---
title: TSIEX02
subtitle: Study Treatment Administration
---
------------------------------------------------------------------------
{{< 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: tsiex02.R
# Prep Environment
library(envsetup)
library(tern)
library(dplyr)
library(rtables)
library(junco)
# Define script level parameters:
# - Define output ID and file location
tblid <- "TSIEX02"
fileid <- tblid
tab_titles <- get_titles_from_file(input_path = '../../_data/', tblid)
string_map <- default_str_map
trtvar <- "TRT01A"
popfl <- "SAFFL"
catlevels <- c("20 mg", "30 mg", "40 mg")
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:
# Read in required data
adsl <- pharmaverseadamjnj::adsl %>%
filter(!!rlang::sym(popfl) == "Y") %>%
select(USUBJID, all_of(trtvar), all_of(popfl))
# If AVISIT is not present in ADEXSUM than create 'Overall' as the Visit, which is used
# for the filtering AVISIT records if it does exist
adexsum <- pharmaverseadamjnj::adexsum %>%
mutate(VISIT = if (exists("AVISIT")) AVISIT else "Overall") %>%
filter(
PARAMCD %in%
c("DOSEDAYS", "CUMDOSE", "MEANDDI", "MEANDD", "MODEDD", "FINDD") &
!is.na(AVAL) &
VISIT == "Overall"
) %>%
mutate(
AVAL1 = case_when(PARAMCD == "DOSEDAYS" ~ AVAL),
AVAL2 = case_when(PARAMCD == "CUMDOSE" ~ AVAL),
AVAL3 = case_when(PARAMCD == "MEANDDI" ~ AVAL),
AVAL4 = case_when(PARAMCD == "MEANDD" ~ AVAL),
AVAL5 = case_when(PARAMCD == "MODEDD" ~ AVAL),
AVALCAT5 = case_when(PARAMCD == "MODEDD" ~ AVALCAT1),
AVAL6 = case_when(PARAMCD == "FINDD" ~ AVAL),
AVALCAT6 = case_when(PARAMCD == "FINDD" ~ AVALCAT1)
) %>%
select(
STUDYID,
USUBJID,
PARAMCD,
AVAL1,
AVAL2,
AVAL3,
AVAL4,
AVAL5,
AVAL6,
AVALCAT5,
AVALCAT6
)
adsl$colspan_trt <- factor(
ifelse(adsl[[trtvar]] == "Placebo", " ", "Active Study Agent"),
levels = c("Active Study Agent", " ")
)
# join data together
ex <- adexsum %>% inner_join(., adsl, by = c("USUBJID"))
# Drop unwanted levels for AVALCAT5 and AVALCAT6 and set levels defined in top section of script
ex$AVALCAT5 <- droplevels(ex$AVALCAT5)
ex$AVALCAT5 <- factor(ex$AVALCAT5, levels = catlevels)
ex$AVALCAT6 <- droplevels(ex$AVALCAT6)
ex$AVALCAT6 <- factor(ex$AVALCAT6, levels = catlevels)
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
)
# Define layout and build table:
extra_args1 <- list(
.stats = "count_unique_fraction",
denom = "n_df"
)
lyt <- rtables::basic_table(
top_level_section_div = " ",
show_colcounts = TRUE,
colcount_format = "N=xx"
) %>%
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 %>%
analyze(
"AVAL1",
table_names = "AVAL1x",
var_labels = "Total dosing days of treatment (excluding days off treatment)~[super a]",
show_labels = "visible",
indent_mod = 0L,
afun = function(x) {
list(
"N" = rcell(length(x), format = jjcsformat_xx("xx"))
)
}
) %>%
analyze(
"AVAL1",
nested = TRUE,
var_labels = "Total dosing days of treatment (excluding days off treatment)~[super a]",
show_labels = "hidden",
indent_mod = 2L,
afun = function(x) {
list(
"Mean (SD)" = rcell(
c(mean(x), sd(x)),
format = jjcsformat_xx("xx.x (xx.xx)")
),
"Median" = rcell(median(x), format = jjcsformat_xx("xx.x")),
"Min, max" = rcell(
c(min(x), max(x)),
format = jjcsformat_xx("xx., xx.")
),
"Interquartile range" = rcell(
c(quantile(x, c(0.25, 0.75), type = 2)),
format = jjcsformat_xx("xx.x, xx.x")
)
)
}
) %>%
analyze(
"AVAL2",
table_names = "AVAL2x",
nested = FALSE,
var_labels = "Cumulative dose ([unit])",
show_labels = "visible",
indent_mod = 0L,
afun = function(x) {
list(
"N" = rcell(length(x), format = jjcsformat_xx("xx"))
)
}
) %>%
analyze(
"AVAL2",
nested = TRUE,
var_labels = "Cumulative dose ([unit])",
show_labels = "hidden",
indent_mod = 2L,
afun = function(x) {
list(
"Mean (SD)" = rcell(
c(mean(x), sd(x)),
format = jjcsformat_xx("xx.x (xx.xx)")
),
"Median" = rcell(median(x), format = jjcsformat_xx("xx.x")),
"Min, max" = rcell(
c(min(x), max(x)),
format = jjcsformat_xx("xx., xx.")
),
"Interquartile range" = rcell(
c(quantile(x, c(0.25, 0.75), type = 2)),
format = jjcsformat_xx("xx.x, xx.x")
)
)
}
) %>%
analyze(
"AVAL3",
table_names = "AVAL3x",
nested = FALSE,
var_labels = "Average daily dose ([unit/day]) (including days off treatment)",
show_labels = "visible",
indent_mod = 0L,
afun = function(x) {
list(
"N" = rcell(length(x), format = jjcsformat_xx("xx"))
)
}
) %>%
analyze(
"AVAL3",
nested = TRUE,
var_labels = "Average daily dose ([unit/day]) (including days off treatment)",
show_labels = "hidden",
indent_mod = 2L,
afun = function(x) {
list(
"Mean (SD)" = rcell(
c(mean(x), sd(x)),
format = jjcsformat_xx("xx.xx (xx.xxx)")
),
"Median" = rcell(median(x), format = jjcsformat_xx("xx.xx")),
"Min, max" = rcell(
c(min(x), max(x)),
format = jjcsformat_xx("xx.x, xx.x")
),
"Interquartile range" = rcell(
c(quantile(x, c(0.25, 0.75), type = 2)),
format = jjcsformat_xx("xx.xx, xx.xx")
)
)
}
) %>%
analyze(
"AVAL4",
table_names = "AVAL4x",
nested = FALSE,
var_labels = "Average daily dose ([unit/day]) (excluding days off treatment)",
show_labels = "visible",
indent_mod = 0L,
afun = function(x) {
list(
"N" = rcell(length(x), format = jjcsformat_xx("xx"))
)
}
) %>%
analyze(
"AVAL4",
nested = TRUE,
var_labels = "Average daily dose ([unit/day]) (excluding days off treatment)",
show_labels = "hidden",
indent_mod = 2L,
afun = function(x) {
list(
"Mean (SD)" = rcell(
c(mean(x), sd(x)),
format = jjcsformat_xx("xx.xx (xx.xxx)")
),
"Median" = rcell(median(x), format = jjcsformat_xx("xx.xx")),
"Min, max" = rcell(
c(min(x), max(x)),
format = jjcsformat_xx("xx.x, xx.x")
),
"Interquartile range" = rcell(
c(quantile(x, c(0.25, 0.75), type = 2)),
format = jjcsformat_xx("xx.xx, xx.xx")
)
)
}
) %>%
analyze(
"AVAL5",
nested = FALSE,
var_labels = "Modal daily dose ([unit/day]), n (%)",
show_labels = "visible",
indent_mod = 0L,
afun = function(x) {
list(
"N" = rcell(length(x), format = jjcsformat_xx("xx"))
)
}
) %>%
analyze(
"AVALCAT5",
afun = a_freq_j,
extra_args = extra_args1,
show_labels = "hidden",
indent_mod = 2L
) %>%
analyze(
"AVAL6",
table_names = "AVAL6x",
nested = FALSE,
var_labels = "Final daily dose ([unit/day])",
show_labels = "visible",
indent_mod = 0L,
afun = function(x) {
list(
"N" = rcell(length(x), format = jjcsformat_xx("xx"))
)
}
) %>%
analyze(
"AVAL6",
nested = TRUE,
var_labels = "Final daily dose ([unit/day])",
show_labels = "hidden",
indent_mod = 2L,
afun = function(x) {
list(
"Mean (SD)" = rcell(
c(mean(x), sd(x)),
format = jjcsformat_xx("xx.x (xx.xx)")
),
"Median" = rcell(median(x), format = jjcsformat_xx("xx.x")),
"Min, max" = rcell(
c(min(x), max(x)),
format = jjcsformat_xx("xx., xx.")
),
"Interquartile range" = rcell(
c(quantile(x, c(0.25, 0.75), type = 2)),
format = jjcsformat_xx("xx.x, xx.x")
)
)
}
) %>%
analyze(
"AVALCAT6",
afun = a_freq_j,
nested = FALSE,
show_labels = "visible",
var_labels = "Final daily dose ([unit/day]), n (%)",
extra_args = extra_args1,
indent_mod = 1L
) %>%
append_topleft("Parameter")
result <- build_table(lyt, ex, alt_counts_df = adsl)
# 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")
```
```{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')`)
::::