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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.
Pharmacoepidemiol Drug Saf 2014; 23(9):984-8PD

Abstract

PURPOSE

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+Show Affiliations

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.

Pub Type(s)

Comparative Study
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

24596340

Citation

Hanatani, Tadaaki, et al. "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." Pharmacoepidemiology and Drug Safety, vol. 23, no. 9, 2014, pp. 984-8.
Hanatani T, Sai K, Tohkin M, et al. 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. Pharmacoepidemiol Drug Saf. 2014;23(9):984-8.
Hanatani, T., Sai, K., Tohkin, M., Segawa, K., Kimura, M., Hori, K., ... Saito, Y. (2014). 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. Pharmacoepidemiology and Drug Safety, 23(9), pp. 984-8. doi:10.1002/pds.3603.
Hanatani T, et al. 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. Pharmacoepidemiol Drug Saf. 2014;23(9):984-8. PubMed PMID: 24596340.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - 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. AU - Hanatani,Tadaaki, AU - Sai,Kimie, AU - Tohkin,Masahiro, AU - Segawa,Katsunori, AU - Kimura,Michio, AU - Hori,Katsuhito, AU - Kawakami,Junichi, AU - Saito,Yoshiro, Y1 - 2014/03/05/ PY - 2013/07/31/received PY - 2014/01/20/revised PY - 2014/01/29/accepted PY - 2014/3/6/entrez PY - 2014/3/7/pubmed PY - 2015/5/12/medline KW - DDW-J KW - antibiotics KW - drug-induced liver injury KW - medical information database KW - pharmacoepidemiology KW - pharmacovigilance SP - 984 EP - 8 JF - Pharmacoepidemiology and drug safety JO - Pharmacoepidemiol Drug Saf VL - 23 IS - 9 N2 - PURPOSE: 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. SN - 1099-1557 UR - https://www.unboundmedicine.com/medline/citation/24596340/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_ L2 - https://doi.org/10.1002/pds.3603 DB - PRIME DP - Unbound Medicine ER -