Determining Which of Several Simultaneously Administered Vaccines Increase Risk of an Adverse Event.

INTRODUCTION

Childhood immunization schedules often involve multiple vaccinations per visit. When increased risk of an adverse event is observed after simultaneous (same-day) vaccinations, it can be difficult to ascertain which triggered the adverse event. This methods paper discusses a systematic process to determine which of the simultaneously administered vaccine(s) are most likely to have caused an observed increase in risk of an adverse event.

METHODS

We use an example from the literature where excess risk of seizure was observed 1 day after vaccination, but same-day vaccination patterns made it difficult to discern which vaccine(s) may trigger the adverse event. We illustrate the systematic identification process using a simulation that retained the observed pattern of simultaneous vaccination in an empirical cohort of vaccinated children. We simulated "true" effects for diphtheria-tetanus-acellular pertussis (DTaP) and pneumococcal conjugate (PCV) on risk of seizure the day after vaccination. We varied the independent and interactive effects of vaccines (on the multiplicative scale). After applying the process to simulated data, we evaluated risk of seizure 1 day after vaccination in the empirical cohort.

RESULTS

In all simulations, we were able to determine which vaccines contributed to excess risk. In the empirical data, we narrowed the association with seizure from all vaccines in the schedule to three likely candidates, DTaP, PCV, and/or Haemophilus influenzae type B (HiB) (p < 0.01, attributable risk when all three were administered together: five per 100,000). Disentangling their associations with seizure would require a larger sample or more variation in the combinations administered. When none of these three were administered, no excess risk was observed.

CONCLUSION

The process outlined could provide valuable information on the magnitude of potential risk from individual and simultaneousvaccinations. Associations should be further investigated with independent data as well as biologically based, statistically independent hypotheses.