Appropriate design and reporting of superiority, equivalence and non-inferiority clinical trials incorporating a benefit–risk assessment: the BRAINS study including expert workshop
Totton N, Julious SA, Coates E, Hughes DA, Cook JA, Biggs K, Hewitt C, Day S, Cook A
Record ID 32018005348
Authors' objectives: Randomised controlled trials are designed to assess the superiority, equivalence or non-inferiority of a new health technology, but which trial design should be used is not always obvious in practice. In particular, when using equivalence or non-inferiority designs, multiple outcomes of interest may be important for the success of a trial, despite the fact that usually only a single primary outcome is used to design the trial. Benefit–risk methods are used in the regulatory clinical trial setting to assess multiple outcomes and consider the trade-off of the benefits against the risks, but are not regularly implemented in publicly funded trials. The aim of the project is to aid the design of clinical trials with multiple outcomes of interest by defining when each trial design is appropriate to use and identifying when to use benefit–risk methods to assess outcome trade-offs (qualitatively or quantitatively) in a publicly funded trial setting. Randomised controlled trials (RCTs) are the gold standard of health technology evaluation. They can be designed to assess the objective of superiority, equivalence or non-inferiority; the objective is determined by the selected research question and primary outcome. However, in practice, selecting the most appropriate outcome measure and, subsequently, trial design can be difficult. In addition, some trials may have more than one outcome of importance to consider; this is particularly the case when using equivalence or non-inferiority designs, as a secondary superiority outcome is often important. This multidimensionality is not considered if the focus of a trial’s success is a single primary outcome. Benefit–risk (B–R) methods are used in the clinical trial regulatory setting to assess multiple outcomes and consider the trade-off of the benefits against the risks, but they are not regularly implemented in publicly funded UK trials. This guidance document aims to fill a knowledge gap, with a focus on publicly funded clinical trials throughout. This is undertaken by first providing recommendations on the most appropriate trial design to select and then identifying when a B–R method may be used within a trial to assess outcome trade-offs, whether this be qualitatively or quantitatively.
Authors' results and conclusions: We created a list of 19 factors to aid researchers in selecting the most appropriate trial design, containing the following overarching sections: population, intervention, comparator, outcomes, feasibility and perspectives. Six key reasons that indicate a benefit–risk method should be considered within a trial were identified: (1) when the success of the trial depends on more than one outcome; (2) when important outcomes within the trial are in competing directions (i.e. a health technology is better for one outcome, but worse for another); (3) to allow patient preferences to be included and directly influence trial results; (4) to provide transparency on subjective recommendations from a trial; (5) to provide consistency in the approach to presenting results from a trial; and (6) to synthesise multiple outcomes into a single metric. Further information was provided to support the use of benefit–risk methods in appropriate circumstances, including the following: methods identified from the review were collated into different groupings and described to aid the selection of a method; potential implementation of methods throughout the trial process were provided and discussed (with examples); and general considerations were described for those using benefit–risk methods. Finally, a checklist of five pieces of information that should be present when reporting benefit–risk methods was defined, with two additional items specifically for reporting the results. These recommendations will assist research teams in selecting which trial design to use and deciding whether or not a benefit–risk method could be included to ensure research questions are answered appropriately. Additional information is provided to support consistent use and clear reporting of benefit–risk methods in the future. The recommendations can also be used by funding committees to confirm that appropriate considerations of the trial design have been made. To aid researchers in selecting an appropriate trial design, a list of 19 factors to consider was created. This list relates to six different sections: population, intervention, comparator, outcomes, feasibility and perspectives. Each factor is described in detail and the list of factors is used in conjunction with examples of trial designs to explain why a particular design might be chosen. Once the appropriate trial design has been selected, considering a B–R method may be justified if one of six key reasons is present: The success of the trial depends on more than one outcome. Important outcomes within the trial are in competing directions (i.e. a health technology is anticipated to be better on one outcome but worse on another). To allow patient preferences to be included and directly influence trial results. To provide transparency on subjective recommendations from a trial. To provide consistency in the approach to presenting results from a trial. To synthesise multiple outcomes into a single metric. In particular, the first reason (considering multiple outcomes) is often applicable to equivalence and non-inferiority trials, in which success also depends on the superiority of a secondary outcome; a description of this was flagged as important in the consensus workshop. Owing to the range of B–R methods available, difficulties arise when discussing a globally recommended B–R assessment. To aid with this, the 92 methods that were identified from the literature review as potentially suitable for use in publicly funded RCTs were categorised into seven groups. The first group was an overarching framework that provided structure for a B–R assessment from start to finish. The most basic group, the second group, was the use of a narrative summary of the benefits and risks; although this is not an official method, it was considered important to provide such a summary at the end of a trial. The next two groups comprised a summary table with a specific structure to contain all relevant information, before moving on to methods that can quantitatively trade off multiple outcomes. The final three groups related to preference elicitation from stakeholders, uncertainty estimation and visualisations. Importantly, these groupings show that quantitative methods are not always necessary or appropriate. However, this should not negate the need for a summary or narrative discussion of subjective interpretations. As it could be argued that favourable and unfavourable outcomes are present in all RCTs, a narrative summary of the benefits and risks would add value to the reports of all publicly funded trials. It is noted that some methods require additional data to be collected, so the need for these added resources and expenses should be considered on a case-by-case basis. To provide some clarity on this, the methods groups were linked with different stages of the RCT, from design through to conclusion and dissemination. Group discussions identified the difficulty of additional work during the trial design stage, which is something that this breakdown of the methods at different stages hopes to address. Finally, when a B–R method has been deemed important to use, whether that be a narrative summary or a quantitative trade-off method, the reporting should be transparent and consistent. A checklist of items to include when reporting the trial design in applications or protocols was created, as was a separate checklist for reporting the trial findings. There are five pieces of information that are recommended when reporting the trial design: a heading of ‘benefit–risk’ explicit use of the term ‘benefit–risk’ a plan for B–R assessment the anticipated benefits and risks discussion of the B–R balance with patient representatives. Two further items are recommended when reporting the results of the trial: a summary table of benefits and risks reporting of quality-adjusted life-years in terms of B–R. The advice and recommendations provided in this report aim to improve the selection of a trial design, understanding of B–R methods and when it is appropriate to include them and how to effectively report the use of the methods. This guidance is aimed at researchers designing publicly funded RCTs, such as those by the National Institute for Health and Care Research or the Medical Research Council, as well as those on the funding panels. Using these recommendations will improve the design of RCTs, as well as the clarity and consistency of reporting the benefits and risks associated with the health technologies being evaluated. Further research should focus on providing more detail on each of the different B–R methods and recommendations on how they can be fully integrated in publicly funded clinical trials. Practical barriers to this implementation could be assessed to ensure that the information presented in this report can be used most effectively.
Authors' methods: A range of methods was used to elicit expert opinion to answer the project objectives, including a web-based survey of relevant researchers, a rapid review of current literature and a 2-day consensus workshop of experts (in 2019). This research was limited in scope and should be considered in conjunction with other trial design methodologies to assess appropriateness. In addition, further research is needed to provide concrete information about which benefit–risk methods are best to use in publicly funded trials, along with recommendations that are specific to each method. In this project, three key methodologies were used across three work packages (WPs) to elicit expert opinion on trial design and B–R methods. These were: WP1, a web-based survey of relevant researchers in the area. The survey was sent to researchers through appropriate mailing lists, as well as through known contacts and networks, for completion. WP2, a rapid review of current literature. The review built on previous reviews to find available B–R methods, but, in addition to previous work, we retrieved details on which of these could be implemented in publicly funded studies, as well as details on each method’s strengths and weaknesses. WP3, a 2-day expert consensus workshop. Results from the survey and the review were presented to a group of experts (n = 15) who had been contacted because of their knowledge of and interest in the area. The nominal group technique was used to select items for inclusion in checklists. Open discussions, supported by the presented findings, were used to gain opinions on reasons for including B–R methods within a trial. Open discussions were thematically analysed to identify the key points discussed and support the results of the checklists.
Project Status: Completed
URL for project: https://www.journalslibrary.nihr.ac.uk/programmes/hta/NIHR129832
Year Published: 2023
URL for published report: https://www.journalslibrary.nihr.ac.uk/hta/BHQZ7691
URL for additional information: English
English language abstract: An English language summary is available
Publication Type: Full HTA
Country: England, United Kingdom
- Clinical Trials as Topic
- Cost-Benefit Analysis
- Randomized Controlled Trials as Topic
- Research Design
Organisation Name: NIHR Health Technology Assessment programme
Contact Address: NIHR Journals Library, National Institute for Health and Care Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK
Contact Name: email@example.com
Contact Email: firstname.lastname@example.org
This is a bibliographic record of a published health technology assessment from a member of INAHTA or other HTA producer. No evaluation of the quality of this assessment has been made for the HTA database.