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Visualising harms in publications of randomised controlled trials: consensus and recommendations
Rachel Phillips1,2, Suzie Cro3, Graham Wheeler3
1Imperial Clinical Trials Unit, School of Public Health, Imperial College London, London, UK r.phillips@imperial.ac.uk.
BMJ (Clinical Research Ed.)
|May 16, 2022
Summary
Visualizations can improve how clinical trial harms are communicated. This study recommends 10 visualizations to present harm outcomes clearly, aiding interpretation in research publications.
Area of Science:
- Clinical Trials and Biostatistics
- Data Visualization in Medical Research
- Scientific Communication
Background:
- Effective communication of harm outcomes in randomized controlled trials (RCTs) is crucial for patient safety and informed decision-making.
- Traditional reporting methods, such as frequency tables, may not always convey the full picture of trial-related harms.
- There is a need for standardized, visually intuitive methods to present harm data in RCT publications.
Purpose of the Study:
- To develop evidence-based recommendations for visually presenting harm outcomes in randomized controlled trials.
- To enhance the clarity and interpretability of harm data for researchers, clinicians, and other stakeholders.
- To provide guidance on selecting appropriate visualizations based on outcome type and research scenario.
Main Methods:
- A consensus study involving experts in clinical trials, statistics, health economics, and data graphics.
- Methodological review of statistical methods and existing visualizations related to harm outcomes.
- Series of consensus meetings where participants critically appraised and voted on candidate visualizations, achieving at least 60% agreement.
Main Results:
- Ten distinct visualizations are recommended for reporting harm outcomes in RCT publications.
- The choice of visualization depends on the type of outcome (e.g., binary, continuous, time-to-event) and the specific research context.
- A decision tree is provided to assist trialists in selecting the most appropriate visualization, with examples and implementation guidance.
Conclusions:
- Visualizations offer a powerful alternative to traditional tables for communicating trial harms, leading to clearer information presentation.
- Increased use of recommended visualizations can improve the interpretation of harm profiles in clinical trial reports.
- While visualizations enhance understanding, statisticians and trial teams must select the most appropriate methods, considering limitations and alongside raw data analysis.
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