Advantages of visualisations to evaluate and communicate adverse event information in randomised controlled trials
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Published version
Author(s)
Cornelius, Victoria
Cro, suzie
Phillips, Rachel
Type
Journal Article
Abstract
Background
Randomised controlled trials (RCTs) provide valuable information and inform the development of harm profiles of new treatments. Harms are typically assessed through the collection of adverse events (AEs). Despite AEs being routine outcomes collected in trials, analysis and reporting of AEs in journal articles are continually shown to be suboptimal. One key challenge is the large volume of AEs, which can make evaluation and communication problematic. Prominent practice is to report frequency tables of AEs by arm. Visual displays offer an effective solution to assess and communicate complex information; however, they are rarely used and there is a lack of practical guidance on what and how to visually display complex AE data.
Methods
In this article, we demonstrate the use of two plots identified to be beneficial for wide use in RCTs, since both can display multiple AEs and are suitable to display point estimates for binary, count, or time-to-event AE data: the volcano and dot plots. We compare and contrast the use of data visualisations against traditional frequency table reporting, using published AE information in two placebo-controlled trials, of remdesivir for COVID-19 and GDNF for Parkinson disease. We introduce statistical programmes for implementation in Stata.
Results/case study
Visualisations of AEs in the COVID-19 trial communicated a risk profile for remdesivir which differed from the main message in the published authors’ conclusion. In the Parkinson’s disease trial of GDNF, the visualisation provided immediate communication of harm signals, which had otherwise been contained within lengthy descriptive text and tables. Asymmetry in the volcano plot helped flag extreme events that were less obvious from review of the frequency table and dot plot. The dot plot allowed a more comprehensive representation by means of a more detailed summary.
Conclusions
Visualisations can better support investigators to assimilate large volumes of data and enable improved informal between-arm comparisons compared to tables. We endorse increased uptake for use in trial publications. Care in construction of visual displays needs to be taken as there can be potential to overemphasise treatment effects in some circumstances.
Randomised controlled trials (RCTs) provide valuable information and inform the development of harm profiles of new treatments. Harms are typically assessed through the collection of adverse events (AEs). Despite AEs being routine outcomes collected in trials, analysis and reporting of AEs in journal articles are continually shown to be suboptimal. One key challenge is the large volume of AEs, which can make evaluation and communication problematic. Prominent practice is to report frequency tables of AEs by arm. Visual displays offer an effective solution to assess and communicate complex information; however, they are rarely used and there is a lack of practical guidance on what and how to visually display complex AE data.
Methods
In this article, we demonstrate the use of two plots identified to be beneficial for wide use in RCTs, since both can display multiple AEs and are suitable to display point estimates for binary, count, or time-to-event AE data: the volcano and dot plots. We compare and contrast the use of data visualisations against traditional frequency table reporting, using published AE information in two placebo-controlled trials, of remdesivir for COVID-19 and GDNF for Parkinson disease. We introduce statistical programmes for implementation in Stata.
Results/case study
Visualisations of AEs in the COVID-19 trial communicated a risk profile for remdesivir which differed from the main message in the published authors’ conclusion. In the Parkinson’s disease trial of GDNF, the visualisation provided immediate communication of harm signals, which had otherwise been contained within lengthy descriptive text and tables. Asymmetry in the volcano plot helped flag extreme events that were less obvious from review of the frequency table and dot plot. The dot plot allowed a more comprehensive representation by means of a more detailed summary.
Conclusions
Visualisations can better support investigators to assimilate large volumes of data and enable improved informal between-arm comparisons compared to tables. We endorse increased uptake for use in trial publications. Care in construction of visual displays needs to be taken as there can be potential to overemphasise treatment effects in some circumstances.
Date Issued
2020-12-22
Date Acceptance
2020-11-16
Citation
Trials, 2020, 21
ISSN
1745-6215
Publisher
BioMed Central
Journal / Book Title
Trials
Volume
21
Copyright Statement
© 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Sponsor
National Institute for Health Research
Grant Number
DRF-2017-10-131
Subjects
Science & Technology
Life Sciences & Biomedicine
Medicine, Research & Experimental
Research & Experimental Medicine
Randomised controlled trials
Adverse events
Adverse reactions
Harms
Visualisation
Graphics
Reporting
Data analysis
SAFETY DATA
DRUG
Adverse events
Adverse reactions
Data analysis
Graphics
Harms
Randomised controlled trials
Reporting
Visualisation
Adenosine Monophosphate
Alanine
Antiparkinson Agents
Antiviral Agents
COVID-19
Computer Graphics
Data Accuracy
Data Analysis
Data Display
Data Visualization
Drug Monitoring
Drug-Related Side Effects and Adverse Reactions
Glial Cell Line-Derived Neurotrophic Factor
Humans
Parkinson Disease
Randomized Controlled Trials as Topic
Research Design
Humans
Parkinson Disease
Alanine
Adenosine Monophosphate
Antiparkinson Agents
Antiviral Agents
Drug Monitoring
Data Display
Research Design
Computer Graphics
Glial Cell Line-Derived Neurotrophic Factor
Randomized Controlled Trials as Topic
Drug-Related Side Effects and Adverse Reactions
Data Accuracy
Data Visualization
Data Analysis
COVID-19
Cardiovascular System & Hematology
General & Internal Medicine
1102 Cardiorespiratory Medicine and Haematology
1103 Clinical Sciences
Publication Status
Published
Article Number
ARTN 1028