Development of a Bayesian response-adaptive trial design for the dexamethasone for excessive menstruation study
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Authors
Hansen, Christian Holm
Warner, Pamela
Parker, Richard A
Walker, Brian R
Critchley, Hilary Od
Weir, Christopher J
Issue Date
2017-12
Type
Article
Language
en_US
Keywords
Dose-Finding , Adaptive Design , Normal Dynamic Linear Model , Simulation , Trial Design Development , Menstruation
Alternative Title
Abstract
It is often unclear what specific adaptive trial design features lead to an efficient design which is also feasible to implement. This article describes the preparatory simulation study for a Bayesian response-adaptive dose-finding trial design. Dexamethasone for Excessive Menstruation aims to assess the efficacy of Dexamethasone in reducing excessive menstrual bleeding and to determine the best dose for further study. To maximise learning about the dose response, patients receive placebo or an active dose with randomisation probabilities adapting based on evidence from patients already recruited. The dose-response relationship is estimated using a flexible Bayesian Normal Dynamic Linear Model. Several competing design options were considered including: number of doses, proportion assigned to placebo, adaptation criterion, and number and timing of adaptations. We performed a fractional factorial study using SAS software to simulate virtual trial data for candidate adaptive designs under a variety of scenarios and to invoke WinBUGS for Bayesian model estimation. We analysed the simulated trial results using Normal linear models to estimate the effects of each design feature on empirical type I error and statistical power. Our readily-implemented approach using widely available statistical software identified a final design which performed robustly across a range of potential trial scenarios.
Description
Citation
Holm Hansen, C., Warner, P., Parker, R. A., Walker, B. R., Critchley, H. O., & Weir, C. J. (2017). Development of a Bayesian response-adaptive trial design for the Dexamethasone for Excessive Menstruation study. Statistical methods in medical research, 26(6), 2681–2699. https://doi.org/10.1177/0962280215606155
Publisher
Statistical Methods in Medical Research