The easiest way to get metalite.ae is to install from CRAN:
install.packages("metalite.ae")Alternatively, to use a new feature or get a bug fix, you can install the development version of metalite.ae from GitHub:
# install.packages("remotes")
remotes::install_github("Merck/metalite.ae")metalite.ae is an R package designed for the analysis of adverse events (AE) in clinical trials. It operates on ADaM datasets and adheres to the metalite structure. The R package streamlines the process of generating production-ready tables, listings, and figures as outlined in the AE summary chapter and the specific AE chapter of the R for Clinical Study Reports and Submission book. The package encompasses the following components:
- Avoid duplicated input by using metadata structure.
- For example, define analysis population once to use in all adverse events analysis.
- Consistent input and output in standard functions.
- Streamlines mock table generation.
# Define metadata
adsl <- forestly::forestly_adsl
adae <- forestly::forestly_adae
adsl$TRT01A <- factor(
adsl$TRT01A,
levels = c("Xanomeline Low Dose", "Placebo"),
labels = c("Low Dose", "Placebo")
)
adae$TRTA <- factor(
adae$TRTA,
levels = c("Xanomeline Low Dose", "Placebo"),
labels = c("Low Dose", "Placebo")
)
analysis_plan <- metalite::plan(
analysis = "ae_summary",
population = "apat",
observation = "wk12",
parameter = "any;rel;ser"
)
meta <- metalite::meta_adam(observation = adae, population = adsl) |>
metalite::define_plan(analysis_plan) |>
metalite::define_population(
name = "apat",
var = c(
"USUBJID", "SAFFL", "TRT01A", "TRTDUR",
"SITEID", "SEX", "RACE", "AGE"
),
group = "TRT01A",
subset = SAFFL == "Y",
label = "All Participants as Treated"
) |>
metalite::define_observation(
name = "wk12",
var = c(
"USUBJID", "SAFFL", "TRTA", "AEDECOD", "AEBODSYS", "AEREL",
"AESER", "AEOUT", "AEACN", "AESDTH", "ASTDT", "AENDT"
),
group = "TRTA",
subset = SAFFL == "Y",
label = "Weeks 0 to 12"
) |>
metalite::define_parameter(
name = "any",
term1 = "",
term2 = "",
var = "AEDECOD",
soc = "AEBODSYS",
label = "All AEs"
) |>
metalite::define_parameter(
name = "rel",
term1 = "Drug-Related",
term2 = "",
subset = AEREL %in% c("POSSIBLE", "PROBABLE"),
var = "AEDECOD",
soc = "AEBODSYS",
label = "Drug-related AEs"
) |>
metalite::define_parameter(
name = "ser",
term1 = "Serious",
term2 = "",
subset = AESER == "Y",
var = "AEDECOD",
soc = "AEBODSYS",
label = "Serious AEs"
) |>
metalite::define_analysis(
name = "ae_summary",
title = "Adverse Event Summary"
) |>
metalite::meta_build()
meta |> # Example AE data created using metalite
prepare_ae_summary(
population = "apat", # Select population by keywords
observation = "wk12", # Select observation by keywords
parameter = "any;rel;ser" # Select AE terms by keywords
) |>
format_ae_summary() |>
tlf_ae_summary(
source = "Source: [CDISCpilot: adam-adsl; adae]", # Define data source
path_outtable = "ae0summary.rtf" # Define output
)