Development of a Model to Predict Transplant-free Survival of Patients With Acute Liver Failure

Abstract

Background & aims: Patients with acute liver failure (ALF) have a high risk of death that can be substantially reduced with liver transplantation. It is a challenge to predict which patients with ALF will survive without liver transplant because available prognostic scoring systems are inadequate. We devised a mathematical model, using a large dataset collected by the Acute Liver Failure Study Group, which can predict transplant-free survival in patients with ALF.

Methods: We performed a retrospective analysis of data from 1974 subjects who met criteria for ALF (coagulopathy and hepatic encephalopathy within 26 weeks of the first symptoms, without pre-existing liver disease) enrolled in the Acute Liver Failure Study Group database from January 1, 1998 through June 11, 2013. We randomly assigned the subjects to development and validation cohorts. Data from the development cohort were analyzed to identify factors associated with transplant-free survival (alive without transplantation by 21 days after admission to the study). Statistically significant variables were used to create a multivariable logistic regression model.

Results: Most subjects were women (70%) and white (78%); acetaminophen overdose was the most common cause (48% of subjects). The rate of transplant-free survival was 50%. Admission values of hepatic encephalopathy grade, ALF etiology, vasopressor use, and log transformations of bilirubin and international normalized ratio were significantly associated with transplant-free survival, based on logistic regression analysis. In the validation cohort, the resulting model predicted transplant-free survival with a C statistic value of 0.84, 66.3% accuracy (95% confidence interval, 63.1%-69.4%), 37.1% sensitivity (95% confidence interval, 32.5%-41.8%), and 95.3% specificity (95% confidence interval, 92.9%-97.1%).

Conclusions: Using data from the Acute Liver Failure Study Group, we developed a model that predicts transplant-free survival of patients with ALF based on easily identifiable hospital admission data. External validation studies are required.

Keywords: Acute Liver Failure; Mortality; Predictive Model; Prognosis.

Figure 1.. ROC Curves for Development and Validation Cohorts

*Depicts the threshold for 80% SS in each cohort

Figure 2.. Comparison of the ALFSG Model to the King’s College Criteria and MELD Score, in Predicting 80% survival

Model c-statistics: ALFSG Model = 0.843; MELD = 0.717; King’s College Criteria APAP (0.560), King’s College Criteria Non-APAP (0.655)