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Predicting clinical outcomes using baseline and follow-up laboratory data from the hepatitis C long-term treatment against cirrhosis trial

Authors

  • Marc G. Ghany,

    Corresponding author
    1. Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Department of Health and Human Services, Bethesda, MD
    • Bldg. 10, Room 9B-16, 10 Center Drive, MSC 1800, Bethesda, MD 20892-1800
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    • fax: 301-496-0491

  • Hae-Young Kim,

    1. New England Research Institutes, Watertown, MA
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  • Anne Stoddard,

    1. New England Research Institutes, Watertown, MA
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  • Elizabeth C. Wright,

    1. Office of the Director, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Department of Health and Human Services, Bethesda, MD
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  • Leonard B. Seeff,

    1. Division of Digestive Diseases and Nutrition, and Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Department of Health and Human Services, Bethesda, MD
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  • Anna S.F. Lok,

    1. Division of Gastroenterology, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI
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  • the HALT-C Trial Group


  • Supported by the National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK contract numbers are listed below). Additional support was provided by the National Institute of Allergy and Infectious Diseases (NIAID); the National Cancer Institute; the National Center for Minority Health and Health Disparities; by General Clinical Research Center and Clinical and Translational Science Center grants from the National Center for Research Resources, National Institutes of Health (NIH grant numbers are listed below); and by the Intramural Research Program of the NIH, NIDDK (M. G. Ghany). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health. Additional funding to conduct this study was supplied by Hoffmann-La Roche, Inc. (now Genentech), through a Cooperative Research and Development Agreement (CRADA) with the National Institutes of Health. Publication #73 of the HALT-C Trial. The HALT-C Trial is registered with clinicaltrials.gov (#NCT00006164).

  • Potential conflict of interests: Dr. Lok is a consultant for, and received grants from, Bristol-Myers Squibb, Gilead, GlaxoSmithKline, Schering-Plough, Merck, and Roche. She also received grants from Eisai. Financial relationships of the authors with Hoffmann-La Roche, Inc. (now Genentech): A.S. Lok is a consultant and receives research support.

Abstract

Predicting clinical outcomes in patients with chronic hepatitis C is challenging. We used the hepatitis C long-term treatment against cirrhosis (HALT-C) trial database to develop two models, using baseline values of routinely available laboratory tests together with changes in these values during follow-up to predict clinical decompensation and liver-related death/liver transplant in patients with advanced hepatitis C. Patients randomized to no treatment and who had ≥2-year follow-up without a clinical outcome were included in the analysis. Four variables (platelet count, aspartate aminotransferase [AST]/alanine aminotransferase [ALT] ratio, total bilirubin, and albumin) with three categories of change (stable, mild, or severe) over 2 years were analyzed. Cumulative incidence of clinical outcome was determined by Kaplan-Meier analysis and Cox regression was used to evaluate predictors of clinical outcome. In all, 470 patients with 60 events were used to develop models to predict clinical decompensation. Baseline values of all four variables were predictive of decompensation. There was a general trend of increasing outcomes with more marked worsening of laboratory values over 2 years, particularly for patients with abnormal baseline values. A model that included baseline platelet count, AST/ALT ratio, bilirubin, and severe worsening of platelet count, bilirubin, and albumin was the best predictor of clinical decompensation. A total of 483 patients with 79 events were used to evaluate predictors of liver-related death or liver transplant. A model that included baseline platelet count and albumin as well as severe worsening of AST/ALT ratio and albumin was the best predictor of liver-related outcomes. Conclusion: Both the baseline value and the rapidity in change of the value of routine laboratory variables were shown to be important in predicting clinical outcomes in patients with advanced chronic hepatitis C. (HEPATOLOGY 2011;)

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