MELD 3.0: The Model for End-Stage Liver Disease Updated for the Modern Era.
MELD 3.0: The Model for End-Stage Liver Disease Updated for the Modern Era.
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DOI:
10.1053/j.gastro.2021.08.050
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发表时间:
2021-12
期刊:
影响因子:
29.4
通讯作者:
Kwong AJ
中科院分区:
文献类型:
--
作者:
Kim WR;Mannalithara A;Heimbach JK;Kamath PS;Asrani SK;Biggins SW;Wood NL;Gentry SE;Kwong AJ
The model for end-stage liver disease (MELD) has been established as a reliable indicator of short-term survival in patients with end-stage liver disease. The current version (MELDNa), consisting of INR and serum bilirubin, creatinine, and sodium, has been used to determine organ allocation priorities for liver transplantation in the United States (US). The objective was to optimize MELD further by taking into account additional variables and updating coefficients with contemporary data. All candidates registered on the liver transplant waitlist in the US national registry from Jan 2016 – Dec 2018 were included. Uni- and multivariable Cox models were developed to predict survival up to 90 days after waitlist registration. Model fit was tested using the concordance statistic and reclassification, and the liver simulated allocation model (LSAM) was used to estimate the impact of replacing MELDNa with the new model. The final multivariable model was characterized by (1) additional variables of female sex and serum albumin, (2) interactions between bilirubin and sodium and between albumin and creatinine, and (3) an upper bound for creatinine at 3.0mg/dL. The final model (MELD 3.0, henceforth), had better discrimination than MELDNa (concordance statistic 0.869 versus 0.862, p<0.01). Importantly, MELD 3.0 correctly reclassified a net of 8.8% of decedents to a higher MELD tier, affording them a meaningfully higher chance of transplant, particularly in women. In the LSAM analysis, MELD 3.0 resulted in fewer waitlist deaths compared to MELDNa (7,788 versus 7,850, p=0.02). MELD 3.0 affords more accurate mortality prediction in general than MELDNa and addresses determinants of waitlist outcomes including the sex disparity.
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