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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:

1. meta_forestly() constructs input metadata for treatment analysis from ADaM datasets.
2. prepare_ae_forestly() prepares datasets for interactive forest plot.
3. format_ae_forestly() formats output layout.
4. ae_forestly() generates an interactive forest plot.

Here is a quick example

library("forestly")

meta_forestly(
  dataset_adsl = forestly_adsl,
  dataset_adae = forestly_adae,
  parameter_term = "any;rel;ser",
  population_subset = SAFFL == "Y",
  observation_subset = SAFFL == "Y"
) |>
  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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.