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Table 3 Summary of key recommendations and proposed actions from the interviews and focus groups with members of the public, researchers and decision-makers

From: How can health economics be used in the design and analysis of adaptive clinical trials? A qualitative analysis

Issue

Recommendation

Action

Clinical effectiveness is the main focus when thinking about the aims of a clinical trial

The importance of clinical effectiveness should be reflected in the development of methods for using health economics in adaptive trials. Possible approaches include:

• Using early examinations of the trial to check that all health economic data are being collected as required

• Using early trial data to update the health economic model

• Using a hierarchy of interim decision rules where any decisions made based on cost-effectiveness depend on decisions made about clinical outcomes

• Only considering health economic outcomes at later examinations of the data

• Using health economic data to make modifications to the trial such as increasing the sample size but not major changes such as stopping the trial early

Explore how existing methods for the use of health economic-based stopping rules would work in the real-world setting, by applying the methods to a diverse range of case studies

Study participants appreciate the importance of cost-effectiveness to decision-makers, but they consider this to be secondary to clinical effectiveness

There needs to be a change in the mentality of the research community towards the role of health economics and cost-effectiveness in healthcare decision-making

Development of materials to educate on the importance and ethical motivations for thinking about cost-effectiveness. This could be written with members of the public and developed into workshops, online materials and leaflets

Stakeholders may not be familiar with the methods of adaptive designs or value of information analysis and their potential advantages and limitations

Develop software and tutorial style case studies for researchers to help them understand the methods and allow them to interpret the results of trials using this approach or use these methods in their own research Development of plain English summaries and case studies highlighting the impact of the methods on patients and the public

A Practical Adaptive and Novel Designs and Analysis (PANDA) Toolkit is under development that aims to provide researchers with training materials on adaptive design clinical trials [58]. This could include materials aimed at members of the public Organise workshops (such as at conferences) for researchers, highlighting the potential for the methods to be used together and issues to consider

If health economics is to inform decisions made using early examinations of data, there may be a need for this specialist knowledge on trial committees

Include health economists on DMECs where health economics is used as part of the design and analysis of adaptive trials

Existing resources that help research teams identify DMEC statisticians, such as StatLink [40], could be extended to identify health economists. All DMEC members could be paid for their contribution and time Use mock DMECs to allow members to review the health economic and clinical data and see where issues with using the health economic data arise

Using health economics in the design and analysis of adaptive trials will require more work before the trial is funded, when researchers may not be paid for this work

Funding bodies should provide alternative funding options that allow researchers to develop new designs Researchers could include time at the start of a study to fully develop an adaptive trial design that uses health economics Researchers should look for methodology grants to fund the development of designs

Groups representing statisticians and health economists (such as the MRC Adaptive Designs Working Group and ISPOR—the Professional Society for Health Economics and Outcomes Research) should work together to persuade funders and regulators of the need for alternative ways to fund adaptive clinical trials and the benefits this will have to health research and maximising limited research budgets

There is currently limited interaction between health economists and statisticians working on trials and more generally between the two research communities

Encourage statisticians and health economists to work together and increase communication to facilitate the implementation of health economics in adaptive trials by sharing expertise

Locally, health economists and statisticians working on the same clinical trial should have regular meetings throughout the study. Nationally, there could be joint events between groups such as the NIHR Statistics Group and the Health Economic Study Group to discuss common issues and encourage training in statistics for health economists and health economics for statisticians

If health economics is to be used in adaptive clinical trials, the methods need to be outlined in advance so the results of the trial are still valid and robust

Before the trial begins, researchers should outline how health economics is going to be used in the trial and how the early examinations of the data will be used to calculate cost-effectiveness and inform decision-making

Extend current work developing guidance for health economic analysis plans to think about specific issues that might arise in adaptive clinical trials [42]. This will likely require health economists to have some experience of working on an adaptive trial

Calculating the costs of conducting an adaptive clinical trial can be complicated. For example, one must provide justifications of costs and cost projections in a grant application

It is important to understand the costs of conducting an adaptive trial such as the costs of finding patients, training staff and analysing data so that one can compare adaptive and non-adaptive trial designs and inform stopping rules based on health economics

Develop a standardised approach for calculating the costs of an adaptive clinical trial, illustrated using a case study