Breaking free of sample size dogma to perform innovative translational research

Abstract

Innovative clinical and translational research is often delayed or prevented by reviewers' expectations that any study performed in humans must be shown in advance to have high statistical power. This supposed requirement is not justifiable and is contradicted by the reality that increasing sample size produces diminishing marginal returns. Studies of new ideas often must start small (sometimes even with an n of 1) because of cost and feasibility concerns, and recent statistical work shows that small sample sizes for such research can produce more projected scientific value per dollar spent than larger sample sizes. Renouncing false dogma about sample size would remove a serious barrier to innovation and translation.

Fig. 1

How sample size influences the scientific or practical value that a study can be expected to produce, under three different scenarios. Numeric labels on the axes are absent because specific values will differ for different studies, but the qualitative relationship illustrated applies to all studies of new ideas. When the idea is a fundamental breakthrough, this will usually be apparent from a relatively small study. A much larger sample size does not produce much additional value. Similarly, when the idea is completely off-target, this will usually be apparent from a relatively small study. In intermediate cases, larger sample sizes might add value. Note, however, that increasing sample size still produces diminishing marginal returns.