American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons | 2021
Joint modelling of liver transplant candidates outperforms the model for end-stage liver disease: The effect of disease development over time on patient outcome.
Abstract
Liver function is measured regularly in liver transplantation (LT) candidates. Currently, these previous disease development data are not used for survival prediction. By constructing and validating joint models (JMs), we aimed to predict outcome based on all available data, using both disease severity and its rate of change over time. Adult LT candidates listed in Eurotransplant between 2007-2018 (n=16,283) and UNOS between 2016-2019 (n=30,533) were included. Patients with acute liver failure, exception points or priority status were excluded. Longitudinal MELD(-Na) data was modeled using spline-based mixed effects. Waiting list survival was modeled with Cox proportional hazards models. The JMs combined the longitudinal and survival analysis. JM 90-day mortality prediction performance was compared to MELD(-Na) in the validation cohorts. MELD(-Na) score and its rate of change over time significantly influenced patient survival. The JMs significantly outperformed the MELD(-Na) score at baseline and during follow-up. Baseline MELD-JM AUC was 0.94 (0.92-0.95) versus MELD AUC 0.87 (0.85-0.89). MELDNa-JM AUC was 0.91 (0.89-0.93) and MELD-Na AUC was 0.84 (0.81-0.87). The JMs were significantly (p<0.001) more accurate than MELD(-Na). After 90 days, we ranked patients for LT based on their MELD-Na and MELDNa-JM survival rates, showing that MELDNa-JM-prioritized patients had 3x higher waiting list mortality.