tbl_summary ( gtsummary) transpose with p-values - gtsummary

Question

I was wondering if there is a way to compose such a table :
library(gtsummary)
data(trial)
add_p_ex1 <-
trial[c("marker", "trt")] %>%
tbl_summary(by = trt) %>%
add_p()
add_p_ex2 <-
trial[c("marker", "death")] %>%
tbl_summary(by = death) %>%
add_p()
as1=add_p_ex1$table_body
as2=add_p_ex2$table_body
write.csv(rbind(as1, as2), file='temp1.csv')
With an output that is transposed version of as1 and as2 like this :
Ideally for K - continuous variable ( eg marker 1 , marker 2, ... maker k) and a P number of categorical variables.
Marker Level (ng/mL) Pvalue
trt
drug A 0.84 (0.24, 1.57) 0.084746992242773
drug B 0.52 (0.19, 1.20)
Death
0 0.73 (0.23, 1.33) 0.605276987642371
1 0.57 (0.20, 1.45)

Answer 1

It's possible to get your table like this, and I've provided a code example below. I am not sure if it's the easiest way to get what you're looking for, however.
library(gtsummary)
library(tidyverse)
# function to transpose a tbl_summary table
gtsummary_transpose <- function(data, con_var, cat_var) {
tbl <- data[c(con_var, cat_var)] %>%
tbl_summary(by = cat_var, missing = "no") %>%
add_p() %>%
modify_header(stat_by = "{level}",
p.value = "p.value",
label = "label") %>%
as_tibble() %>%
select(-label) %>%
pivot_longer(cols = -p.value) %>%
select(name, value, p.value)
# add a header row
bind_rows(
tibble(name = attr(data[[cat_var]], "label") %||% cat_var),
tbl
) %>%
fill(p.value, .direction = "up") %>%
mutate(p.value = ifelse(row_number() == 1, p.value, NA))
}
gtsummary_transpose(trial, "marker", "trt")
# transose multiple tables, and stack them
tibble(variable = c("trt", "grade")) %>%
mutate(
tbl = map(variable, ~gtsummary_transpose(trial, "marker", .x))
) %>%
unnest(cols = tbl) %>%
gt::gt() %>%
gt::cols_hide(vars(variable)) %>%
gt::cols_label(name = "Characteristic", value = "Marker Level", p.value = "p-value") %>%
gt::fmt_missing(columns = everything(), missing_text = "")