The performance of three logistic regression models, incorporating different combinations of quantified causality criteria, was evaluated for the detection of safety signals from vaccine spontaneous report data
The logistic regression model integrating only the measure of the strength of association appeared to have the lowest performance for predicting known safety issues
The unexpectedness of the time-to-onset distribution for a given vaccine–event pair (when compared with the time-to-onset distribution of the same event reported following exposure to other vaccines) appeared to be best predictor of the reported event being a known safety issue
Logistic regression offers a framework in which quantified causality criteria can be combined to evaluate the probability of a vaccine–event pair being an adverse reaction following immunization based on our existing knowledge of vaccine safety profiles