---
title: TSFAE22A
subtitle: Subjects With Treatment-emergent Adverse Events by System Organ Class, Preferred Term, and Race
---
------------------------------------------------------------------------
{{< include ../../_utils/envir_hook.qmd >}}
```{r setup, echo = FALSE, warning = FALSE, message = FALSE}
options(docx.add_datetime = FALSE, tidytlg.add_datetime = FALSE)
envsetup_config_name <- "default"
# Path to the combined config file
envsetup_file_path <- file.path("../..", "envsetup.yml")
Sys.setenv(ENVSETUP_ENVIRON = '')
library(envsetup)
loaded_config <- config::get(config = envsetup_config_name, file = envsetup_file_path)
envsetup::rprofile(loaded_config)
dpscomp <- compound
dpspdr <- paste(protocol,dbrelease,rpteff,sep="__")
aptcomp <- compound
aptpdr <- paste(protocol,dbrelease,rpteff,sep="__")
###### Study specific updates (formerly in envre)
dpscomp <- "standards"
dpspdr <- "jjcs__NULL__jjcs - core"
apt <- FALSE
library(junco)
default_str_map <- rbind(default_str_map, c("&ctcae", "5.0"))
```
## Output
:::: panel-tabset
## {{< fa regular file-lines sm fw >}} Preview
```{r variant1, results='hide', warning = FALSE, message = FALSE}
# Program Name: tsfae22a.R
# Prep Environment
library(envsetup)
library(tern)
library(dplyr)
library(rtables)
library(junco)
# Define script level parameters:
# - Define output ID and file location
tblid <- "TSFAE22a"
fileid <- tblid
tab_titles <- get_titles_from_file(input_path = '../../_data/', tblid)
string_map <- default_str_map
trtvar <- "TRT01A"
popfl <- "SAFFL"
combined_colspan_trt <- TRUE
if (combined_colspan_trt == TRUE) {
# Set up levels and label for the required combined columns
add_combo <- add_combo_facet(
"Combined",
label = "Combined",
levels = c("Xanomeline High Dose", "Xanomeline Low Dose")
)
# choose if any facets need to be removed - e.g remove the combined column for placebo
rm_combo_from_placebo <- cond_rm_facets(
facets = "Combined",
ancestor_pos = NA,
value = " ",
split = "colspan_trt"
)
mysplit <- make_split_fun(post = list(add_combo, rm_combo_from_placebo))
}
# Process Data:
adsl <- pharmaverseadamjnj::adsl %>%
filter(!!rlang::sym(popfl) == "Y") %>%
select(STUDYID, USUBJID, all_of(trtvar), all_of(popfl), RACE)
adae <- pharmaverseadamjnj::adae %>%
filter(TRTEMFL == "Y") %>%
select(USUBJID, TRTEMFL, AEBODSYS, AEDECOD, RACE)
adsl$colspan_trt <- factor(
ifelse(adsl[[trtvar]] == "Placebo", " ", "Active Study Agent"),
levels = c("Active Study Agent", " ")
)
colspan_trt_map <- create_colspan_map(
adsl,
non_active_grp = "Placebo",
non_active_grp_span_lbl = " ",
active_grp_span_lbl = "Active Study Agent",
colspan_var = "colspan_trt",
trt_var = trtvar
)
# Add total for Race - adsl
totalrace1 <- adsl %>%
filter(RACE != "UNKNOWN" & !is.na(RACE)) %>%
mutate(RACE = "Total")
adsl <- bind_rows(totalrace1, adsl)
adsl <- adsl %>%
mutate(
RACEcat = case_when(
RACE == "Total" ~ "Total",
RACE == "WHITE" ~ "White",
RACE == "BLACK OR AFRICAN AMERICAN" ~ "Black",
RACE == "ASIAN" ~ "Asian",
RACE != "UNKNOWN" & !is.na(RACE) ~ "Other"
)
) %>%
filter(RACEcat %in% c("Total", "White", "Black", "Asian", "Other")) %>%
select(-RACE)
adsl$spanheader <- factor(
ifelse(adsl$RACEcat == "Total", " ", "Race"),
levels = c(" ", "Race")
)
adsl$RACEcat <- factor(
adsl$RACEcat,
levels = c("Total", "White", "Black", "Asian", "Other")
)
# Add total for Race - adae
totalrace2 <- adae %>%
filter(RACE != "UNKNOWN" & !is.na(RACE)) %>%
mutate(RACE = "Total")
adae <- bind_rows(totalrace2, adae)
adae <- adae %>%
mutate(
RACEcat = case_when(
RACE == "Total" ~ "Total",
RACE == "WHITE" ~ "White",
RACE == "BLACK OR AFRICAN AMERICAN" ~ "Black",
RACE == "ASIAN" ~ "Asian",
RACE != "UNKNOWN" & !is.na(RACE) ~ "Other"
)
) %>%
filter(RACEcat %in% c("Total", "White", "Black", "Asian", "Other")) %>%
select(-RACE)
adae$RACEcat <- factor(
adae$RACEcat,
levels = c("Total", "White", "Black", "Asian", "Other")
)
# join data together
ae <- left_join(adsl, adae, by = c("USUBJID", "RACEcat"))
# Define layout and build table:
extra_args_1 <- list(
denom = "n_altdf",
.stats = c("count_unique_fraction")
)
extra_args_2 <- list(
denom = "n_altdf",
.stats = c("count_unique")
)
lyt <- basic_table(
top_level_section_div = " ",
show_colcounts = FALSE
) %>%
split_cols_by(
"colspan_trt",
split_fun = trim_levels_to_map(map = colspan_trt_map)
)
if (combined_colspan_trt == TRUE) {
lyt <- lyt %>%
split_cols_by(trtvar, split_fun = mysplit)
} else {
lyt <- lyt %>%
split_cols_by(trtvar)
}
lyt <- lyt %>%
split_cols_by("spanheader", split_fun = trim_levels_in_group("RACEcat")) %>%
split_cols_by("RACEcat") %>%
analyze(
popfl,
afun = a_freq_j,
show_labels = "hidden",
section_div = c(" "),
extra_args = append(
extra_args_2,
list(
label = "Analysis set: Safety",
val = "Y",
section_div = c(" ")
)
)
) %>%
analyze(
"TRTEMFL",
afun = a_freq_j,
show_labels = "hidden",
extra_args = append(
extra_args_1,
list(
label = "Subjects with >=1 AE",
val = "Y",
section_div = c(" ")
)
)
) %>%
split_rows_by(
"AEBODSYS",
split_label = "System Organ Class",
split_fun = trim_levels_in_group("AEDECOD"),
label_pos = "topleft",
section_div = c(" "),
nested = FALSE
) %>%
summarize_row_groups(
"AEBODSYS",
cfun = a_freq_j,
extra_args = extra_args_1
) %>%
analyze("AEDECOD", afun = a_freq_j, extra_args = extra_args_1) %>%
append_topleft(" Preferred Term, n (%)")
result <- build_table(lyt, ae, alt_counts_df = adsl)
# Post-Processing step to sort by descending count on chosen active treatment columns.
# col_paths_summary(result)
if (length(adae$TRTEMFL) != 0) {
result <- sort_at_path(
result,
c("root", "AEBODSYS"),
scorefun = jj_complex_scorefun(
colpath = c(
"colspan_trt",
"Active Study Agent",
trtvar,
"Combined",
"spanheader",
" ",
"RACEcat",
"Total"
)
)
)
result <- sort_at_path(
result,
c("root", "AEBODSYS", "*", "AEDECOD"),
scorefun = jj_complex_scorefun(
colpath = c(
"colspan_trt",
"Active Study Agent",
trtvar,
"Combined",
"spanheader",
" ",
"RACEcat",
"Total"
)
)
)
}
# Add titles and footnotes:
result <- set_titles(result, tab_titles)
# Convert to tbl file and output table
tt_to_tlgrtf(string_map = string_map, tt =
result,
file = fileid,
orientation = "portrait",
label_width_ins = 1.5,
nosplitin = list(cols = c(trtvar))
)
```
```{r result1, echo=FALSE, message=FALSE, warning=FALSE, test = list(result_v1 = "result")}
tt_to_flextable_j(result, tblid, string_map = string_map)
```
[Download RTF file](`r paste0(tolower(tblid), '.rtf')`)
::::