In HIV/HCV, Combined Metabolite Model Predicts Liver Disease Events

Novel set of metabolites can predict end-stage liver disease events up to 2 years in advance in patients with HIV and hepatitis C virus (HCV), according to a new study.

“Advanced liver disease due to HCV is a leading cause of HIV-related morbidity and mortality,” the researchers wrote. “There remains a need to develop noninvasive predictors of clinical outcomes in persons with HIV/HCV coinfection.”

The nested case-control study included 126 patients with HIV/HCV coinfection. The investigation used multiple quantitative metabolomic assays to discover a prognostic profile best able to predict ascites, hepatic encephalopathy, hepatocellular carcinoma, and other end-stage liver disease events in patients.

While the study’s baseline model, which included demographic and clinical data, had an area under the curve of 0.79, three models had areas under the curve between 0.84 and 0.89, the researchers reported. Those models—baseline plus amino acids, lipid metabolites, and all combined metabolites—had “very good accuracy” in signaling patients at risk of an end-stage liver disease events as far as 2 years ahead of the event.

In particular, the combined metabolites model demonstrated a sensitivity of 0.70, a specificity of 0.85, a positive likelihood ratio of 4.78, and a negative likelihood ratio 0.35, according to the study.

“We report that quantification of a novel set of metabolites may allow earlier identification of patients with HIV/HCV who have the greatest risk of developing end-stage liver disease clinical events,” the researchers concluded.

—Jolynn Tumolo

Reference:

Naggie S, Lusk S, Thompson JW, et al. Metabolomic signature as a predictor of liver disease events in patients with HIV/HCV coinfection. J Infect Dis. 2020;222(12):2012-2020. https://doi.org/10.1093/infdis/jiaa316