Society: AASLD
Background: Organ allocation based on the principles of urgency vs utility presents an ethical conundrum given the scarcity of liver grafts. The current Model for End-Stage Liver Disease (MELD) score prioritizes the sickest patients but fails to consider potential additional life-years gained from liver transplant (LT). We aimed to develop a new algorithm for equitable prioritization of liver grafts.
Methods: Using OPTN/UNOS data up to December 2021, we developed a robust model to estimate LT survival benefit defined as extra years of life that a candidate can achieve with LT versus remaining on the waitlist (life-years from transplant [LYFTs]). Weibull regression model was fitted using recipient-only characteristics at waitlist registration. The model was manually built based on a-priori clinical knowledge and flexible splines and interaction terms were generated for 86 estimated parameters. The model predicted the marginal median life expectancies of a patient under the counterfactual circumstances of receiving LT vs remaining waitlisted, and the LYFT score for the patient was calculated as the difference between life expectancy after LT vs waitlist. We proposed a novel score (MoNaLISA: Maximization Of Net Liver Survival benefit and medical Acuity) as the geometric average of the LYFT and MELD score which conceptually balances principles of utility (LYFT) and urgency (MELD). Monte Carlo simulations with bootstrap resampling were conducted to assess the impact of (i) MELD, MELD-Na, and MELD 3.0 score, (ii) MaxLYFT which prioritizes recipients by LYFT scores to maximize LT survival benefit at a population level, (iii) MoNaLISA score.
Results: 219,384 adult LT candidates were included in complete-case analyses with 1.64 million person-years follow-up. The model exhibited excellent goodness-of-fit and Harrell’s C-index of 0.784 (Figure 1). The model also affirmed numerous “clinically-expected” statistical interactions. For example, age was an important effect modifier, as the gain in life expectancy after LT was generally lesser for older recipients (predicted LYFT of 23.1 years for a recipient aged 30 years vs LYFT of 13.8 years for a recipient aged 55 years). Through resampling-based simulations, MELD, MELD-Na, MELD 3.0, MoNaLISA and MaxLYFT respectively yielded 9.5 vs 12.8 vs 12.9 vs 14.2 and 14.5 additional years-of-life per liver graft. Interestingly, MoNaLISA had a negligible adverse impact on 6-month waitlist mortality (22.5%) vs MELD schemes (21.9%-22.6%). MaxLYFT, unsurprisingly, had the highest 6-month waitlist mortality (27.8%) (Figure 2).
Conclusion: We present a novel liver allocation score that maximizes LT survival benefit while minimizing 6-month waitlist mortality. Assuming 13,000 waitlist registrations and 7,000 LTs occur annually in the USA, MoNaLISA adds 9,800 life-years with a negligible increase in waitlist deaths.

Figure 1: Goodness-of-fit of the LYFT survival model across various clinical subgroups, showing predicted survivorship versus observed Kaplan-Meier survival curves
Figure 2: Comparison between MELD versus proposed MaxLYFT and MONALISA allocation schemes
Objective: To compare waitlist mortality in older ( ≥ 65 years) and younger patients (18-64 years) with acute on chronic liver failure (ACLF) and identify independent risk factors. In addition, we also wanted to compare 90-day and 1-year patient survival (PS) following liver transplant (LT) in older and younger patients.
Methods: All older and younger adults who underwent LT for ACLF (using the European Association for the Study of Liver-Chronic Liver Failure (EASL-CLIF) Criteria) between 2005-2021 were identified using the UNOS database.We excluded those listed with status 1, 1A, or 1B, multi-organ transplant and living donor transplant. Unadjusted KM survival curves were used to evaluate patient survival (PS). The Cox proportional hazards (CPH) regression model was used to evaluate the risk factors for survival. We started with univariate analysis, followed by multivariate analysis.
Results: 4313 older patients were listed and 2142 were transplanted with ACLF. During the same period, 26,628 younger patients were listed and 16,931 were transplanted with ACLF. Older patients were more likely to die or be removed from the waitlist at 30-days compared to younger patients (20.4% vs 16.7%, P < 0.0001) (Figure 1). Older patients had significantly higher wait-list mortality across all grades of ACLF but were more pronounced in ACLF-2 (23.7% vs 14.8%, P <0.0001 and ACLF-3 (43.3% vs 29.9 %, P < 0.0001). On multivariable competing risk analysis age (HR 1.04, 95% CI 1.017-1.07), female sex ( HR 1.22, 95% CI 1.06-1.42), MELD-Na score (OR 1.09, 95% CI 1.08-1.1), hepatic encephalopathy grades 1-2 ( HR 1.36, 95% CI 1.10-1.68), grades 3/4 ( HR 1.51, 95% CI 1.19-1.92) and respiratory failure (OR 2.64, 95% CI 2.15-3.23) were risk factors for increased waitlist mortality in older patients, while higher albumin (HR 0.82, 95% CI 0.74-0.90) and black race ( HR 0.65, 95% CI 0.50-0.93 compared to whites) were associated with lower mortality (Table 1).
Post LT- survival: 90- day (P=0.0003, figure 2) and 1-year (P<0.0001, Figure 3) PS in older patients were lower than younger patients. Older patients with ACLF-1 had similar 90-day PS compared to younger patients with ACLF-1 (P = 0.46), but PS were significantly lower in ACLF grades 2 and 3. Similarly, 1-year PS was lower in older patients across ACLF grades (Figure 3).
Conclusion
Older patients (> 65 years) with ACLF have significantly higher waitlist mortality and lower post-LT survival than younger patients.

