Sequential Data-Mining for Adverse Events After Recombinant Herpes Zoster Vaccination Using the Tree-Based Scan...

Area of Science:

• Vaccine safety surveillance
• Biostatistics
• Pharmacovigilance

Background:

• Tree-based scan statistics offer a flexible approach for vaccine safety monitoring without pre-specifying adverse events.
• Previous applications have demonstrated the utility of this method in identifying potential safety signals.

Purpose of the Study:

• To apply a binomial tree-based scan statistic to detect adverse events following recombinant herpes zoster (RZV) vaccination.
• To assess vaccine safety using a large, real-world claims database.

Main Methods:

• A sequential binomial tree-based scan statistic was employed to analyze adverse events within 28 days post-RZV vaccination compared to a subsequent period.
• Data from 999,876 RZV doses administered to individuals aged ≥50 years were analyzed from IBM MarketScan.
• Formal adjustments were made for repeated statistical analyses over time.

Main Results:

• Statistically significant signals were detected solely for unspecified adverse effects/complications following immunization.
• The attributable risk was low, estimated at 2 excess cases per 100,000 vaccinations.
• Ninety percent of identified cases occurred within one week of vaccination, consistent with non-serious events like fever, fatigue, and headache.

Conclusions:

• The tree-based scan statistic method successfully identified potential safety signals for RZV vaccination in an untargeted manner.
• The detected signals likely represent common, non-serious adverse events, indicating a favorable safety profile.
• This methodology enables early detection of potential safety issues, facilitating ongoing vaccine safety monitoring.