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Title: Statistical issues when incorporating emerging therapies into ongoing randomised clinical trials
Author: Howard, Dena Rose
ISNI:       0000 0004 7431 8345
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2018
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This research investigates the incorporation of an emerging therapy as a new randomised arm in a confirmatory clinical trial that is open to recruitment. It may take many years to run confirmatory trials from concept to reporting within a rapidly changing drug development environment, hence in order to optimally inform policy and practice it is advantageous for trials to be able to adapt to emerging developments. It is becoming increasingly desirable to researchers, regulators and patients to allow such an adaptation to be made within a clinical trial to ensure that new treatments are evaluated as quickly as possible, and resources are optimised. A comprehensive literature review confirmed that there is currently no clear methodological guidance on this topic, although treatment arms have been added into confirmatory trials in practice. Unfortunately the statistical considerations were not always appropriately addressed, often leading to uninterpretable or invalid outcomes. In this research, the necessary considerations to ensure statistical validity are identified and considered. The probability of false positive conclusions must be controlled, whilst ensuring that trial outcomes are not compromised or biased by the amendment. The need for multiple testing adjustment due to assessing multiple hypotheses within the same protocol and with shared control data is investigated, and recommendations are provided that apply to multi-arm trials in general. Adaptive analysis methods using p-value combination across the trial stages are compared to non-adaptive methods, with appropriate multiplicity adjustment considered. The findings are implemented to successfully incorporate a new experimental therapy within a large, confirmatory leukaemia trial. Guidance is presented detailing the requirements deemed necessary to ensure statistical validity, including recommendations so that the adaptation to add a new experimental arm to an ongoing trial is appropriate and acceptable. It is hoped that this will encourage consideration of adding arms more widely in future.
Supervisor: Brown, Julia M. ; Gregory, Walter M. ; Todd, Susan Sponsor: National Institute for Health Research
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available