title: Risk of Acute Liver Failure in Patients With Drug-Induced Liver Injury: Evaluation of Hy's Law and a New Prognostic Model.
abstract: Few studies have evaluated the ability of laboratory tests to predict risk of acute liver failure (ALF) among patients with drug-induced liver injury (DILI). We aimed to develop a highly sensitive model to identify DILI patients at increased risk of ALF. We compared its performance with that of Hy's Law, which predicts severity of DILI based on levels of alanine aminotransferase or aspartate aminotransferase and total bilirubin, and validated the model in a separate sample.
  
  
  
  We conducted a retrospective cohort study of 15,353 Kaiser Permanente Northern California members diagnosed with DILI from 2004 through 2010, liver aminotransferase levels above the upper limit of normal, and no pre-existing liver disease. Thirty ALF events were confirmed by medical record review. Logistic regression was used to develop prognostic models for ALF based on laboratory results measured at DILI diagnosis. External validation was performed in a sample of 76 patients with DILI at the University of Pennsylvania.
  
  
  
  Hy's Law identified patients that developed ALF with a high level of specificity (0.92) and negative predictive value (0.99), but low level of sensitivity (0.68) and positive predictive value (0.02). The model we developed, comprising data on platelet count and total bilirubin level, identified patients with ALF with a C statistic of 0.87 (95% confidence interval [CI], 0.76-0.96) and enabled calculation of a risk score (Drug-Induced Liver Toxicity ALF Score). We found a cut-off score that identified patients at high risk patients for ALF with a sensitivity value of 0.91 (95% CI, 0.71-0.99) and a specificity value of 0.76 (95% CI, 0.75-0.77). This cut-off score identified patients at high risk for ALF with a high level of sensitivity (0.89; 95% CI, 0.52-1.00) in the validation analysis.
  
  
  
  Hy's Law identifies patients with DILI at high risk for ALF with low sensitivity but high specificity. We developed a model (the Drug-Induced Liver Toxicity ALF Score) based on platelet count and total bilirubin level that identifies patients at increased risk for ALF with high sensitivity.
authors.affiliation: Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: vincentl@mail.med.upenn.edu.
authors.forename: Vincent
authors.initials: V
authors.lastname: Lo Re
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: Kevin
authors.initials: K
authors.lastname: Haynes
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: Kimberly A
authors.initials: KA
authors.lastname: Forde
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: David S
authors.initials: DS
authors.lastname: Goldberg
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: James D
authors.initials: JD
authors.lastname: Lewis
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: Dean M
authors.initials: DM
authors.lastname: Carbonari
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: Kimberly B F
authors.initials: KB
authors.lastname: Leidl
authors.affiliation: Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: K Rajender
authors.initials: KR
authors.lastname: Reddy
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: Melissa S
authors.initials: MS
authors.lastname: Nezamzadeh
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: Jason
authors.initials: J
authors.lastname: Roy
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: Daohang
authors.initials: D
authors.lastname: Sha
authors.affiliation: Division of Research, Kaiser Permanente Northern California, Oakland, California.
authors.forename: Amy R
authors.initials: AR
authors.lastname: Marks
authors.affiliation: Division of Research, Kaiser Permanente Northern California, Oakland, California.
authors.forename: Jolanda
authors.initials: J
authors.lastname: De Boer
authors.affiliation: Division of Research, Kaiser Permanente Northern California, Oakland, California.
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Schneider
authors.affiliation: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Rutgers Biomedical & Health Sciences, Rutgers, the State University of New Jersey, Newark, New Jersey.
authors.forename: Brian L
authors.initials: BL
authors.lastname: Strom
authors.affiliation: Division of Research, Kaiser Permanente Northern California, Oakland, California.
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Corley
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001663:Bilirubin / Q000097:blood; D002140:California; D056486:Chemical and Drug Induced Liver Injury / Q000150:complications*; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D017114:Liver Failure, Acute / Q000139:chemically induced* / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D010976:Platelet Count; D011379:Prognosis; D012189:Retrospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D000637:Transaminases / Q000097:blood; D055815:Young Adult
chemical_list: D000637:Transaminases; D001663:Bilirubin
keywords: Acute liver failure; DILI; Drug-induced liver injury; Hepatotoxicity; Hy’s law