title: Designing a cost-effective clinical trial.
abstract: Researchers and administrators must decide which clinical trials are worth doing and how many subjects are needed for a trial. We calculated sample size considering the costs of implementing the results of the trial and the trial costs using (1) Neyman-Pearson methods and (2) a Bayesian cost-benefit method. We illustrate these methods in a clinical trial sponsored by the National Institutes of Health that compares two levels of blood urea nitrogen clearance by haemodialysis for patients with end-stage renal disease. When applied to evaluations of research proposals, these methods may help researchers to decide whether to begin a study, and, if so, how many subjects to enrol in it. These methods should be especially useful for large studies intended to inform health policy.
authors.affiliation: Department of Health Research & Policy, Stanford University School of Medicine, CA, USA.
authors.forename: J C
authors.initials: JC
authors.lastname: Hornberger
authors.forename: B W
authors.initials: BW
authors.lastname: Brown
authors.forename: J
authors.initials: J
authors.lastname: Halpern
mesh_terms: D001499:Bayes Theorem; D003362:Cost-Benefit Analysis / Q000379:methods*; D003657:Decision Making; D017048:Health Care Costs; D006801:Humans; D007676:Kidney Failure, Chronic / Q000628:therapy; D016032:Randomized Controlled Trials as Topic / Q000191:economics*; D006435:Renal Dialysis / Q000191:economics; D012107:Research Design; D018401:Sample Size; D015996:Survival Rate; D014481:United States