FDA Table 13

Patients With Common Adverse Events Occurring at >=XX% Frequency, Safety Population, Pooled Analyses

Table Preview

Setup

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

adsl <- random.cdisc.data::cadsl
adae <- random.cdisc.data::cadae

# Pre-processing --------------------------------------------
adsl <- adsl %>%
  filter(SAFFL == "Y") # safety population

data <- adae %>%
  filter(
    # safety population
    SAFFL == "Y"
  )

Build Table

tbl <- tbl_hierarchical(
  data,
  variables = c(AEDECOD),
  by = TRT01A,
  id = USUBJID,
  denominator = adsl,
  overall_row = FALSE
) %>%
  # filter with >=5% Frequency
  filter_hierarchical(sum(n) / sum(N) >= 0.05) %>%
  modify_header(label = "Preferred Term") %>%
  remove_footnote_header(columns = everything())

tbl

Build ARD

ard <- gather_ard(tbl)
ard

$tbl_hierarchical

{cards} data frame: 99 x 13

   group1 group1_level variable variable_level   context stat_name stat_label  stat stat_fmt fmt_fun warning error gts_column
1    <NA>                TRT01A      A: Drug X categori…         n          n   134      134       0                   stat_1
2    <NA>                TRT01A      A: Drug X categori…         N          N   400      400       0                   stat_1
3    <NA>                TRT01A      A: Drug X categori…         p          % 0.335     33.5    <fn>                   stat_1
4    <NA>                TRT01A      B: Place… categori…         n          n   134      134       0                   stat_2
5    <NA>                TRT01A      B: Place… categori…         N          N   400      400       0                   stat_2
6    <NA>                TRT01A      B: Place… categori…         p          % 0.335     33.5    <fn>                   stat_2
7    <NA>                TRT01A      C: Combi… categori…         n          n   132      132       0                   stat_3
8    <NA>                TRT01A      C: Combi… categori…         N          N   400      400       0                   stat_3
9    <NA>                TRT01A      C: Combi… categori…         p          %  0.33     33.0    <fn>                   stat_3
10 TRT01A    A: Drug X  AEDECOD      dcd A.1.… hierarch…         n          n    50       50    <fn>                   stat_1

ℹ 89 more rows

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