Laura Flight1, Fahid Arshad2, Rachel Barnsley2, Kian Patel2, Steven Julious2, Alan Brennan3, Susan Todd4. 1. Medical Statistics Group, School of Health and Related Research, University of Sheffield, Sheffield, England, UK. Electronic address: l.flight@sheffield.ac.uk. 2. Medical Statistics Group, School of Health and Related Research, University of Sheffield, Sheffield, England, UK. 3. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, England, UK. 4. Department of Mathematics and Statistics, University of Reading, Reading, England, UK.
Abstract
OBJECTIVE: 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. Nevertheless, 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 used in the design, analysis, and reporting of adaptive designs. METHODS: 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. 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 used at the interim analysis for 18/19 of trials with results. The reporting of health economic results was suboptimal for the (17/19) trials with published results. CONCLUSIONS: Appropriate consideration is rarely given to the health economic analysis of adaptive designs. Opportunities to use 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.
OBJECTIVE: 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. Nevertheless, 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 used in the design, analysis, and reporting of adaptive designs. METHODS: 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. 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 used at the interim analysis for 18/19 of trials with results. The reporting of health economic results was suboptimal for the (17/19) trials with published results. CONCLUSIONS: Appropriate consideration is rarely given to the health economic analysis of adaptive designs. Opportunities to use 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.
Authors: Munyaradzi Dimairo; Philip Pallmann; James Wason; Susan Todd; Thomas Jaki; Steven A Julious; Adrian P Mander; Christopher J Weir; Franz Koenig; Marc K Walton; Jon P Nicholl; Elizabeth Coates; Katie Biggs; Toshimitsu Hamasaki; Michael A Proschan; John A Scott; Yuki Ando; Daniel Hind; Douglas G Altman Journal: BMJ Date: 2020-06-17
Authors: Mathyn Vervaart; Mark Strong; Karl P Claxton; Nicky J Welton; Torbjørn Wisløff; Eline Aas Journal: Med Decis Making Date: 2021-12-30 Impact factor: 2.749
Authors: James M S Wason; Munyaradzi Dimairo; Katie Biggs; Sarah Bowden; Julia Brown; Laura Flight; Jamie Hall; Thomas Jaki; Rachel Lowe; Philip Pallmann; Mark A Pilling; Claire Snowdon; Matthew R Sydes; Sofía S Villar; Christopher J Weir; Nina Wilson; Christina Yap; Helen Hancock; Rebecca Maier Journal: BMC Med Date: 2022-08-10 Impact factor: 11.150
Authors: Munyaradzi Dimairo; Philip Pallmann; James Wason; Susan Todd; Thomas Jaki; Steven A Julious; Adrian P Mander; Christopher J Weir; Franz Koenig; Marc K Walton; Jon P Nicholl; Elizabeth Coates; Katie Biggs; Toshimitsu Hamasaki; Michael A Proschan; John A Scott; Yuki Ando; Daniel Hind; Douglas G Altman Journal: Trials Date: 2020-06-17 Impact factor: 2.279
Authors: Jay J H Park; Rebecca F Grais; Monica Taljaard; Etheldreda Nakimuli-Mpungu; Fyezah Jehan; Jean B Nachega; Nathan Ford; Denis Xavier; Andre P Kengne; Per Ashorn; Maria Eugenia Socias; Zulfiqar A Bhutta; Edward J Mills Journal: Lancet Glob Health Date: 2021-05 Impact factor: 26.763