Accessibility navigation

Methodological aspects of multi-arm adaptive clinical trials

Abery, J. E. (2021) Methodological aspects of multi-arm adaptive clinical trials. PhD thesis, University of Reading

Text - Thesis
· Please see our End User Agreement before downloading.

[img] Text - Thesis Deposit Form
· Restricted to Repository staff only

[img] Text - Thesis Deposit Form
· Restricted to Repository staff only

[img] Text - Thesis Deposit Form
· Restricted to Repository staff only

[img] Text - Thesis Deposit Form
· Restricted to Repository staff only

[img] Text - Thesis Deposit Form
· Restricted to Repository staff only


It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.48683/1926.00105276


In the present healthcare climate, there is an urgent need to increase the efficiency with which novel therapies are evaluated. Multi-arm adaptive trials allow multiple treatments to be tested within a single protocol and offer the facility to respond to emerging data. Such trials allow treatment arms to be dropped or even added partway through the trial, directing resources to promising treatments. In this thesis, methodologies for two-stage adaptive trials with binary outcomes are explored, focussing on those approaches in which an intermediate outcome may be used for the purposes of treatment selection. Methodology for the multi-arm multi-stage approach developed by Royston et al. (2003, 2011), here denoted MAMS(R), is extended so that feasible and admissible trial designs may be obtained under the log odds ratio parameterisation. A simulation study suggests that these MAMS(R) designs perform favourably compared with the well-established combination method when a common outcome is monitored, but not when an intermediate outcome is incorporated. A proposal is made for increasing the efficiency and flexibility of MAMS(R) methodology by implementing conditional error calculations within a closed testing procedure. This approach allows the trial design to be updated at the interim analysis, resulting in gains in efficiency, particularly in trials where an intermediate outcome is used and where some promising treatments are dropped. The conditional error approach is then extended to offer the facility of adding a new treatment arm to an ongoing multi-arm adaptive trial. The procedure achieves good power, ensures Type I error rate control and performs particularly well if a new treatment arm is added when promising treatments have been dropped from the trial. Recommendations for using the new developments are given. It is hoped that this research will widen the use of MAMS(R) methodology in practice.

Item Type:Thesis (PhD)
Thesis Supervisor:Todd, S.
Thesis/Report Department:Department of Mathematics and Statistics
Identification Number/DOI:
Divisions:Science > School of Mathematical, Physical and Computational Sciences
ID Code:105276
Date on Title Page:2020


Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation