Demographics and Baseline Clinical Characteristics, Safety Population, Pooled Analysis (or Trial X)

FDA Table 02

Table Preview

Setup

# Load libraries & data -------------------------------------
library(dplyr)
library(gtsummary)

adsl <- pharmaverseadam::adsl |>
  # removing screen failure observations
  filter(TRT01A != "Screen Failure") |>
  # Adding a numeric biomarker (weight)
  left_join(
    pharmaverseadam::advs |>
      filter(VSTESTCD == "WEIGHT", VISIT == "BASELINE") |>
      select(USUBJID, WEIGHTBL = AVAL),
    by = "USUBJID",
    relationship = "one-to-one"
  )


# Pre-processing --------------------------------------------
# Filter for the safety population, x
data <- adsl |>
  filter(SAFFL == "Y")

Build Table

tbl <- data |>
  tbl_summary(
    by = "TRT01A",
    include = c("SEX", "AGE", "AGEGR1", "ETHNIC", "RACE"),
    type = all_continuous() ~ "continuous2", # arranges statistics into multiple lines
    statistic = list(
      all_continuous() ~ c(
        "{mean} ({sd})",
        "{median} ({min}, {max})"
      ),
      all_categorical() ~ "{n} ({p}%)"
    ),
    label = list(AGEGR1 = "Age Group, Years")
  ) |>
  add_overall(last = TRUE, col_label = "**Total Population**  \nN = {N}") |>
  # remove default footnote
  remove_footnote_header(columns = everything())

tbl

Build ARD

ard <- gather_ard(tbl)
ard

$tbl_summary

{cards} data frame: 193 x 12

   group1 group1_level variable variable_level  context stat_name stat_label  stat fmt_fun warning error gts_column
1  TRT01A      Placebo      SEX              F tabulate         n          n    53    <fn>                   stat_1
2  TRT01A      Placebo      SEX              F tabulate         N          N    86    <fn>                   stat_1
3  TRT01A      Placebo      SEX              F tabulate         p          % 0.616    <fn>                   stat_1
4  TRT01A      Placebo      SEX              M tabulate         n          n    33    <fn>                   stat_1
5  TRT01A      Placebo      SEX              M tabulate         N          N    86    <fn>                   stat_1
6  TRT01A      Placebo      SEX              M tabulate         p          % 0.384    <fn>                   stat_1
7  TRT01A      Placebo     RACE      AMERICAN… tabulate         n          n     0    <fn>                   stat_1
8  TRT01A      Placebo     RACE      AMERICAN… tabulate         N          N    86    <fn>                   stat_1
9  TRT01A      Placebo     RACE      AMERICAN… tabulate         p          %     0    <fn>                   stat_1
10 TRT01A      Placebo     RACE      BLACK OR… tabulate         n          n     8    <fn>                   stat_1

ℹ 183 more rows

ℹ Use `print(n = ...)` to see more rows

$add_overall

{cards} data frame: 68 x 10

   variable variable_level  context stat_name stat_label  stat fmt_fun warning error gts_column
1       SEX              F tabulate         n          n   143    <fn>                   stat_0
2       SEX              F tabulate         N          N   254    <fn>                   stat_0
3       SEX              F tabulate         p          % 0.563    <fn>                   stat_0
4       SEX              M tabulate         n          n   111    <fn>                   stat_0
5       SEX              M tabulate         N          N   254    <fn>                   stat_0
6       SEX              M tabulate         p          % 0.437    <fn>                   stat_0
7      RACE      AMERICAN… tabulate         n          n     1    <fn>                   stat_0
8      RACE      AMERICAN… tabulate         N          N   254    <fn>                   stat_0
9      RACE      AMERICAN… tabulate         p          % 0.004    <fn>                   stat_0
10     RACE      BLACK OR… tabulate         n          n    23    <fn>                   stat_0

ℹ 58 more rows
ℹ Use `print(n = ...)` to see more rows