title: Bayesian sample size calculations in phase II clinical trials using informative conjugate priors.
abstract: A number of researchers have discussed phase II clinical trials from a Bayesian perspective. A recent article by Tan and Machin focuses on sample size calculations, which they determine by specifying a diffuse prior distribution and then calculating a posterior probability that the true response will exceed a prespecified target. In this article, we extend these sample size calculations to include informative prior distributions using various strategies that allow researchers with both optimistic and pessimistic priors direct involvement in the sample size decision making. We select the informative priors via multiple methods determined by the mean, median or mode of the conjugate prior. These cases can result in varying sample sizes.
authors.affiliation: Department of Preventive Medicine and Public Health, Medical Statistics and Research Design Unit, Kansas Cancer Institute, University of Kansas Medical Center, Kansas City, KS, USA.
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Mayo
authors.forename: Byron J
authors.initials: BJ
authors.lastname: Gajewski
mesh_terms: D001499:Bayes Theorem; D017322:Clinical Trials, Phase II as Topic / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D015233:Models, Statistical; D011336:Probability; D018401:Sample Size; D035501:Uncertainty