Ani Kardashian1, Jin Ge1, Charles E McCulloch2, Matthew R Kappus3, Michael A Dunn4, Andres Duarte-Rojo4,5, Michael L Volk6, Robert S Rahimi7, Elizabeth C Verna8, Daniel R Ganger9, Daniela Ladner10, Jennifer L Dodge11, Brian Boyarsky12, Mara McAdams-DeMarco12,13, Dorry L Segev12, Jennifer C Lai1. 1. Division of Gastroenterology and Hepatology, Department of Medicine, University of California, San Francisco, San Francisco, CA. 2. Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA. 3. Division of Gastroenterology, Department of Medicine, Duke University School of Medicine, Durham, NC. 4. Center for Liver Diseases, Thomas A. Starzl Transplantation Institute, and Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA. 5. Division of Gastroenterology & Hepatology, University of Arkansas for Medical Sciences, Little Rock, AR. 6. Division of Gastroenterology and Hepatology, and Transplantation Institute, Loma Linda University Health, Loma Linda, CA. 7. Annette C. and Harold C. Simmons Transplant Institute, Baylor University Medical Center, Baylor Scott and White, Dallas, TX. 8. Center for Liver Disease and Transplantation, Columbia University Medical Center, New York, NY. 9. Division of Gastroenterology and Hepatology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL. 10. Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL. 11. Department of Surgery, Division of Transplant Surgery, University of California, San Francisco, San Francisco, CA. 12. Department of Surgery, Johns Hopkins School of Medicine, Baltimore, MD. 13. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Abstract
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.
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.
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