Abstract
A Phase IIB clinical trial typically is a single-arm study aimed at deciding whether a new treatment E is sufficiently promising, relative to a standard therapy, S, to include in a large-scale randomized trial. Thus, Phase IIB trials are inherently comparative even though a standard therapy arm usually is not included. Uncertainty regarding the response rate Θ(S) of S is rarely made explicit, either in planning the trial or interpreting its results. We propose practical Bayesian guidelines for deciding whether E is promising relative to S in settings where patient response is binary and the data are monitored continuously. The design requires specification of an informative prior for Θ(S), a targeted improvement for E, and bounds on the allowed sample size. No explicit specification of a loss function is required. Sampling continues until E is shown to be either promising or not promising relative to S with high posterior probability, or the maximum sample size is reached. The design provides decision boundaries, a probability distribution for the sample size at termination, and operating characteristics under fixed response probabilities with E.
Original language | English (US) |
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Pages (from-to) | 337-349 |
Number of pages | 13 |
Journal | Biometrics |
Volume | 50 |
Issue number | 2 |
DOIs | |
State | Published - 1994 |
ASJC Scopus subject areas
- Statistics and Probability
- General Biochemistry, Genetics and Molecular Biology
- General Immunology and Microbiology
- General Agricultural and Biological Sciences
- Applied Mathematics