Chinese Journal of Pharmacovigilance ›› 2023, Vol. 20 ›› Issue (5): 568-573.
DOI: 10.19803/j.1672-8629.20220447

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Comparative study on data set of drug-induced liver injury

YAO Keyu1, ZHANG Shuqi1, JIN Rui2, LIU Lihong1#, ZHU Yan1,*   

  1. 1Institute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China;
    2Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091
  • Received:2022-07-28 Online:2023-05-15 Published:2023-05-16

Abstract: Objective To investigate and compare the data sources and methods for risk assessment and drug classification related to DILI so as to provide reference for the construction of DILI datasets and for clinical practice, research and regulation. Methods Five data sets (DILIrank, DICIst, Liver Tox, Suzuki, Greene) that involved more than 300 drugs and assessed the severity of human drug-induced liver injury were selected. The data sources, data volume, DILI risk assessment methods and drug classification were compared and analyzed. Results The data sources included drug labels, literature, network databases, clinical/registration center cases, regulators and other channels. LiverTox involved the largest number of drugs, DILIrank had the highest coincidence with other datasets, and the classification by DILIrank and LiverTox was more detailed. Risk assessment of DILI was classified according to the severity and odds of liver injury. DILI was determined by expert opinions or causal assessment. Conclusion A high-quality data set is related to the data source, data quantity, assessment methods and drug classification. Chinese drug-induced liver injury data sets, especially DILI data sets of Chinese medicines, need to be improved.

Key words: drug-induced liver injury, data set, risk assessment, DILI classification

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