Drugs Associated with Hepatotoxicity and their Reporting Frequency of Liver Adverse Events in VigiBase (TM) Unified List Based on International Collaborative Work

BACKGROUND Challenges exist in the clinical diagnosis of drug-induced liver injury (DILI) and in obtaining information on hepatotoxicity in humans. OBJECTIVE (i) To develop a unified list that combines drugs incriminated in well vetted or adjudicated DILI cases from many recognized sources and drugs that have been subjected to serious regulatory actions due to hepatotoxicity; and (ii) to supplement the drug list with data on reporting frequencies of liver events in the WHO individual case safety report database (VigiBase). DATA SOURCES AND EXTRACTION (i) Drugs identified as causes of DILI at three major DILI registries; (ii) drugs identified as causes of drug-induced acute liver failure (ALF) in six different data sources, including major ALF registries and previously published ALF studies; and (iii) drugs identified as being subjected to serious governmental regulatory actions due to their hepatotoxicity in Europe or the US were collected. The reporting frequency of adverse events was determined using VigiBase, computed as Empirical Bayes Geometric Mean (EBGM) with 90% confidence interval for two customized terms, 'overall liver injury' and 'ALF'. EBGM of >or=2 was considered a disproportional increase in reporting frequency. The identified drugs were then characterized in terms of regional divergence, published case reports, serious regulatory actions, and reporting frequency of 'overall liver injury' and 'ALF' calculated from VigiBase. DATA SYNTHESIS After excluding herbs, supplements and alternative medicines, a total of 385 individual drugs were identified; 319 drugs were identified in the three DILI registries, 107 from the six ALF registries (or studies) and 47 drugs that were subjected to suspension or withdrawal in the US or Europe due to their hepatotoxicity. The identified drugs varied significantly between Spain, the US and Sweden. Of the 319 drugs identified in the DILI registries of adjudicated cases, 93.4% were found in published case reports, 1.9% were suspended or withdrawn due to hepatotoxicity and 25.7% were also identified in the ALF registries/studies. In VigiBase, 30.4% of the 319 drugs were associated with disproportionally higher reporting frequency of 'overall liver injury' and 83.1% were associated with at least one reported case of ALF. CONCLUSIONS This newly developed list of drugs associated with hepatotoxicity and the multifaceted analysis on hepatotoxicity will aid in causality assessment and clinical diagnosis of DILI and will provide a basis for further characterization of hepatotoxicity.

Use of Hy's law and a new composite algorithm to predict acute liver failure in patients with drug-induced liver injury.

BACKGROUND & AIMS Hy's Law, which states that hepatocellular drug-induced liver injury (DILI) with jaundice indicates a serious reaction, is used widely to determine risk for acute liver failure (ALF). We aimed to optimize the definition of Hy's Law and to develop a model for predicting ALF in patients with DILI. METHODS We collected data from 771 patients with DILI (805 episodes) from the Spanish DILI registry, from April 1994 through August 2012. We analyzed data collected at DILI recognition and at the time of peak levels of alanine aminotransferase (ALT) and total bilirubin (TBL). RESULTS Of the 771 patients with DILI, 32 developed ALF. Hepatocellular injury, female sex, high levels of TBL, and a high ratio of aspartate aminotransferase (AST):ALT were independent risk factors for ALF. We compared 3 ways to use Hy's Law to predict which patients would develop ALF; all included TBL greater than 2-fold the upper limit of normal (×ULN) and either ALT level greater than 3 × ULN, a ratio (R) value (ALT × ULN/alkaline phosphatase × ULN) of 5 or greater, or a new ratio (nR) value (ALT or AST, whichever produced the highest ×ULN/ alkaline phosphatase × ULN value) of 5 or greater. At recognition of DILI, the R- and nR-based models identified patients who developed ALF with 67% and 63% specificity, respectively, whereas use of only ALT level identified them with 44% specificity. However, the level of ALT and the nR model each identified patients who developed ALF with 90% sensitivity, whereas the R criteria identified them with 83% sensitivity. An equal number of patients who did and did not develop ALF had alkaline phosphatase levels greater than 2 × ULN. An algorithm based on AST level greater than 17.3 × ULN, TBL greater than 6.6 × ULN, and AST:ALT greater than 1.5 identified patients who developed ALF with 82% specificity and 80% sensitivity. CONCLUSIONS When applied at DILI recognition, the nR criteria for Hy's Law provides the best balance of sensitivity and specificity whereas our new composite algorithm provides additional specificity in predicting the ultimate development of ALF.