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Causality assessment methods in drug induced liver injury: Strengths and weaknesses

期刊

JOURNAL OF HEPATOLOGY
卷 55, 期 3, 页码 683-691

出版社

ELSEVIER
DOI: 10.1016/j.jhep.2011.02.007

关键词

Drug induced liver injury; Hepatotoxicity; CIOMS/RUCAM scale; Causality assessment methods; Diagnosis; Risk factors; Limitations

资金

  1. Agenda Espanola del Medicamento
  2. Fondo de Investigacion Sanitaria [FIS 07-0980]
  3. Instituto de Salud Carlos III

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Diagnosis of drug-induced liver injury (DILI) remains a challenge and eagerly awaits the development of reliable hepatotoxicity biomarkers. Several methods have been developed in order to facilitate hepatotoxicity causality assessments. These methods can be divided into three categories: (1) expert judgement, (2) probabilistic approaches, and (3) algorithms or scales. The last category is further divided into general and liver-specific scales. The Council for International Organizations of Medical Sciences (CIOMS) scale, also referred to as the Roussel Uclaf Causality Assessment Method (RUCAM), although cumbersome and difficult to apply by physicians not acquainted with DILI, is used by many expert hepatologists, researchers, and regulatory authorities to assess the probability of suspected causal agents. However, several limitations of this scale have been brought to light, indicating that a number of adjustments are needed. This review is a detailed timely criticism to alert the readers of the limitations and give insight into what would be needed to improve the scale. Instructions on how to approach DILI diagnosis in practice are provided, using CIOMS as an aid to emphasize the topics to be addressed when assessing DILI cases. Amendments of the CIOMS scale in the form of applying authoritative evidence-based criteria, a simplified scoring system and appropriate weighting given to individual parameters based on statistical evaluations with large databases will provide wider applicability in the clinical setting. (C) 2011 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

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