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Comparing the Value of Data Visualization Methods for Communicating Harms in Clinical Trials.

Publication ,  Journal Article
Qureshi, R; Chen, X; Goerg, C; Mayo-Wilson, E; Dickinson, S; Golzarri-Arroyo, L; Hong, H; Phillips, R; Cornelius, V; McAdams DeMarco, M; Li, T ...
Published in: Epidemiol Rev
December 21, 2022

In clinical trials, harms (i.e., adverse events) are often reported by simply counting the number of people who experienced each event. Reporting only frequencies ignores other dimensions of the data that are important for stakeholders, including severity, seriousness, rate (recurrence), timing, and groups of related harms. Additionally, application of selection criteria to harms prevents most from being reported. Visualization of data could improve communication of multidimensional data. We replicated and compared the characteristics of 6 different approaches for visualizing harms: dot plot, stacked bar chart, volcano plot, heat map, treemap, and tendril plot. We considered binary events using individual participant data from a randomized trial of gabapentin for neuropathic pain. We assessed their value using a heuristic approach and a group of content experts. We produced all figures using R and share the open-source code on GitHub. Most original visualizations propose presenting individual harms (e.g., dizziness, somnolence) alone or alongside higher level (e.g., by body systems) summaries of harms, although they could be applied at either level. Visualizations can present different dimensions of all harms observed in trials. Except for the tendril plot, all other plots do not require individual participant data. The dot plot and volcano plot are favored as visualization approaches to present an overall summary of harms data. Our value assessment found the dot plot and volcano plot were favored by content experts. Using visualizations to report harms could improve communication. Trialists can use our provided code to easily implement these approaches.

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Published In

Epidemiol Rev

DOI

EISSN

1478-6729

Publication Date

December 21, 2022

Volume

44

Issue

1

Start / End Page

55 / 66

Location

United States

Related Subject Headings

  • Neuralgia
  • Humans
  • Gabapentin
  • Epidemiology
  • Data Visualization
  • 4206 Public health
  • 4202 Epidemiology
  • 11 Medical and Health Sciences
 

Citation

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Qureshi, R., Chen, X., Goerg, C., Mayo-Wilson, E., Dickinson, S., Golzarri-Arroyo, L., … Li, T. (2022). Comparing the Value of Data Visualization Methods for Communicating Harms in Clinical Trials. Epidemiol Rev, 44(1), 55–66. https://doi.org/10.1093/epirev/mxac005
Qureshi, Riaz, Xiwei Chen, Carsten Goerg, Evan Mayo-Wilson, Stephanie Dickinson, Lilian Golzarri-Arroyo, Hwanhee Hong, et al. “Comparing the Value of Data Visualization Methods for Communicating Harms in Clinical Trials.Epidemiol Rev 44, no. 1 (December 21, 2022): 55–66. https://doi.org/10.1093/epirev/mxac005.
Qureshi R, Chen X, Goerg C, Mayo-Wilson E, Dickinson S, Golzarri-Arroyo L, et al. Comparing the Value of Data Visualization Methods for Communicating Harms in Clinical Trials. Epidemiol Rev. 2022 Dec 21;44(1):55–66.
Qureshi, Riaz, et al. “Comparing the Value of Data Visualization Methods for Communicating Harms in Clinical Trials.Epidemiol Rev, vol. 44, no. 1, Dec. 2022, pp. 55–66. Pubmed, doi:10.1093/epirev/mxac005.
Qureshi R, Chen X, Goerg C, Mayo-Wilson E, Dickinson S, Golzarri-Arroyo L, Hong H, Phillips R, Cornelius V, McAdams DeMarco M, Guallar E, Li T. Comparing the Value of Data Visualization Methods for Communicating Harms in Clinical Trials. Epidemiol Rev. 2022 Dec 21;44(1):55–66.
Journal cover image

Published In

Epidemiol Rev

DOI

EISSN

1478-6729

Publication Date

December 21, 2022

Volume

44

Issue

1

Start / End Page

55 / 66

Location

United States

Related Subject Headings

  • Neuralgia
  • Humans
  • Gabapentin
  • Epidemiology
  • Data Visualization
  • 4206 Public health
  • 4202 Epidemiology
  • 11 Medical and Health Sciences