had independent significant influences on 90‐day mortality in the 2 German cohorts. The impracticality of adopting the same allocation scheme for different countries should reinforce the concept that each country or region may need to develop their own predictive model for organ allocation. This is the case in Italy where a critical revision of the current liver allocation policy was recently prepared after a national consensus conference process that involved transplant surgeons and transplant hepatologists. A new national model that blends together the principles of urgency, utility, and transplant benefit has been developed based on current scientific evidence.6 Again, this system of allocation would be hard to translate to other countries, due to different population characteristics, disease burden, and geography that each country or consortium has.7 Lastly, despite some acknowledged limitations of the study by Schrem et al.,2 such as the retrospective design and the lack of information on potentially relevant prognostic variables (ie, graft steatosis), the authors properly pointed out that because allocation schemes offer clinicians schemes, and not rules, there is no obligation for the transplant professional to accept a liver offered for a specific patient. However, in an urgency‐based allocation system, the competition between transplant centers is increased due to the pressure to accept the organ offered for a patient even if the matching between donor and recipient is not optimal. A strong effort should be made by the transplant community to define national prognostic models able to properly optimize the use of a scarce resource, by using balanced principles of urgency and equity, and integrating them with transplant benefit, which is easily made into a mathematical model but difficult to realize in the daily clinical practice when up to 20% of patients still die on the waiting list.

The impact of donor liver graft quality on postoperative outcome in liver transplant recipients. A single centre experience.

The Donor Risk Index (DRI) has become a universal score for organ allocation in liver transplantation (LT) worldwide. The aim of this study was to evaluate the impact of liver graft quality measured by DRI, CIT, WIT and donor age on intraoperative hemodynamics (reperfusion syndrome) and early postoperative outcome, defined as initial graft poor function (within 3 days of LT), of deceased donor liver transplant (DDLT) recipients. Secondary end-points were the assessment of the impact of graft quality on the intraoperative and postoperative day 1 hemostasis (evaluated using ROTEM assay). We retrospectively analyzed 135 patients who underwent deceased-donor LT between January 2013 and December 2014. Patient demographic data (age, sex, cause of End-Stage Liver Disease), preoperative paraclinical data (total bilirubin, creatinine, serum sodium), severity of liver disease scores (Model for End-Stage Liver Disease - MELD and MELD-sodium), intraoperative blood loss and blood products transfusion, incidence of post reperfusion syndrome, postoperative biochemical data (including total bilirubin, hepatic transaminases, lactate levels) and outcome (initial graft poor function diagnosis) were noted. Donor characteristics including DRI, CIT, WIT and donor age were noted. Coagulation was assessed by rotational thromboelastometry (ROTEM) after reperfusion of the graft and on postoperative day 1 in order to determine the effects of liver graft quality on hemostasis. Donor age has significantly correlated with decreased derived ROTEM parameters time to the maximum velocity of clot formation - MaxVt (p = 0.000), area under the curve (AUC) (p = 0.008) and maximum clot elasticity (MCE) (p = 0.018) although no difference in transfusion requirements has been observed. A longer CIT was associated with an increase in AST and ALT observed during the early postoperative period: day 1 ALT (p = 0.032) and AST (p = 0.008), day 2 ALT (p = 0.001) and AST (p = 0.001) and day 3 AST (p = 0.010) and ALT (p = 0.001). Higher DRI correlated with higher bilirubin levels measured on postoperative day 1 (p = 0.027) and 2 (p = 0.001). Patients who developed initial graft poor function received liver grafts from older donors (p = 0.05) with a higher DRI (p = 0.002). Our results suggest a significant impact of donor age and DRI on perioperative coagulation kinetics that may be a result of initial graft poor function. Although CIT and DRI correlated with a more severe cholestasis and hepatocitolysis during the early postoperative period these seems to be short-lived.

A Multistep, Consensus-Based Approach to Organ Allocation in Liver Transplantation: Toward a “Blended Principle Model”

Since Italian liver allocation policy was last revised (in 2012), relevant critical issues and conceptual advances have emerged, calling for significant improvements. We report the results of a national consensus conference process, promoted by the Italian College of Liver Transplant Surgeons (for the Italian Society for Organ Transplantation) and the Italian Association for the Study of the Liver, to review the best indicators for orienting organ allocation policies based on principles of urgency, utility, and transplant benefit in the light of current scientific evidence. MELD exceptions and hepatocellular carcinoma were analyzed to construct a transplantation priority algorithm, given the inequity of a purely MELD-based system for governing organ allocation. Working groups of transplant surgeons and hepatologists prepared a list of statements for each topic, scoring their quality of evidence and strength of recommendation using the Centers for Disease Control grading system. A jury of Italian transplant surgeons, hepatologists, intensivists, infectious disease specialists, epidemiologists, representatives of patients' associations and organ-sharing organizations, transplant coordinators, and ethicists voted on and validated the proposed statements. After carefully reviewing the statements, a critical proposal for revising Italy's current liver allocation policy was prepared jointly by transplant surgeons and hepatologists.

The Evolution of Organ Allocation for Liver Transplantation: Tackling Geographic Disparity Through Broader Sharing.

The liver transplant allocation system has evolved to a ranking system of “sickest-first” system based on objective criteria. Yet, organs continue to be distributed first within OPOs and regions that are largely based on historical practice patterns related to kidney transplantation and were never designed to minimize waitlist death or equalize opportunity for liver transplant. The current proposal is a move to enhance survival though the application of modern mathematical techniques to optimize liver distribution. Like MELDbased allocation, it will never be perfect and should be continually evaluated and revised. However, the disparity in access, which favors those residing in or able to travel to privileged areas, to the detriment of the patients dying on the list in underserved areas, is simply not defensible in 2015.