Comparison of epidemiologic methods for active surveillance of vaccine safety

Abstract

Objective We performed a simulation study to compare four study designs [(matched-cohort, vaccinated-only (risk-interval) cohort, case–control, and self-controlled case-series (SCCS)] in the context of vaccine safety active surveillance. Methods For each combination of various incidence levels (3, 30, 300 per 10 5 person-years) and relative risks (RR 1.5–18), 100 case sets were infused into the cohort, matching 10 5 vaccinated to 10 5 unvaccinated on age and gender. The matched-cohort was converted into weekly accumulated data intervals with the other three study design samples drawn from each. Analyses were with appropriate regression models. The signal detection time was the first week where the log likelihood ratio (LLR) exceeded the upper boundary from the MaxSPRT sequential analysis method. Empirical type I (false positive) and type II (power) error rates and risk estimate bias were also calculated. Results The matched-cohort design exhibited the shortest detection time, lowest false positive rate and highest empirical power followed by the risk-interval cohort, SCCS, and case–control. In most monitoring weeks, the risk estimate bias was smallest for the cohort, followed by the risk-interval, SCCS and case–control designs. Conclusions The cohort study design performed the best in the sequential analysis of active surveillance for vaccine safety. The risk-interval cohort and SCCS designs offer reasonable and efficient alternatives, especially if selection bias is a concern. Future research should address seasonality or age effects.