Disease-specific waitlist outcomes in liver transplantation - a retrospective study

Superiority of the new sex-adjusted models to remove the female disadvantage restoring equity in liver transplant allocation

BACKGROUND AND AIMS

Model for End-stage Liver Disease (MELD) and MELDNa are used worldwide to guide graft allocation in liver transplantation (LT). Evidence exists that females are penalized in the present allocation systems. Recently, new sex-adjusted scores have been proposed with improved performance respect to MELD and MELDNa. GEMA-Na, MELD 3.0, and sex-adjusted MELDNa were developed to improve the 90-day dropout prediction from the list. The present study aimed at evaluating the accuracy and calibration of these scores in an Italian setting.

METHODS

The primary outcome of the present study was the dropout from the list up to 90 days because of death or clinical deterioration. We retrospectively analysed data from 855 adults enlisted for liver transplantation in the Lazio region (Italy) (2012-2018). Ninety-day prediction of GEMA-Na, MELD 3.0 and sex-adjusted MELDNa with respect to MELD and MELDNa was analysed. Brier score and Brier Skill score were used for accuracy, and the Greenwood-Nam-D'Agostino test was used to evaluate the calibration of the models.

RESULTS

GEMA-Na (concordance = .82, 95% CI = .75-.89), MELD 3.0 (concordance = .81, 95% CI = .74-.87) and sex-adjusted MELDNa (concordance = .81, 95% CI = .74-.88) showed the best 90-day dropout prediction. GEMA-Na showed a higher increase in accuracy with respect to MELD (p = .03). No superiority was shown with respect to MELDNa. All the tested scores showed a good calibration of the models. Using GEMA-Na instead of MELD would potentially save one in nine dropouts and could save one dropout per 285 patients listed.

CONCLUSIONS

Validation and reclassification of the sex-adjusted score GEMA-Na confirm its superiority in predicting short-term dropout also in an Italian setting when compared with MELD.

Liver Transplantation for Primary Sclerosing Cholangitis (PSC) With or Without Inflammatory Bowel Disease (IBD)-A European Society of Organ Transplantation (ESOT) Consensus Statement

Primary sclerosing cholangitis (PSC) is the classical hepatobiliary manifestation of inflammatory bowel disease (IBD) and a lead indication for liver transplantation (LT) in the western world. In this article, we present a Consensus Statement on LT practice, developed by a dedicated Guidelines' Taskforce of the European Society of Organ Transplantation (ESOT). The overarching goal is to provide practical guidance on commonly debated topics, including indications and timing of LT, management of bile duct stenosis in patients on the transplant waiting list, technical aspects of transplantation, immunosuppressive strategies post-transplant, timing and extension of intestinal resection and futility criteria for re-transplantation.

Changings and Challenges in Liver Transplantation for Nonalcoholic Fatty Liver Disease/Steatohepatitis

Liver transplantation for nonalcoholic fatty liver disease/steatohepatitis (NAFLD/NASH) is increasing rapidly worldwide. Compared with alcohol and viral-related liver disease, NAFLD/NASH is more frequently associated with a systemic metabolic syndrome, which significantly affects other organs, requiring multidisciplinary management, in all phases of liver transplant.

Liver Transplantation for the Nonhepatologist

Liver transplantation (LT) is a life-saving and evidence-based intervention for patients with acute liver failure and chronic end-stage liver disease. Significant progress has been made in advancing pre-LT management, transplant techniques, post-LT long-term care, and immunosuppression regimes. However, as rates of DC continue to increase, causes of liver disease and indications for LT continue to be investigated to ensure equity and further improve liver allocation models, waitlist outcomes, and post-LT outcomes for all patient populations.

Liver transplantation for non-alcoholic fatty liver disease: indications and post-transplant management

Non-alcoholic fatty liver disease (NAFLD) is currently the fastest growing indication to liver transplantation (LT) in Western Countries, both for end stage liver disease and hepatocellular carcinoma. NAFLD/non-alcoholic steatohepatitis (NASH) is often expression of a systemic metabolic syndrome; therefore, NAFLD/NASH patients require a multidisciplinary approach for a proper pre-surgical evaluation, which is important to achieve a post-transplant outcome comparable to that of other indications to LT. NAFLD/NASH patients are also at higher risk of post-transplant cardiovascular events, diabetes, dyslipidemia, obesity, renal impairment and recurrent NASH. Lifestyle modifications, included diet and physical activity, are key to improve survival and quality of life after transplantation. A tailored immunosuppressive regimen may be proposed in selected patients. Development of new drugs for the treatment of recurrent NASH is awaited.

Metabolic mechanisms for and treatment of NAFLD or NASH occurring after liver transplantation

The rising tide of non-alcoholic fatty liver disease (NAFLD) associated with the obesity epidemic is a major health concern worldwide. NAFLD - specifically its more advanced form, non-alcoholic steatohepatitis (NASH)-related cirrhosis - is now the fastest growing indication for liver transplantation in the USA and Europe. Although the short-term and mid-term overall survival rates of patients who receive a liver transplant for NASH-related cirrhosis are essentially similar to those of patients who receive a transplant for other liver indications, recipients with NASH-related cirrhosis have an increased risk of waiting-list mortality and of developing recurrent liver disease and cardiometabolic complications in the longer term after liver transplantation. This Review provides a brief overview of the epidemiology of NAFLD and NASH and the occurrence of NAFLD or NASH in patients after liver transplantation for NASH and other liver indications. It also discusses the putative metabolic mechanisms underlying the emergence of NAFLD or NASH after liver transplantation as well as optimal therapeutic approaches for recipients of liver transplants, including the management of cardiometabolic comorbidities, tailored immunosuppression, lifestyle changes and pharmacotherapy for NAFLD.

Use of neural network models to predict liver transplantation waitlist mortality

Current liver transplantation (LT) organ allocation relies on Model for End-Stage Liver Disease-sodium scores to predict mortality in patients awaiting LT. This study aims to develop neural network (NN) models that more accurately predict LT waitlist mortality. The study evaluates patients listed for LT between February 27, 2002, and June 30, 2021, using the Organ Procurement and Transplantation Network/United Network for Organ Sharing registry. We excluded patients listed with Model for End-Stage Liver Disease (MELD) exception scores and those listed for multiorgan transplant, except for liver-kidney transplant. A subset of data from the waiting list was used to create a mortality prediction model at 90 days after listing with 105,140 patients. A total of 28 variables were selected for model creation. The data were split using random sampling into training, validation, and test data sets in a 60:20:20 ratio. The performance of the model was assessed using area under the receiver operating curve (AUC-ROC) and area under the precision-recall curve (AUC-PR). AUC-ROC for 90-day mortality was 0.936 (95% confidence interval [CI], 0.934-0.937), and AUC-PR was 0.758 (95% CI, 0.754-0.762). The NN 90-day mortality model outperformed MELD-based models for both AUC-ROC and AUC-PR. The 90-day mortality model specifically identified more waitlist deaths with a higher recall (sensitivity) of 0.807 (95% CI, 0.803-0.811) versus 0.413 (95% CI, 0.409-0.418; p < 0.001). The performance metrics were compared by breaking the test data set into multiple patient subsets by ethnicity, gender, region, age, diagnosis group, and year of listing. The NN 90-day mortality model outperformed MELD-based models across all subsets in predicting mortality. In conclusion, organ allocation based on NN modeling has the potential to decrease waitlist mortality and lead to more equitable allocation systems in LT.