An updated method improved the assessment of adverse drug reaction in routine pharmacovigilance.
OBJECTIVE
Updating a logistic causality assessment method to improve its agreement with consensual expert judgment (CEJ).


METHODS
A random sample of 53 drug-event pairs from a pharmacovigilance database were evaluated independently by CEJ and by a group of experts in pharmacovigilance using the logistic method. Causes of disagreement between both approaches were analyzed, and changes in the assessment of some criteria of the logistic method were proposed and tested in models. The model giving results closest to the CEJ was retained and compared with the initial version on another set of drug-event pairs.


RESULTS
Finally, only the criterion "Search for nondrug cause" was changed into "Search for other causes." The assessment not investigated, possible other cause decreased the probability of drug causation instead of being neutral, whereas the assessment not applicable, not required remained neutral. This new version presents much improved specificity (0.56 vs. 0.33), relatively good sensitivity (0.96), and positive and negative predictive values (0.92 and 0.71).


CONCLUSIONS
The updated logistic method presented here improves the initial version that had poor specificity and tended to overestimate drug causation. This new version presents satisfactory characteristics to be used in routine pharmacovigilance.
Université de Bordeaux, U657, 146 rue Léo Saignat, F-33076 Bordeaux cedex, France. helene.theophile@pharmaco.u-bordeaux2.fr
Hélène
H
Théophile
Manon
M
André
Yannick
Y
Arimone
Françoise
F
Haramburu
Ghada
G
Miremont-Salamé
Bernard
B
Bégaud
D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D015984:Causality; D064420:Drug-Related Side Effects and Adverse Reactions; D005602:France; D006801:Humans; D016015:Logistic Models; D017891:Pharmacoepidemiology / Q000379:methods / Q000706:statistics & numerical data*; D060735:Pharmacovigilance; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity