title: A detection algorithm for drug-induced liver injury in medical information databases using the Japanese diagnostic scale and its comparison with the Council for International Organizations of Medical Sciences/the Roussel Uclaf Causality Assessment Method scale.
abstract: OBJECTIVE
  Drug-induced liver injury (DILI) is one of the primary targets for pharmacovigilance using medical information databases (MIDs). Because of diagnostic complexity, a standardized method for identifying DILI using MIDs has not yet been established. We applied the Digestive Disease Week Japan 2004 (DDW-J) scale, a Japanese clinical diagnostic criteria for DILI, to a DILI detection algorithm, and compared it with the Council for International Organizations of Medical Sciences/the Roussel Uclaf Causality Assessment Method (CIOMS/RUCAM) scale to confirm its consistency. Characteristics of DILI cases identified by the DDW-J algorithm were examined in two Japanese MIDs.
  
  
  METHODS
  Using an MID from the Hamamatsu University Hospital, we constructed a DILI detection algorithm on the basis of the DDW-J scale. We then compared the findings between the DDW-J and CIOMS/RUCAM scales. We examined the characteristics of DILI after antibiotic treatment in the Hamamatsu population and a second population that included data from 124 hospitals, which was derived from an MID from the Medical Data Vision Co., Ltd. We performed a multivariate logistic regression analysis to assess the possible DILI risk factors.
  
  
  RESULTS
  The concordance rate was 79.4% between DILI patients identified by the DDW-J and CIOMS/RUCAM; the Spearman rank correlation coefficient was 0.952 (P < 0.0001). Men showed a significantly higher risk for DILI after antibiotic treatments in both MID populations.
  
  
  CONCLUSIONS
  The DDW-J and CIOMS/RUCAM algorithms were equivalent for identifying the DILI cases, confirming the utility of our DILI detection method using MIDs. This study provides evidence supporting the use of MID analyses to improve pharmacovigilance.
authors.affiliation: Division of Medicinal Safety Science, National Institute of Health Sciences, Tokyo, Japan; Department of Regulatory Science, Graduate School of Pharmaceutical Sciences, Nagoya City University, Aichi, Japan.
authors.forename: Tadaaki
authors.initials: T
authors.lastname: Hanatani
authors.forename: Kimie
authors.initials: K
authors.lastname: Sai
authors.forename: Masahiro
authors.initials: M
authors.lastname: Tohkin
authors.forename: Katsunori
authors.initials: K
authors.lastname: Segawa
authors.forename: Michio
authors.initials: M
authors.lastname: Kimura
authors.forename: Katsuhito
authors.initials: K
authors.lastname: Hori
authors.forename: Junichi
authors.initials: J
authors.lastname: Kawakami
authors.forename: Yoshiro
authors.initials: Y
authors.lastname: Saito
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data; D000465:Algorithms; D056486:Chemical and Drug Induced Liver Injury / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology; D016208:Databases, Factual / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007564:Japan; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D060735:Pharmacovigilance; D012307:Risk Factors; D018709:Statistics, Nonparametric
keywords: DDW-J; antibiotics; drug-induced liver injury; medical information database; pharmacoepidemiology; pharmacovigilance