Sample sizes and negative studies in clinical vaccine research

Abstract

Negative studies of vaccine adverse events occur with some frequency in the published literature. They serve important roles in fending off claims posed by the anti-vaccine movement and in reinforcing public health efforts to prevent diseases. Still, negative studies frequently suffer from concerns of adequate sample size. The double-significance Neyman–Pearson formula for sample size calculation that is now in vogue results in immense sample sizes that can lead to illogical interpretations. The late Professor Alvan R. Feinstein, the father of quantitative clinical epidemiology, proposed a more logical approach that would reduce the confusion and call for more moderate sample sizes. Understanding the issues involved in sample size calculations is important to those who design clinical vaccine studies. The implications of the calculations have far-reaching effects upon elements of feasibility such as the expense of the study, the ability to recruit adequate numbers, and even whether the study will be done at all.