
Customizing Plot Limits for AE Proportions and Differences
Source:vignettes/customize-xlimit.Rmd
customize-xlimit.Rmd
The interactive AE forest plots include AE-specific tables. In this vignette, we demonstrate how users can customize the limits when plotting AE proportions, their differences, and corresponding confidence intervals.
Step 1: build your metadata
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()
Step 2: customize limits for AE proportion/difference plotting
Users can control these limits by specifying the
prop_range = ...
and diff_range = ...
arguments within the format_ae_forestly()
function.
Specifically, prop_range
sets the limits for AE
proportions, while diff_range
defines the limits for AE
proportion differences and their confidence intervals.
By default, the limits are set based on the minimum and maximum values observed across all AEs, rounded and extended by ±2 units for better visualization.
In the example below, we modify the AE proportion limits to range from -0.5 to 30, and the AE proportion difference limits from -10 to 35. Please note that if the specified range does not fully encompass the observed minimum or maximum values, a warning message will be displayed.
meta |>
prepare_ae_forestly() |>
format_ae_forestly(prop_range = c(-0.5, 30), diff_range = c(-10, 35)) |>
ae_forestly()