4.5 Article

Visualising harms in publications of randomised controlled trials: consensus and recommendations

Journal

BMJ-BRITISH MEDICAL JOURNAL
Volume 377, Issue -, Pages -

Publisher

BMJ PUBLISHING GROUP
DOI: 10.1136/bmj-2021-068983

Keywords

-

Funding

  1. National Institute for Health and Care Research (NIHR) [DRF-2017-10-131]
  2. NIHR advanced fellowship [NIHR300593]
  3. NIHR
  4. MRC [MC_UU_00004/07, MC_UU_12023/21, MC_UU_12023/29]
  5. National Institutes of Health Research (NIHR) [DRF-2017-10-131, NIHR300593] Funding Source: National Institutes of Health Research (NIHR)
  6. MRC [MC_UU_00004/07] Funding Source: UKRI

Ask authors/readers for more resources

This study aims to improve the communication of harm outcomes in publications of randomised controlled trials through the development of recommendations for visually presenting harm outcomes. Through a consensus study, experts in clinical trials identified and recommended 10 visualisations, along with a decision tree to assist trialists in choosing appropriate visualisations. Visualisations provide a powerful tool for communicating harm in clinical trials, offering clearer presentation of information and more informative interpretations.
OBJECTIVE To improve communication of harm in publications of randomised controlled trials via the development of recommendations for visually presenting harm outcomes. DESIGN Consensus study. SETTING 15 clinical trials units registered with the UK Clinical Research Collaboration, an academic population health department, Roche Products, and The BMJ. PARTICIPANTS Experts in clinical trials: 20 academic statisticians, one industry statistician, one academic health economist, one data graphics designer, and two clinicians. MAIN OUTCOME MEASURES A methodological review of statistical methods identified visualisations along with those recommended by consensus group members. Consensus on visual recommendations was achieved (at least 60% of the available votes) over a series of three meetings with participants. The participants reviewed and critically appraised candidate visualisations against an agreed framework and voted on whether to endorse each visualisation. Scores marginally below this threshold (50-60%) were revisited for further discussions and votes retaken until consensus was reached. RESULTS 28 visualisations were considered, of which 10 are recommended for researchers to consider in publications of main research findings. The choice of visualisations to present will depend on outcome type (eg, binary, count, time-to-event, or continuous), and the scenario (eg, summarising multiple emerging events or one event of interest). A decision tree is presented to assist trialists in deciding which visualisations to use. Examples are provided of each endorsed visualisation, along with an example interpretation, potential limitations, and signposting to code for implementation across a range of standard statistical software. Clinician feedback was incorporated into the explanatory information provided in the recommendations to aid understanding and interpretation. CONCLUSIONS Visualisations provide a powerful tool to communicate harms in clinical trials, offering an alternative perspective to the traditional frequency tables. Increasing the use of visualisations for harm outcomes in clinical trial manuscripts and reports will provide clearer presentation of information and enable more informative interpretations. The limitations of each visualisation are discussed and examples of where their use would be inappropriate are given. Although the decision tree aids the choice of visualisation, the statistician and clinical trial team must ultimately decide the most appropriate visualisations for their data and objectives. Trialists should continue to examine crude numbers alongside visualisations to fully understand harm profiles.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available