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library(forestly)
library(metalite)
The interactive AE forest plots include AE-specific tables presenting numerical values for AE proportions, differences, and confidence intervals (CI), alongside their visualizations. Directly below the column visualizing the AE proportion difference, a legend is displayed. By default, this legend reads: “Treatment <- Favor -> Placebo”. In this vignette, we demonstrate how to customize this legend.
Building interactive AE forest plots starts with constructing the metadata. The detailed procedure for building metadata is covered in the vignette Generate Interactive AE Forest Plots with Drill Down to AE Listing. Therefore, in this vignette, we will skip those details and directly use the metadata created there.
adsl <- forestly_adsl
adae <- forestly_adae
adsl$TRTA <- factor(forestly_adsl$TRT01A,
levels = c("Xanomeline Low Dose", "Placebo"),
labels = c("Low Dose", "Placebo")
)
adae$TRTA <- factor(forestly_adae$TRTA,
levels = c("Xanomeline Low Dose", "Placebo"),
labels = c("Low Dose", "Placebo")
)
meta <- meta_adam(population = adsl, observation = adae) |>
define_plan(plan = plan(
analysis = "ae_forestly",
population = "apat",
observation = "apat",
parameter = "any;drug-related"
)) |>
define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") |>
define_population(
name = "apat", group = "TRTA", id = "USUBJID",
subset = SAFFL == "Y", label = "All Patient as Treated"
) |>
define_observation(
name = "apat", group = "TRTA",
subset = SAFFL == "Y", label = "All Patient as Treated"
) |>
define_parameter(
name = "any",
subset = NULL,
label = "Any AEs",
var = "AEDECOD", soc = "AEBODSYS"
) |>
define_parameter(
name = "drug-related",
subset = toupper(AREL) == "RELATED",
label = "Drug-related AEs",
var = "AEDECOD", soc = "AEBODSYS"
) |>
meta_build()
Users can modify the legend for the AE proportion difference by
specifying the diff_label = ...
argument within the
format_ae_forestly()
function. The default setting is
diff_label = "Treatment <- Favor -> Placebo"
.
In the example below, we show how to change the legend text. We encourage users to tailor this label to best reflect the context of their specific study.
meta |>
prepare_ae_forestly() |>
format_ae_forestly(diff_label = "New Drug <- Favor -> SoC", ) |>
ae_forestly()
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.
Health stats visible at Monitor.