A concept for causality assessment and causal inference of adverse events cases


Submitted: August 3, 2022
Accepted: October 19, 2022
Published: November 2, 2022
Abstract Views: 712
PDF: 253
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Authors

  • Ahmed Al-Imam Department of Anatomy and Cellular Biology, College of Medicine, University of Baghdad, Baghdad, Iraq; Department of Computer Science and Statistics, Doctoral School, Poznan University of Medical Sciences, Poznan, Poland; Alumni Ambassador, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom. https://orcid.org/0000-0003-1846-9424
  • Ahmed Sami College of Pharmacy, Al-Mustansiriya University, Baghdad, Iraq; Baghdad Teaching Hospital, Baghdad Medical City Teaching Complex, Baghdad, Iraq.
  • Samantha Lane Drug Safety Research Unit, Southampton, United Kingdom.
  • Manal Younus Iraqi Pharmacovigilance Centre, Ministry of Health, Baghdad, Iraq; International Society of Pharmacovigilance, Middle East Chapter, London, United Kingdom.

Dear Editor,

 

Causality assessment of adverse drug events is essential in pharmacovigilance to assess the relationship between the medicine and the event.1,2 Regulatory authorities recommend using standardized methods for causality assessment.3,4 The World Health Organization-Uppsala Monitoring Center (WHO-UMC) system offers generalized criteria for establishing causal relationships.3 In contrast, the Roussel Uclaf Causality Assessment Method (RUCAM) provides a specialized system to assess Drug-Induced Liver Injury (DILI) cases. We systematically reviewed the literature and verified that these systems are among the best tools currently available for signal detection and causality assessment. [...]


Edwards IR, Aronson JK. Adverse drug reactions: definitions, diagnosis, and management. Lancet 2000;356:1255-9.

Al-Imam A, Motyka MA, Witulska Z, et al. Spatiotemporal mapping of online interest in cannabis and popular psychedelics before and during the COVID-19 pandemic in Poland. Int J Environ Res Public Health 2022;19:6619.

The World Health Organization. The use of the WHO-UMC system for standardised case causality assessment [Internet]. Who.int. 2013.Accessed 1 July 2022. Available from: https://www.who.int/publications/m/item/WHO-causality-assessment

LiverTox: Clinical and research information on drug-induced liver injury [Internet]. Bethesda (MD): National Institute of Diabetes and Digestive and Kidney Diseases; 2012. Roussel Uclaf Causality Assessment Method (RUCAM) in Drug Induced Liver Injury. Updated 2019 May 4. Available from: https://www.ncbi.nlm.nih.gov/books/NBK548272/

Drug-induced liver injury (DILI): Current status and future directions for drug development and the post-market setting. A consensus by a CIOMS Working Group. Geneva, Switzerland: Council for International Organizations of Medical Sciences (CIOMS), 2020.

Kassid OM, Odhaib SA, Altemimi MT. Flutamide-induced hepatotoxicity: A case report. J Biol Res 2022; ahead of print. doi: 10.4081/jbr.2022.10371

U.S. Food and Drug Administration. DILIrank [Internet]. Liver Toxicity Knowledge Base (LTKB). 2022. Accessed 1 July 2022. Available from: https://www.fda.gov/science-research/bioinformatics-tools/liver-toxicity-knowledge-base-ltkb

LiverTox: Clinical and research information on drug-induced liver injury [Internet]. Bethesda (MD): National Institute of Diabetes and Digestive and Kidney Diseases; 2012. PMID: 31643176.

Larasati A, DeYong C, Slevitch L. Comparing neural network and ordinal logistic regression to analyze attitude responses. Serv Sci 2011;3:304-12.

Uppsala Monitoring Centre. VigiFlow [Internet]. Vigiflow.who-umc.org. 2022. Accessed 29 September 2022. Available from: https://vigiflow.who-umc.org/

Uppsala Monitoring Centre. VigiLyze [Internet]. Vigiflow.who-umc.org. 2022. Accessed 29 September 2022. Available from: https://vigilyze.who-umc.org/

Abd AK, Kadhim DJ, Younus MM. Assessment of causality, severity and seriousness of adverse event following immunization in Iraq: A retrospective study based on Iraqi Pharmacovigilance Database. Iraqi J Pharm Sci 2019;28:142-50.

Al-Imam A. Optimizing Linear Models via Sinusoidal Transformation for Boosted Machine Learning in Medicine. J Fac Med Baghdad 2019;61:128-36.

Al-Imam, A., Sami, A., Lane, S., & Younus, M. (2022). A concept for causality assessment and causal inference of adverse events cases. Journal of Biological Research - Bollettino Della Società Italiana Di Biologia Sperimentale, 95(2). https://doi.org/10.4081/jbr.2022.10772

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