Susanna Naggie1,2, Sam Lusk1, J Will Thompson3,4, Meredith Mock2, Cynthia Moylan2, Joseph E Lucas5, Laura Dubois3, Lisa St John-Williams3, M Arthur Moseley3, Keyur Patel1,6. 1. Duke Clinical Research Institute, Duke University, Durham, North Carolina, USA. 2. Duke University School of Medicine, Durham, North Carolina, USA. 3. Duke Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, USA. 4. Department of Pharmacology and Cancer Biology, Duke University, Durham, North Carolina, USA. 5. Vital Statistics LLC, Durham, North Carolina, USA. 6. University of Toronto, Toronto, Ontario, Canada.
Abstract
BACKGROUND: Advanced liver disease due to hepatitis C virus (HCV) is a leading cause of human immunodeficiency virus (HIV)-related morbidity and mortality. There remains a need to develop noninvasive predictors of clinical outcomes in persons with HIV/HCV coinfection. METHODS: We conducted a nested case-control study in 126 patients with HIV/HCV and utilized multiple quantitative metabolomic assays to identify a prognostic profile that predicts end-stage liver disease (ESLD) events including ascites, hepatic encephalopathy, hepatocellular carcinoma, esophageal variceal bleed, and spontaneous bacterial peritonitis. Each analyte class was included in predictive modeling, and area under the receiver operator characteristic curves (AUC) and accuracy were determined. RESULTS: The baseline model including demographic and clinical data had an AUC of 0.79. Three models (baseline plus amino acids, lipid metabolites, or all combined metabolites) had very good accuracy (AUC, 0.84-0.89) in differentiating patients at risk of developing an ESLD complication up to 2 years in advance. The all combined metabolites model had sensitivity 0.70, specificity 0.85, positive likelihood ratio 4.78, and negative likelihood ratio 0.35. CONCLUSIONS: 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 ESLD clinical events.
BACKGROUND: Advanced liver disease due to hepatitis C virus (HCV) is a leading cause of human immunodeficiency virus (HIV)-related morbidity and mortality. There remains a need to develop noninvasive predictors of clinical outcomes in persons with HIV/HCV coinfection. METHODS: We conducted a nested case-control study in 126 patients with HIV/HCV and utilized multiple quantitative metabolomic assays to identify a prognostic profile that predicts end-stage liver disease (ESLD) events including ascites, hepatic encephalopathy, hepatocellular carcinoma, esophageal variceal bleed, and spontaneous bacterial peritonitis. Each analyte class was included in predictive modeling, and area under the receiver operator characteristic curves (AUC) and accuracy were determined. RESULTS: The baseline model including demographic and clinical data had an AUC of 0.79. Three models (baseline plus amino acids, lipid metabolites, or all combined metabolites) had very good accuracy (AUC, 0.84-0.89) in differentiating patients at risk of developing an ESLD complication up to 2 years in advance. The all combined metabolites model had sensitivity 0.70, specificity 0.85, positive likelihood ratio 4.78, and negative likelihood ratio 0.35. CONCLUSIONS: 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 ESLD clinical events.
Authors: Monica A Konerman; Shruti H Mehta; Catherine G Sutcliffe; Trang Vu; Yvonne Higgins; Michael S Torbenson; Richard D Moore; David L Thomas; Mark S Sulkowski Journal: Hepatology Date: 2014-01-16 Impact factor: 17.425
Authors: Marion G Peters; Peter Bacchetti; Ross Boylan; Audrey L French; Phyllis C Tien; Michael W Plankey; Marshall J Glesby; Michael Augenbraun; Elizabeth T Golub; Roksana Karim; Julie Parkes; William Rosenberg Journal: AIDS Date: 2016-03-13 Impact factor: 4.177
Authors: Vincent Lo Re; Michael J Kallan; Janet P Tate; A Russell Localio; Joseph K Lim; Matthew Bidwell Goetz; Marina B Klein; David Rimland; Maria C Rodriguez-Barradas; Adeel A Butt; Cynthia L Gibert; Sheldon T Brown; Lesley Park; Robert Dubrow; K Rajender Reddy; Jay R Kostman; Brian L Strom; Amy C Justice Journal: Ann Intern Med Date: 2014-03-18 Impact factor: 25.391
Authors: Vincent Lo Re; Michael J Kallan; Janet P Tate; Joseph K Lim; Matthew Bidwell Goetz; Marina B Klein; David Rimland; Maria C Rodriguez-Barradas; Adeel A Butt; Cynthia L Gibert; Sheldon T Brown; Lesley S Park; Robert Dubrow; K Rajender Reddy; Jay R Kostman; Amy C Justice; A Russell Localio Journal: Open Forum Infect Dis Date: 2015-07-09 Impact factor: 3.835