important information
quickly and memorably.
multiple layers
of complexity.
guidance simply
and visually.
imagery to communicate quickly and impactfully.
treatment
effect
patients
decision
making
but raw numbers alone can be overwhelming.
to express our data more impactfully and more effectively.
endpoints in a simple visual. This provides a more complete picture
of the data, including the treatment effect on individual components.
Clinical outcomes are typically displayed in order of severity.
The Y-axis represents the cumulative percentage of patients
experiencing the event over time.
Additionally, a horizontal violin plot can be used to illustrate
continuous outcomes, such as eGFR,
for patients who did not
experience any hard
events, thereby offering
insight into the distribution
of continuous measures.
a third party who is solely responsible for its contents.
the Maraca plot
a combined bar and forest plot, shows details of the different components as they are added one by one.
helps infer the win probability of the active treatment versus the control by highlighting areas where the active treatment outperforms the control. This is indicated by deviations from the diagonal line.
visually explores various ‘what-if’ scenarios, such as identifying combinations of hazard ratio and mean difference in continuous distributions that result in the same win odds.
1. Karpefors M, Lindholm D, Gasparyan SB. The maraca plot: A novel visualization of
hierarchical composite endpoints. Clin Trials. 2022;20(1):84–88.
2. Heerspink HJL, Jongs N, Schloemer P, et al. Development and validation of a new hierarchical composite end point for clinical trials of kidney disease progression. J Am Soc Nephrol. 2023;34(11):2025–2038.
3. Little DJ, Gasparyan SB, Schloemer P, et al. Validity and utility of a hierarchical composite endpoint for clinical trials of kidney disease progression: A review. J Am Soc Nephrol. 2023;34(10):1928–1935.
4. Manuscript submitted for publication. Available at: https://arxiv.org/abs/2506.02287. Last accessed June 2025.
5. Kovesdy CP. Epidemiology of chronic kidney disease: an update 2022. Kidney Int Suppl (2011). 2022;12(1):7–11. doi:10.1016/j.kisu.2021.11.003
6. Karpefors M, Gasparyan SB, Huhn M (2024). maraca: The Maraca Plot: Visualization of Hierarchical Composite Endpoints in Clinical Trials. R package version ≥0.7.0. https://doi. org/10.32614/CRAN.package.maraca.
7. Gasparyan SB (2025). hce: Design and Analysis of Hierarchical Composite Endpoints. R package version ≥0.7.0. https://doi.org/10.32614/CRAN.package.hce.
Novel Data visualisations
in disease areas such as Chronic Kidney Disease (CKD).
millions worldwide.5
short, these plots visually represent complex outcomes in a way
that enhances understanding of treatment effects.
and meaningful, we are able to reveal the true impact of our data.