Discover and read the best of Twitter Threads about #AdaptiveDesigns

Most recents (6)

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

(1/4)
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

(2/4)
Similarly, the RECOVERY-Respiratory Support trial (ISRCTN16912075) seeks to identify optimal respiratory support using a multi-arm multi-stage structure. More details are here:

warwick.ac.uk/fac/sci/med/re…

@recovery_rs @WarwickCTU

(3/4)
Read 4 tweets
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
(1/6)
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.

nejm.org/doi/full/10.10…

@NIAIDNews
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)
Read 6 tweets
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

tandfonline.com/doi/full/10.10…
(2/4)
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.

tandfonline.com/doi/full/10.10…
(3/4)
Read 4 tweets
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) Image
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)
Read 7 tweets
We’re now passing over to @DrGWheeler to walk us through software for adaptive designs!
Sorry, attempt 2 (@JMSWason not too experienced with adding gifs!)
In 2020 Michael Grayling @UniofNewcastle & @DrGWheeler @ucl published a review of software for #AdaptiveDesigns in clinical trials.

Lack of available software is a known barrier to using better trial designs in practice. Q: “How bad is this problem?” 1/9
journals.sagepub.com/doi/full/10.11…
Our research questions were:

1. How many articles proposing new adaptive designs included code with the paper, or a link to code available elsewhere?

2. Which adaptive design approaches and features are well supported by current software, and (importantly), which are not? 2/9
Read 10 tweets
The fact that adaptive designs allow prespecified changes to be made to an ongoing trial based on interim results also creates the potential for biases to be introduced at different stages of the trial. #AdaptiveDesigns
This brings additional demands for transparency and adequate reporting of adaptive trials so that consumers of research findings can make informed judgements about the validity and trustworthiness of results. #AdaptiveDesigns
Inadequately reported adaptive trials that are difficult to interpret their results and reproduce methods, results, and inference. This can severely undermine public confidence in research findings to influence clinical practice resulting in research waste.
Read 9 tweets

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