
Build an Interactive Baseline Characteristic Table
interactive-baseline.Rmd
There are 2 key metadata types:
- metadata for the baseline characteristic table
- metadata for the AE subgroup specific table
Build metadata
Metadata for baseline characteristic table
The code below is the same as meta_sl_example()
.
adsl <- r2rtf::r2rtf_adsl
adsl$TRTA <- adsl$TRT01A
adsl$TRTA <- factor(adsl$TRTA,
levels = c("Placebo", "Xanomeline Low Dose", "Xanomeline High Dose"),
labels = c("Placebo", "Low Dose", "High Dose")
)
meta_sl <- meta_adam(
population = adsl,
observation = adsl
) |>
define_plan(plan = plan(
analysis = "base_char", population = "apat",
observation = "apat", parameter = "age;gender;race"
)) |>
define_population(
name = "apat",
group = "TRTA",
subset = quote(SAFFL == "Y"),
var = c("USUBJID", "TRTA", "SAFFL", "AGEGR1", "SEX", "RACE")
) |>
define_observation(
name = "apat",
group = "TRTA",
subset = quote(SAFFL == "Y"),
var = c("USUBJID", "TRTA", "SAFFL", "AGEGR1", "SEX", "RACE")
) |>
define_parameter(
name = "age",
var = "AGE",
label = "Age (years)",
vargroup = "AGEGR1"
) |>
define_parameter(
name = "gender",
var = "SEX",
label = "Gender"
) |>
define_parameter(
name = "race",
var = "RACE",
label = "Race"
) |>
define_analysis(
name = "base_char",
title = "Participant Baseline Characteristics by Treatment Group",
label = "baseline characteristic table"
) |>
meta_build()
A metadata of the AE subgroup specific analysis
In this vignette, we will directly use the metadata built by
meta_ae_example()
.
meta_ae <- meta_ae_example()
Customization (Optional)
If you want to capitalize only the first letter of “RACE” (e.g.,
Black or african american) or any other character variable, you can
customize the react_base_char
function at the beginning of
the code.
# function to capitalize the first letter of a string that has multiple words
capitalize_words <- function(x) {
sapply(x, function(word) {
paste0(toupper(substr(word, 1, 1)), tolower(substr(word, 2, nchar(word))))
})
}
# 1) In "data_population": extract the RACE values as a character vector
race_values_pop <- meta_sl[["data_population"]]$RACE # Use $ to get a vector
# Capitalize the race values
meta_sl[["data_population"]]$RACE <- capitalize_words(race_values_pop) # Assign back as a vector
# 2) In "data_observation": extract the RACE values as a character vector
race_values_obs <- meta_sl[["data_observation"]]$RACE # Use $ to get a vector
# Capitalize the race values
meta_sl[["data_observation"]]$RACE <- capitalize_words(race_values_obs) # Assign back as a vector
Build a reactable
Baseline characteristic table + Participants With Drug-Related AE
react_base_char(
metadata_sl = meta_sl,
metadata_ae = meta_ae,
ae_subgroup = c("age", "race", "gender"),
ae_specific = "rel",
width = 1200
)
Baseline characteristic table + Participants With Serious AE
react_base_char(
metadata_sl = meta_sl,
metadata_ae = meta_ae,
ae_subgroup = c("age", "race", "gender"),
ae_specific = "ser",
width = 1200
)