Ryan, Elizabeth G., Bruce, Julie, Metcalfe, Andrew J., Stallard, Nigel, Lamb, Sarah E., Viele, Kert, Young, Duncan and Gates, Simon (2019) Using Bayesian adaptive designs to improve phase III trials : a respiratory care example. BMC Medical Research Methodology, 19 . 99. doi:10.1186/s12874-019-0739-3 ISSN 1471-2288.
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Abstract
Background
Bayesian adaptive designs can improve the efficiency of trials, and lead to trials that can produce high quality evidence more quickly, with fewer patients and lower costs than traditional methods. The aim of this work was to determine how Bayesian adaptive designs can be constructed for phase III clinical trials in critical care, and to assess the influence that Bayesian designs would have on trial efficiency and study results.
Methods
We re-designed the High Frequency OSCillation in Acute Respiratory distress syndrome (OSCAR) trial using Bayesian adaptive design methods, to allow for the possibility of early stopping for success or futility. We constructed several alternative designs and studied their operating characteristics via simulation. We then performed virtual re-executions by applying the Bayesian adaptive designs using the OSCAR data to demonstrate the practical applicability of the designs.
Results
We constructed five alternative Bayesian adaptive designs and identified a preferred design based on the simulated operating characteristics, which had similar power to the original design but recruited fewer patients on average. The virtual re-executions showed the Bayesian sequential approach and original OSCAR trial yielded similar trial conclusions. However, using a Bayesian sequential design could have led to a reduced sample size and earlier completion of the trial.
Conclusions
Using the OSCAR trial as an example, this case study found that Bayesian adaptive designs can be constructed for phase III critical care trials. If the OSCAR trial had been run using one of the proposed Bayesian adaptive designs, it would have terminated at a smaller sample size with fewer deaths in the trial, whilst reaching the same conclusions. We recommend the wider use of Bayesian adaptive approaches in phase III clinical trials.
Trial registration
OSCAR Trial registration ISRCTN, ISRCTN10416500. Retrospectively registered 13 June 2007.
| Item Type: | Journal Article |
|---|---|
| Subjects: | R Medicine > RC Internal medicine |
| Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences > Statistics and Epidemiology Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School |
| Library of Congress Subject Headings (LCSH): | Respiratory distress syndrome -- Patients -- Mortality, Bayesian statistical decision theory |
| Journal or Publication Title: | BMC Medical Research Methodology |
| Publisher: | BioMed Central Ltd. |
| ISSN: | 1471-2288 |
| Official Date: | 14 May 2019 |
| Dates: | Date Event 14 May 2019 Published 22 April 2019 Accepted |
| Volume: | 19 |
| Article Number: | 99 |
| DOI: | 10.1186/s12874-019-0739-3 |
| Status: | Peer Reviewed |
| Publication Status: | Published |
| Access rights to Published version: | Open Access (Creative Commons open licence) |
| Date of first compliant deposit: | 28 May 2019 |
| Date of first compliant Open Access: | 30 May 2019 |
| RIOXX Funder/Project Grant: | Project/Grant ID RIOXX Funder Name Funder ID |
| Related URLs: | |
| URI: | https://wrap.warwick.ac.uk/117580/ |
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