Causality assessment of adverse drug reactions: comparison of the results obtained from published decisional algorithms and from the evaluations of an expert panel, according to different levels of imputability
Article first published online: 23 APR 2003
Journal of Clinical Pharmacy and Therapeutics
Volume 28, Issue 2, pages 137–143, April 2003
How to Cite
Macedo, A. F., Marques, F. B., Ribeiro, C. F. and Teixeira, F. (2003), Causality assessment of adverse drug reactions: comparison of the results obtained from published decisional algorithms and from the evaluations of an expert panel, according to different levels of imputability. Journal of Clinical Pharmacy and Therapeutics, 28: 137–143. doi: 10.1046/j.1365-2710.2003.00475.x
- Issue published online: 23 APR 2003
- Article first published online: 23 APR 2003
- Received 13 November 2002, Accepted 7 March 2003
- adverse drug reaction;
- causality assessment;
- global introspection;
Objectives: To evaluate agreement between causality assessments of reported adverse drug reactions (ADRs) obtained from decisional algorithms, with those obtained from an expert panel using the WHO global introspection method (GI), according to different levels of imputability and to evaluate the influence of confounding variables.
Method: Two hundred reports were included in this study. An independent researcher used decisional algorithms, while an expert panel assessed the same ADR reports using the GI, both aimed at evaluating causality. Reports were divided according to the presence, absence or lack of information on confounding variables.
Results: The rates of concordance between assessments made using the algorithms and GI according to levels of imputability were: 45% for ‘certain’, 61% for ‘probable’, 46% for ‘possible’ and 17% for drug unrelated terms. When confounding variables were taken into account, the rates of concordance for the ‘absence of information’, ‘lack of information’ and ‘presence of confounding variables’ in the ‘certain’ group were 49, 69 and 7%, respectively. The corresponding values for the ‘probable’ group were 80, 68 and 24% and 30, 51 and 51%, respectively for the ‘possible’ group.
Conclusion: Full agreement with global introspection was not found for any level of causality assessment. Confounding variables were found to be associated with low levels of agreement between decision algorithms and the GI method compromising the algorithms' sensitivity and specificity.