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Predicting survival after liver transplantation based on pre-transplant MELD score: a systematic review of the literature.

ABSTRACT: The model for end-stage liver disease (MELD) score is used to stratify candidates for liver transplantation based on objective measures of disease severity. MELD has been validated as a predictor of wait-list mortality in transplantation candidates and has been postulated as a predictor of post-transplant survival. The purpose of this study was to examine the predictive value of the pre-transplantation MELD score on post-transplant survival from relevant existing studies. A systematic review and critical appraisal was performed using Cochrane guidelines. PubMed, the Cochrane Library, Embase, and Web of Science were searched for articles published in the English language since 2005 using a structured search strategy. There were 3058 discrete citations identified and screened for possible inclusion. Any study examining the relationship between pre-transplant MELD and post-transplant survival in the general transplant population was included. Thirty-seven studies met these criteria and were included in the review. Studies were all case series that typically involved stratified analyses of survival by MELD. They represented 15 countries and a total of 53,691 patients. There was significant clinical heterogeneity in patient populations across studies, which precluded performance of a meta-analysis. In 15 studies, no statistically significant association between MELD and post-transplant survival was found. In the remaining 22, some association was found. Eleven studies also measured predictive ability with c-statistics. Values were below 0.7 in all but two studies, suggesting poor predictive value. In summary, while the majority of studies reported an association between pre-transplantation MELD score and post-transplant survival, they represented a low level of evidence. Therefore, their findings should be interpreted conservatively.

SUBMITTER: Klein KB

PROVIDER: S-EPMC3861188 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Predicting survival after liver transplantation based on pre-transplant MELD score: a systematic review of the literature.

Klein Kristin B KB Stafinski Taenia D TD Menon Devidas D

PloS one 20131212 12

The model for end-stage liver disease (MELD) score is used to stratify candidates for liver transplantation based on objective measures of disease severity. MELD has been validated as a predictor of wait-list mortality in transplantation candidates and has been postulated as a predictor of post-transplant survival. The purpose of this study was to examine the predictive value of the pre-transplantation MELD score on post-transplant survival from relevant existing studies. A systematic review and ...[more]

PMID: 24349010

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Project description:ImportanceLiver allocation is determined by the model for end-stage liver disease (MELD), a scoring system based on 4 laboratory measurements. During the MELD era, sex disparities in liver transplant have increased and there are no modifications to MELD based on sex.ObjectiveTo use laboratory values stored in electronic health records to describe population-level sex differences in all MELD laboratory values (in healthy individuals and patients with liver disease) and propose a sex adjustment.Design, setting, and participantsA retrospective cohort study was conducted from March 2019 to April 2020 to evaluate sex differences in laboratory values in liver transplant patients, patients with liver disease who did not undergo transplant, and healthy controls. Primary analyses were conducted in Vanderbilt University Medical Center (VUMC)'s deidentified electronic health record system. Replication analyses were conducted in the All of Us Research Program. Simulations of a sex-adjusted sodium-adjusted MELD (MELDNa) score were completed using liver transplant waiting list data from the liver simulated allocation modeling system. Patients who regularly used VUMC with measurements for any MELDNa component laboratory were included in the analyses. Analysis took place from November 2019 to March 2021.ExposuresElectronic health record-reported sex.Main outcomes and measureCreatinine, bilirubin, international normalized ratio, and sodium levels.ResultsThe VUMC sample was composed of 623 931 individuals (359 976 [57.7%] female) with a median (IQR) age of 44 (23-61) years. All component MELDNa laboratory values and calculated MELDNa scores yielded significant sex differences within VUMC (mean [SD] creatinine: male, 0.99 [0.39] mg/dL; female, 0.79 [0.30] mg/dL; P < .001; bilirubin: male, 0.76 [0.83] mg/dL; female, 0.58 [0.64] mg/dL; P < .001; international normalized ratio of prothrombin rate: male, 1.24 [0.42]; female, 1.20 [0.40]; P < .001; sodium: male, 139.00 [2.36] mEq/L; female, 139.03 [2.28] mEq/L; P < .001), resulting in MELDNa scoring that disadvantaged female individuals. This pattern persisted when the sample was divided into healthy controls, individuals with liver disease who did not undergo transplant, and patients who did undergo liver transplant. Female transplant patients had a greater number of decompensation traits (mean [SD]: male, 1.34 [1.11]; female, 1.60 [1.09]; P = .005), despite having lower MELDNa scores (mean [SD]: male, 21.72 [6.11]; female, 20.21 [6.15]; P = .005), indicating MELDNa scores are not accurately representing disease severity in female individuals. In simulations, the sex-adjusted MELDNa score modestly increased female transplant rate and decreased overall death.Conclusions and relevanceThese results demonstrate pervasive sex differences in all laboratory values used in MELDNa scoring and highlight the need and utility of a sex-adjustment to the MELDNa protocol.

Project description:BackgroundControversy exists regarding the best predictive model of liver transplant waiting list (WL) mortality. Models for end-stage liver disease-glomerular filtration rate assessment in liver disease (MELD-GRAIL) and MELD-GRAIL-Na were recently described to provide better prognostication, particularly in females. We evaluated the performance of these scores compared to MELD and MELD-Na.MethodsConsecutive patients with cirrhosis waitlisted for liver transplant from 1998 to 2017 were examined in this single-center study. The primary outcome was 90-d WL mortality. MELD, MELD-Na, MELD-GRAIL, and MELD-GRAIL-Na at the time of WL registration were compared. Model discrimination was assessed with area under the receiver operating characteristic curves and Harrell's C-index after fitting Cox models. Model calibration was examined with Grønnesby and Borgan's modification of the Hosmer-Lemeshow formula and by comparing predicted/observed outcomes across model strata.ResultsThe study population comprised 1108 patients with a median age of 53.5 (interquartile range 48-59) y and male predominance (74.9%). All models had excellent areas under the receiver operating characteristic curves for the primary outcome (MELD 0.89, MELD-Na 0.91, MELD-GRAIL 0.89, MELD-GRAIL-Na 0.89; all comparisons P > 0.05). Youden index cutoffs for 90-d mortality were as follows: MELD, 19; MELD-Na, 22; MELD-GRAIL, 18; and MELD-GRAIL-Na, 17. Variables associated with 90-d mortality on multivariable Cox regression were sodium, bilirubin, creatinine, and international normalized ratio. There were no differences in model discrimination using Harrell's C-index. All models were well calibrated; however, divergence between observed and predicted mortality was noted with scores ≥25.ConclusionThere were no demonstrable differences in discrimination or calibration of GRAIL-based models compared with MELD or MELD-Na in our cohort. This suggests that GRAIL-based models may not have meaningful improvements in discriminatory ability when applied to other settings.

Project description:Background & aimsLiver transplant priority in the US and Europe follows the 'sickest-first' principle. However, for patients with hepatocellular carcinoma (HCC), priority is based on binary tumor criteria to expedite transplant for patients with 'acceptable' post-transplant outcomes. Newer risk scores developed to overcome limitations of these binary criteria are insufficient to be used for waitlist priority as they focus solely on HCC-related pre-transplant variables. We sought to develop a risk score to predict post-transplant survival for patients using HCC- and non-HCC-related variables.MethodsWe performed a retrospective cohort study using national registry data on adult deceased-donor liver transplant (DDLT) recipients with HCC from 2/27/02-12/31/18. We fit Cox regression models focused on 5- and 10-year survival to estimate beta coefficients for a risk score using manual variable selection. We then calculated absolute predicted survival time and compared it to available risk scores.ResultsAmong 6,502 adult DDLT recipients with HCC, 11 variables were selected in the final model. The AUCs at 5- and 10-years were: 0.62, 95% CI 0.57-0.67 and 0.65, 95% CI 0.58-0.72, which was not statistically significantly different to the Metroticket and HALT-HCC scores. The LiTES-HCC score was able to discriminate patients based on post-transplant survival among those meeting Milan and UCSF criteria.ConclusionWe developed and validated a risk score to predict post-transplant survival for patients with HCC. By including HCC- and non-HCC-related variables (e.g., age, chronic kidney disease), this score could allow transplant professionals to prioritize patients with HCC in terms of predicted survival. In the future, this score could be integrated into survival benefit-based models to lead to meaningful improvements in life-years at the population level.Lay summaryWe created a risk score to predict how long patients with liver cancer will live if they get a liver transplant. In the future, this could be used to decide which waitlisted patients should get the next transplant.

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Predicting survival after liver transplantation based on pre-transplant MELD score: a systematic review of the literature.

Publications

Predicting survival after liver transplantation based on pre-transplant MELD score: a systematic review of the literature.

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