Development and Validation of a Model for Prediction of End-Stage Liver Disease in People With HIV. (1st April 2022) - Kim, H. Nina; Nance, Robin M.; Lo Re, Vincent; Silverberg, Michael J.; Franco, Ricardo; Sterling, Timothy R.; Cachay, Edward R.; Horberg, Michael A.; Althoff, Keri N.; Justice, Amy C.; Moore, Richard D.; Klein, Marina; et al.
Abstract : Supplemental Digital Content is Available in the Text. Abstract : Background: End-stage liver disease (ESLD) is a leading cause of non–AIDS-related death among people with HIV (PWH). Factors that increase the progression of liver disease include comorbidities and HIV-specific factors, but we currently lack a tool to apply this evidence into clinical practice. Methods: We developed and validated a risk prediction model for ESLD among PWH who received care in 12 cohorts of the North American AIDS Cohort Collaboration on Research and Design between 2000 and 2016 and had fibrosis-4 index > 1.45. The first occurrence of ascites, variceal bleed, spontaneous bacterial peritonitis, or hepatic encephalopathy was verified by standardized medical record review. The Bayesian model averaging was used to select predictors among biomarkers and diagnoses and the Harrell C statistic to assess model discrimination. Results: Among 13, 787 PWH in the training set, 82% were men and 54% were Black with a mean age of 48 years. Three hundred ninety ESLD events occurred over a mean 5.4 years. Among the ESLD cases, 52% had hepatitis C virus, 15% hepatitis B virus, and 31% alcohol use disorder. Twelve factors together predicted ESLD risk moderately well (C statistic 0.79, 95% confidence interval: 0.76 to 0.81): age, sex, race/ethnicity, chronic hepatitis B or C, and routinely collected laboratory values reflecting hepatic impairment (serum albumin, aspartate aminotransferase, total bilirubin, and platelets) and lipid metabolism (triglycerides, high-density lipoprotein, and total cholesterol). Our model performed well in the test set (C statistic 0.81, 95% confidence interval: 0.76 to 0.86). Conclusion: This model of readily accessible clinical parameters predicted ESLD in a large diverse population of PWH.