Free Webinar
Sample Sizes for Vaccine Trials
Trial Designs for Assessing Vaccine Efficacy, Safety & Durability
In this webinar, Calvin O'Brien, Research Statistician at nQuery, has explored vaccine trial designs, specifically how to assess three key aspects of vaccine performance:
In this webinar we have covered the statistical foundation of vaccine development and rollout using real world examples.
Most vaccine studies focus primarily on efficacy (how well a vaccine protects against disease) and safety (whether the vaccine causes adverse events). However, the full picture requires looking at various aspects together in order to assess the suitability of rollout to a large population, along with monitoring post rollout.
Vaccine trials present unique statistical challenges because they typically require larger sample sizes than therapeutic trials, focus heavily on safety in healthy populations, and need to detect relatively rare events. The statistical methods must account for changing background disease rates, potential waning immunity, and the ethical considerations of placebo control groups when effective vaccines become available.
Vaccine trials require large sample sizes for several reasons:
Efficacy assessment typically uses comparative statistics between vaccine and control groups, measuring relative risk reduction through methods like Poisson regression or Cox proportional hazards models. Safety assessment often employs self-controlled case series methods that compare incidence rates of adverse events within individuals before and after vaccination, requiring different statistical approaches and sample size calculations.
Durability assessment relies on specialized statistical designs such as deferred vaccination models and crossover designs that allow ethical follow-up after initial efficacy is established. These approaches use time-to-event analyses, waning efficacy models, and methods to distinguish between true durability issues versus emerging variants that might evade immunity.
COVID-19 vaccine trials implemented several statistical innovations, including:
Traditional vaccine trials emphasize efficacy and safety, but to fully understand a vaccine's value, durability—the persistence of protection—must also be assessed. This webinar covers comprehensive approaches that combine short-term outcomes with long-term monitoring, offering a more complete picture of vaccine performance over time and across diverse populations.
Evaluating vaccine efficacy requires appropriate endpoints and statistical tests. Core techniques include proportion tests, risk ratio assessments, and case-control comparisons, all of which help determine how well the vaccine reduces disease incidence. The session explores how efficacy estimates are derived under varying assumptions and how to adjust for confounding variables.
Vaccine safety is not a static outcome—it evolves with widespread use. Methods such as the Self-Controlled Case Series (SCCS) and relative incidence modeling are vital for detecting rare or delayed adverse events. This session explains how to apply these methods during Phase IV and in observational post-licensure data.
Understanding durability requires longitudinal monitoring and trial designs tailored to detect waning efficacy. The webinar introduces deferred vaccination designs and breakthrough infection tracking as strategies to measure declining protection, along with subgroup analyses to identify populations at higher risk for waning protection.
With the rise of new technologies and variants, vaccine trial design must evolve. This webinar touches on adaptive frameworks, improved post-market surveillance methods, and advanced statistical modeling that are reshaping how vaccine performance is assessed.
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