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Decision Theoretic Designs for Phase II Clinical Trials with Multiple Outcomes
Author(s) -
Stallard Nigel,
Thall Peter F.,
Whitehead John
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.00971.x
Subject(s) - frequentist inference , bayesian probability , phase (matter) , clinical trial , decision theory , clinical study design , computer science , function (biology) , medicine , intensive care medicine , bayesian inference , statistics , mathematics , artificial intelligence , chemistry , organic chemistry , evolutionary biology , biology
Summary. In many phase II clinical trials, it is essential to assess both efficacy and safety. Although several phase II designs that accommodate multiple outcomes have been proposed recently, none are derived using decision theory. This paper describes a Bayesian decision theoretic strategy for constructing phase II designs based on both efficacy and adverse events. The gain function includes utilities assigned to patient outcomes, a reward for declaring the new treatment promising, and costs associated with the conduct of the phase II trial and future phase III testing. A method for eliciting gain function parameters from medical collaborators and for evaluating the design's frequentist operating characteristics is described. The strategy is illustrated by application to a clinical trial of peripheral blood stem cell transplantation for multiple myeloma.