Flight, L., Arshad, F., Barnsley, R., Patel, K., Julious, S., Brennan, A. and Todd, S.
ORCID: https://orcid.org/0000-0002-9981-923X
(2019)
A review of clinical trials with an adaptive design and health economic analysis.
Value in Health, 22 (4).
pp. 391-398.
ISSN 1098-3015
doi: 10.1016/j.jval.2018.11.008
Abstract/Summary
An adaptive design uses data collected as a clinical trial progresses to inform modifications to the trial. Hence, adaptive designs and health economics aim to facilitate efficient and accurate decision-making. However, it is unclear whether the methods are considered together in the design, analysis and reporting of trials. This review aims to establish how health economic outcomes are utilised in the design, analysis and reporting of adaptive designs. Registered and published trials up to August 2016 with an adaptive design and health economic analysis were identified. The use of health economics in the design, analysis and reporting was assessed. Summary statistics are presented and recommendations formed based on the research team’s experiences and a practical interpretation of the results. Thirty-seven trials with an adaptive design and health economic analysis were identified. It was not clear whether the health economic analysis accounted for the adaptive design in 17/37 trials where this was thought necessary, nor whether health economic outcomes were utilised at the interim analysis for 18/19 of trials with results. The reporting of health economic results was sub-optimal for the (17/19) trials with published results. Appropriate consideration is rarely given to the health economic analysis of adaptive designs. Opportunities to utilise health economic outcomes in the design and analysis of adaptive trials are being missed. Further work is needed to establish whether adaptive designs and health economic analyses can be used together to increase the efficiency of health technology assessments without compromising accuracy.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/80755 |
| Identification Number/DOI | 10.1016/j.jval.2018.11.008 |
| Refereed | Yes |
| Divisions | Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics |
| Publisher | Elsevier |
| Download/View statistics | View download statistics for this item |
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