The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A new method for assessing drug causation provided agreement with experts' judgment
Abstract
Background and objective The many methods proposed for causality assessment of adverse drug reaction (ADR) generally rely on algorithms. They have no clear relationship to probabilities, however, a situation we attempted to improve. Study design and setting Thirty ADR cases corresponding to 32 suspect drugs were randomly selected from the French pharmacovigilance database. The statistical weighting was performed by using a multilinear regression with logit(p) as the dependent variable and seven judgment criteria as independent variables. The best model (i.e., giving the best correlation with the gold standard) was retained for the new causality assessment method. Results The weights [logit(p)] for the 21 choices, on average three for each of the seven criteria, ranged from -3.95 to 0.86, secondarily rounded to multiples of 0.5. The correlation between the probability obtained from the final method and the gold standard was quite good (R(2) = .92). Conclusion This method based on the rational weighting of seven causality criteria is straightforward to use and provides very good agreement with experts' judgment. Moreover, unlike most classical algorithms, it respects one basic rule of probabilities-namely, a symmetrical probability distribution for drug causation around the .5 neutral position (maximum uncertainty).
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The reliability of expert judgement is traditionally compromised by inherent subjectivity and lack of uniformity, leading to suboptimal reproducibility between experts.
“Traditionally, the reliability of expert judgement is compromised by its inherent subjectivity and lack of uniformity, culminating in suboptimal reproducibility between experts.”
From Methods for causality assessment of idiosyncratic drug‐induced liver injury (2025) · cites this paper as [21]
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Cites
A method for estimating the probability of adverse drug reactions
Naranjo, C. A., Busto, U., Sellers, E. M., Sandor, P., Ruiz, I., Roberts, E. A., Janecek, E., Domecq, C., & Greenblatt, D. J. (1981) · Clinical Pharmacology and Therapeutics · doi:10.1038/clpt.1981.154 · Cited by 11,914 · cited 1×
“For these reasons, we used expert consensus, as in the design of some existing causality assessment methods [14–16].”
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Research works printed but not linked: 18
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Methods for Causality Assessment of Adverse Drug Reactions: A Systematic Review
Agbabiaka, T. B., Savović, J., & Ernst, E. (2008) · Drug Safety · doi:10.2165/00002018-200831010-00003 · Cited by 366
Methods for causality assessment of idiosyncratic drug‐induced liver injury
García‐Cortés, M., Matilla‐Cabello, G., & Lucena, M. I. (2025) · Liver International · doi:10.1111/liv.16083 · Cited by 15
Metadata
- Authors
- Arimone, Y., Bégaud, B., Miremont-Salamé, G., Fourrier-Réglat, A., Molimard, M., Moore, N., & Haramburu, F.
- Venue
- Journal of Clinical Epidemiology
- Publisher
- Elsevier BV
- Published
- 2006-03
- Volume
- 59
- Issue
- 3
- Pages
- 308-314
- ISSN
- 0895-4356
- Cited by
- 54
- References
- 1
- Language
- en
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