## Michael A. Proschan, National Institutes of Health

### Two-Stage Designs to Adaptively Modify Sample Size in Clinical
Trials

Sample size calculations are essential to ensure a
well-designed clinical trial. Unfortunately, they depend on unknown
nuisance parameters and the treatment effect. The nuisance parameter
for the comparison of means with a continuous outcome is the variance,
while for the comparison of proportions with a dichotomous outcome it
is the overall event probability. Ideally, the treatment effect
parameter is chosen as the minimum clinically relevant treatment
difference, but this may also not be known, and in practice one often
chooses a treatment effect that was similar to those seen in other
trials. But those other trials may not be sufficiently similar, so
why not use data from the current trial to estimate these parameters?
This talk discusses two-stage clinical trials in which the first stage
is used to estimate parameters upon which the ultimate sample size is
based. The first part of the talk focuses on trials in which only the
nuisance parameter must be estimated, and the second part considers
trials in which the treatment effect is estimated.