PANDA is an open access & multidisciplinary practical educational resource for those who are keen to learn more about adaptive designs. The aim is to help them make baby steps & bridge the existing practical knowledge gap. See demo version here: panda.demo2.epigenesys.org.uk
Our target audience includes statisticians, clinicians, proposal developers, trial managers, data managers, health economists, and reviewers of grant applications. See the scope of what is covered by the PANDA toolkit: panda.demo2.epigenesys.org.uk/about_panda
The toolkit is structured to enable users to easily find content that is relevant to them. We take PANDA users through a learning journey from planning & design to reporting covering general considerations & specific types of adaptive designs.
Detailed case studies are presented focusing on practical aspects so that users can reproduce what was done & learn from them. We also illustrate the design, monitoring, & analysis of trials using specific adaptive designs including snippets on statistical code. For example:
We want PANDA to be a repository of practical resources such as available statistical software, guidance, tutorial papers, easy-to-read books with case studies, and other related online learning resources.
This is a community resource so we would like researchers to contribute by sharing their practical experiences of running adaptive trials including positive & negative experiences & lessons learned. Please feel free to contact us on related issues via panda-group@sheffield.ac.uk
While platform trials are clearly more prominent in COVID-19 than they were before the pandemic, many other COVID-19 trials use adaptive features. Some examples to follow. #adaptivedesigns
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The MATIS trial (NCT04581954) is a multi-arm multi-stage trial with early stopping for lack of benefit which seeks to evaluate treatments to prevent more severe disease. @JMSWason
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Similarly, the RECOVERY-Respiratory Support trial (ISRCTN16912075) seeks to identify optimal respiratory support using a multi-arm multi-stage structure. More details are here:
A number of COVID-19 trials use a platform structure and we will look at a few examples in the later stages of development in this thread. #adaptivedesigns
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The first treatment to be shown to benefit COVID-19 patients was identified within the ACTT trial. The platform allows to stop the evaluation for benefit and lack thereof as well as adding additional treatments.
The RECOVERY trial (recoverytrial.net) is with 38,000 patients to date the largest COVID trial. This has allowed several questions to be answered including dexamethasone as an effective treatment for severe disease. @PeterHorby@MartinLandray@RichardHaynes3 (3/6)
Throughout this week we have made the case that adaptive designs can be useful to improve efficiency and discussed practical challenges. Two recent papers have made the case that trials that are adaptive can be particularly helpful in the of COVID-19. #adaptivedesigns (1/4)
Different types of adaptations and their utility for studies of COVID-19 treatments have been reviewed in
But the utility of adaptive designs is not limited to studies of COVID-19 treatments. They can also be useful for trials that are impacted by COVID-19 as argued here.
The TAIloR trial (ISRCTN: 51069819) was a multi-arm multi-stage clinical trial that investigated the utility of different doses of telmisartan to reduce insulin resistance in HIV-positive individuals. @thomas_jaki (1/n).
The trial had one interim analysis during which doses that were deemed insufficiently promising were dropped from the study and in the study two of the initial three doses were dropped at this point. (2/n)
Due to the ability to eliminate insufficiently promising doses, fewer patients were exposed to doses that did not provide benefit to patients. (3/n)
The NOTACS trial (ISRCTN: 14092678) an adaptive, multicentre, parallel group, randomised controlled trial comparing the efficacy, cost-effectiveness and safety of 2 types of oxygen therapy in patients at high risk of post-operative pulmonary complication after cardiac surgery 1/n
After a pre-defined number of patients have been recruited and completed follow-up, we will use the data accumulated so far to re-estimate the nuisance parameters and use these to repeat the sample size calculation. (3/n)
Adaptive designs, and other innovative approaches, provide great benefits but are also more complex to run. In 2019, the Adaptive Designs Working Group started investigating what extra resource Clinical Trials Units (CTUs) might need to support #adaptivedesigns. (1/7)
Funded by the @NIHRresearch@UKCTUNetwork CTU Support Fund and led by Newcastle CTU, the “Costing Adaptive Trials (CAT)’ project set about answering this question. Step 1 was a snazzy logo. (2/7)
We then did a mock costing exercise. Seven CTUs agreed to cost five trial scenarios - each based on a real trial. For each, we outlined a non-adaptive and adaptive version. CTUs returned the staff resource and other costs that they’d put in a funding application. (3/7)