Post-Authorization Active Surveillance Safety Study Using Secondary Data to Monitor Real-World Safety of Spikevax in Europe (COVID-19)

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Assessment of risk minimisation measure implementation or effectiveness

Non-interventional study

• Non-interventional study design:
  Cohort

  Other
• Non-interventional study design, other:
  Self-controlled case series

Study drug and medical condition

• Medicinal product name:
  SPIKEVAX
• Study drug International non-proprietary name (INN) or common name:
  COVID-19 MRNA VACCINE (NUCLEOSIDE-MODIFIED)
• Anatomical Therapeutic Chemical (ATC) code:
  (J07BN01) covid-19, RNA-based vaccine

  covid-19, RNA-based vaccine

Population studied

• Age groups:
  • Children (2 to < 12 years)
  • Adolescents (12 to < 18 years)
  • Adults (18 to < 46 years)
  • Adults (46 to < 65 years)
  • Adults (65 to < 75 years)
  • Adults (75 to < 85 years)
  • Adults (85 years and over)
• Special population of interest:
  Immunocompromised

  Pregnant women
• Estimated number of subjects:
  500000

Study design details

• Main study objective:
  Primary objective: ; - To assess whether vaccination with Spikevax (by dose number where feasible and for any dose) Secondary objective:; - To assess whether vaccination with Spikevax is associated with increased rates of the AESI compared with the expected rates in subpopulations of interest
• Data analysis plan:
  Signal detection will be conducted first. For identified signals, signal evaluation will follow. ; For signal detection, the underlying analytic principle is the observed - expected (O-E) analysis, which aims to compare AESI rates in vaccinees, with the rates expected for a non-vaccinated population as similar as possible in its demographic and other relevant characteristics to the vaccinated population. ; For signal evaluation using self-controlled designs, the ratio between the incidence rate estimate in the risk period and the incidence rate estimate in the control period (incidence rate ratio) will be computed using conditional Poisson regression. ; For parallel cohort designs, appropriate contrasts will be estimated in exposed vs. unexposed cohorts, while controlling for measured confounding.