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Metabolomic Signature as a Predictor of Liver Disease Events in Patients With HIV/HCV Coinfection.

Publication ,  Journal Article
Naggie, S; Lusk, S; Thompson, JW; Mock, M; Moylan, C; Lucas, JE; Dubois, L; St John-Williams, L; Moseley, MA; Patel, K
Published in: J Infect Dis
November 13, 2020

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.

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Published In

J Infect Dis

DOI

EISSN

1537-6613

Publication Date

November 13, 2020

Volume

222

Issue

12

Start / End Page

2012 / 2020

Location

United States

Related Subject Headings

  • Prognosis
  • Predictive Value of Tests
  • Models, Biological
  • Middle Aged
  • Microbiology
  • Metabolome
  • Male
  • Humans
  • Hepatitis C
  • HIV Infections
 

Citation

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Naggie, S., Lusk, S., Thompson, J. W., Mock, M., Moylan, C., Lucas, J. E., … Patel, K. (2020). Metabolomic Signature as a Predictor of Liver Disease Events in Patients With HIV/HCV Coinfection. J Infect Dis, 222(12), 2012–2020. https://doi.org/10.1093/infdis/jiaa316
Naggie, Susanna, Sam Lusk, J Will Thompson, Meredith Mock, Cynthia Moylan, Joseph E. Lucas, Laura Dubois, Lisa St John-Williams, M Arthur Moseley, and Keyur Patel. “Metabolomic Signature as a Predictor of Liver Disease Events in Patients With HIV/HCV Coinfection.J Infect Dis 222, no. 12 (November 13, 2020): 2012–20. https://doi.org/10.1093/infdis/jiaa316.
Naggie S, Lusk S, Thompson JW, Mock M, Moylan C, Lucas JE, et al. Metabolomic Signature as a Predictor of Liver Disease Events in Patients With HIV/HCV Coinfection. J Infect Dis. 2020 Nov 13;222(12):2012–20.
Naggie, Susanna, et al. “Metabolomic Signature as a Predictor of Liver Disease Events in Patients With HIV/HCV Coinfection.J Infect Dis, vol. 222, no. 12, Nov. 2020, pp. 2012–20. Pubmed, doi:10.1093/infdis/jiaa316.
Naggie S, Lusk S, Thompson JW, Mock M, Moylan C, Lucas JE, Dubois L, St John-Williams L, Moseley MA, Patel K. Metabolomic Signature as a Predictor of Liver Disease Events in Patients With HIV/HCV Coinfection. J Infect Dis. 2020 Nov 13;222(12):2012–2020.
Journal cover image

Published In

J Infect Dis

DOI

EISSN

1537-6613

Publication Date

November 13, 2020

Volume

222

Issue

12

Start / End Page

2012 / 2020

Location

United States

Related Subject Headings

  • Prognosis
  • Predictive Value of Tests
  • Models, Biological
  • Middle Aged
  • Microbiology
  • Metabolome
  • Male
  • Humans
  • Hepatitis C
  • HIV Infections