Description
Interactive Forest Plot.
Description
Interactive forest plot for clinical trial safety analysis using 'metalite', 'reactable', 'plotly', and Analysis Data Model (ADaM) datasets. Includes functionality for adverse event filtering, incidence-based group filtering, hover-over reveals, and search and sort operations. The workflow allows for metadata construction, data preparation, output formatting, and interactive plot generation.
README.md
forestly 
Installation
The easiest way to get forestly is to install from CRAN:
install.packages("forestly")
Alternatively, to use a new feature or get a bug fix, you can install the development version of forestly from GitHub:
# install.packages("remotes")
remotes::install_github("Merck/forestly")
Overview
The forestly package creates interactive forest plots for clinical trial analysis & reporting.
- Safety analysis
- Specific adverse events analysis
- Efficacy analysis (future work)
- Subgroup analysis
We assume ADaM datasets are ready for analysis and leverage metalite data structure to define inputs and outputs.
Workflow
The general workflow is:
meta_forestly()constructs input metadata for treatment analysis from ADaM datasets.prepare_ae_forestly()prepares datasets for interactive forest plot.format_ae_forestly()formats output layout.ae_forestly()generates an interactive forest plot.
Here is a quick example
library("forestly")
meta_forestly(
forestly_adsl,
forestly_adae
) |>
prepare_ae_forestly(parameter = "any;rel;ser") |>
format_ae_forestly() |>
ae_forestly()
Interactive features
The interactive features for safety analysis include:
- Select different AE criteria.
- Filter by incidence of AE in one or more groups.
- Reveal information by hovering the mouse over a data point.
- Search bars to find subjects with selected adverse events (AEs).
- Sort value by clicking the column header.
- Drill-down listing by clicking $\blacktriangleright$.
References
- Paper: 2023 PHUSE US Connect
- Talk: 2021 R/Pharma Conference.