---
title: TSFAE20B
subtitle: Demographic Characteristics for Subjects With Serious Treatment-emergent Adverse Events
---
------------------------------------------------------------------------
{{< 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
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## {{< fa regular file-lines sm fw >}} Preview
```{r variant1, results='hide', warning = FALSE, message = FALSE}
# Program Name: tsfae20b.R
# Prep Environment
library(envsetup)
library(tern)
library(forcats)
library(dplyr)
library(rtables)
library(junco)
# Define script level parameters:
tblid <- "TSFAE20b"
titles <- get_titles_from_file(input_path = '../../_data/', tblid)
string_map <- default_str_map
fileid <- tblid
popfl <- "SAFFL"
trtvar <- "TRT01A"
subjFilterText <- "SAE"
ctrl_grp <- "Placebo"
# Process Data
adsl <- pharmaverseadamjnj::adsl %>%
filter(!!rlang::sym(popfl) == "Y") %>%
create_colspan_var(
non_active_grp = ctrl_grp,
non_active_grp_span_lbl = " ",
active_grp_span_lbl = "Active Study Agent",
colspan_var = "colspan_trt",
trt_var = trtvar
) %>%
select(
USUBJID,
!!rlang::sym(popfl),
!!rlang::sym(trtvar),
SEX_DECODE,
AGEGR1,
RACE_DECODE,
ETHNIC_DECODE,
colspan_trt
)
# Factor reformatting (e.g., Include missing in the "Unknown" category).
adsl$SEX_DECODE <- forcats::fct_na_value_to_level(
adsl$SEX_DECODE,
level = "Unknown"
)
adsl$AGEGR1_DECODE <- forcats::fct_na_value_to_level(
factor(stringr::str_replace(as.character(adsl$AGEGR1), ">=", "\u2265")),
level = "Unknown"
)
adsl$RACE_DECODE <- forcats::fct_collapse(
forcats::fct_na_value_to_level(adsl$RACE_DECODE, level = "Unknown"),
"Not reported or unknown" = c("Not reported", "Unknown")
)
adsl$ETHNIC_DECODE <- forcats::fct_collapse(
forcats::fct_na_value_to_level(adsl$ETHNIC_DECODE, level = "Unknown"),
"Not reported or unknown" = c("Not reported", "Unknown")
)
had_ae <- pharmaverseadamjnj::adae %>%
filter(TRTEMFL == "Y" & AESER == "Y") %>%
select(USUBJID, TRTEMFL) %>%
distinct(USUBJID, .keep_all = TRUE)
adsl <- adsl %>%
left_join(had_ae) %>%
mutate(TRTEMFL = ifelse(is.na(TRTEMFL), "N", "Y"))
# Define layout and build table
colspan_trt_map <- create_colspan_map(
adsl,
non_active_grp = ctrl_grp,
non_active_grp_span_lbl = " ",
active_grp_span_lbl = "Active Study Agent",
colspan_var = "colspan_trt",
trt_var = trtvar
)
ref_path <- c("colspan_trt", " ", trtvar, ctrl_grp)
add_active_combo <- make_split_fun(
post = list(
add_combo_facet(
name = "Combined",
label = "Combined",
levels = c("Xanomeline High Dose", "Xanomeline Low Dose")
),
cond_rm_facets(
facets = "Combined",
ancestor_pos = NA,
value = " ",
split = "colspan_trt"
)
)
)
extra_args_rr <- list(
riskdiff = FALSE
)
extra_args_rr2 <- append(
extra_args_rr,
list(resp_var = "TRTEMFL", drop_levels = TRUE)
)
lyt <- basic_table(
show_colcounts = TRUE,
colcount_format = "N=xx",
top_level_section_div = " "
) %>%
append_topleft("Characteristic") %>%
split_cols_by(
"colspan_trt",
split_fun = trim_levels_to_map(map = colspan_trt_map)
) %>%
split_cols_by(trtvar, split_fun = add_active_combo)
lyt <- lyt %>%
analyze(
"TRTEMFL",
afun = a_freq_j,
extra_args = append(
extra_args_rr,
list(
label = paste("Subjects with >= 1", subjFilterText),
val = "Y",
.stats = c("count_unique_fraction")
)
),
show_labels = "hidden"
) %>%
analyze(
vars = "SEX_DECODE",
var_labels = "Sex, n/Ns (%)",
show_labels = "visible",
afun = a_freq_resp_var_j,
extra_args = extra_args_rr2,
nested = FALSE
) %>%
analyze(
vars = "AGEGR1_DECODE",
var_labels = "Age group (years), n/Ns (%)",
show_labels = "visible",
afun = a_freq_resp_var_j,
extra_args = extra_args_rr2,
nested = FALSE
) %>%
analyze(
vars = "RACE_DECODE",
var_labels = "Race, n/Ns (%)",
show_labels = "visible",
afun = a_freq_resp_var_j,
extra_args = extra_args_rr2,
nested = FALSE
) %>%
analyze(
vars = "ETHNIC_DECODE",
var_labels = "Ethnicity, n/Ns (%)",
show_labels = "visible",
afun = a_freq_resp_var_j,
extra_args = extra_args_rr2,
nested = FALSE
)
result <- build_table(lyt, adsl)
# Post-Processing:
result <- safe_prune_table(result, prune_func = count_pruner())
# Add titles and footnotes:
result <- set_titles(result, titles)
# Convert to tbl file and output table
tt_to_tlgrtf(string_map = string_map, tt = result, file = fileid, orientation = "landscape")
```
```{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')`)
::::