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Designing a cost‐effective clinical trial
Author(s) -
Hornberger John C.,
Brown Byron Wm.,
Halpern Jerry
Publication year - 1995
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780142008
Subject(s) - clinical trial , sample size determination , blood urea nitrogen , medicine , bayesian probability , medical physics , computer science , actuarial science , statistics , renal function , business , mathematics , artificial intelligence
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.