We propose a Bayesian formulation of the sample size problem for
planning clinical trials. The frequentist paradigm for calculating sample sizes
for clinical trials is to prespecify the type I and II error probabilities.
These error probabilities are conditional on the true hypotheses. Instead we
propose prespecifying posterior probabilities which are conditional on the
outcome of the trial. Our method is easy to implement and has intuitive
interpretations. We illustrate an application of our method to the planning of
cancer clinical trials for the Eastern Cooperative Oncology Group
(ECOG).