Identifying an Optimal Liver Frailty Index Cutoff to Predict Waitlist Mortality in Liver Transplant Candidates.

Journal Article (Journal Article;Multicenter Study)

BACKGROUND AND AIMS: Frailty, as measured by the Liver Frailty Index (LFI), is associated with liver transplant (LT) waitlist mortality. We sought to identify an optimal LFI cutoff that predicts waitlist mortality. APPROACH AND RESULTS: Adults with cirrhosis awaiting LT without hepatocellular carcinoma at nine LT centers in the United States with LFI assessments were included. Multivariable competing risk analysis assessed the relationship between LFI and waitlist mortality. We identified a single LFI cutoff by evaluating the fit of the competing risk models, searching for the cutoff that gave the best model fit (as judged by the pseudo-log-likelihood). We ascertained the area under the curve (AUC) in an analysis of waitlist mortality to find optimal cutoffs at 3, 6, or 12 months. We used the AUC to compare the discriminative ability of LFI+Model for End Stage Liver Disease-sodium (MELDNa) versus MELDNa alone in 3-month waitlist mortality prediction. Of 1,405 patients, 37 (3%), 82 (6%), and 135 (10%) experienced waitlist mortality at 3, 6, and 12 months, respectively. LFI was predictive of waitlist mortality across a broad LFI range: 3.7-5.2. We identified an optimal LFI cutoff of 4.4 (95% confidence interval [CI], 4.0-4.8) for 3-month mortality, 4.2 (95% CI, 4.1-4.4) for 6-month mortality, and 4.2 (95% CI, 4.1-4.4) for 12-month mortality. The AUC for prediction of 3-month mortality for MELDNa was 0.73; the addition of LFI to MELDNa improved the AUC to 0.79. CONCLUSIONS: LFI is predictive of waitlist mortality across a wide spectrum of LFI values. The optimal LFI cutoff for waitlist mortality was 4.4 at 3 months and 4.2 at 6 and 12 months. The discriminative performance of LFI+MELDNa was greater than MELDNa alone. Our data suggest that incorporating LFI with MELDNa can more accurately represent waitlist mortality in LT candidates.

Full Text

Duke Authors

Cited Authors

  • Kardashian, A; Ge, J; McCulloch, CE; Kappus, MR; Dunn, MA; Duarte-Rojo, A; Volk, ML; Rahimi, RS; Verna, EC; Ganger, DR; Ladner, D; Dodge, JL; Boyarsky, B; McAdams-DeMarco, M; Segev, DL; Lai, JC

Published Date

  • March 2021

Published In

Volume / Issue

  • 73 / 3

Start / End Page

  • 1132 - 1139

PubMed ID

  • 32491208

Pubmed Central ID

  • PMC7710552

Electronic International Standard Serial Number (EISSN)

  • 1527-3350

Digital Object Identifier (DOI)

  • 10.1002/hep.31406

Language

  • eng

Conference Location

  • United States