---
title: TSFAE07B
subtitle: Subjects With Treatment-emergent Adverse Events of Special Interest - AESI Grouping
---
------------------------------------------------------------------------
{{< 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: tsfae07b.R
# Prep Environment
library(envsetup)
library(tern)
library(dplyr)
library(rtables)
library(junco)
# Define script level parameters:
# - Define output ID and file location
tblid <- "TSFAE07b"
fileid <- tblid
tab_titles <- get_titles_from_file(input_path = '../../_data/', tblid)
string_map <- default_str_map
trtvar <- "TRT01A"
popfl <- "SAFFL"
special_interest_var <- "CQ01NAM"
aerelvar <- "AEREL"
aeactionvar <- "AEACN"
combined_colspan_trt <- TRUE
risk_diff <- TRUE
rr_method <- "wald"
ctrl_grp <- "Placebo"
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))
}
# Optional lab section parameters
labsection <- TRUE
lab_params <- c("AST", "ALT")
lab_labels <- c("AST>5xULN", "ALT>5xULN")
lab_var <- c("MCRIT1MN", "MCRIT1MN")
lab_vals <- c("2,3", "2,3") # Note both character or numeric values can be enclosed within in one set of double quotations here
# Process Data:
adsl <- pharmaverseadamjnj::adsl %>%
filter(!!rlang::sym(popfl) == "Y") %>%
select(STUDYID, USUBJID, all_of(trtvar), all_of(popfl))
lbdata <- NULL
# Optional lab section
if (labsection == TRUE) {
for (i in 1:length(lab_params)) {
filter_val <- unlist(strsplit(lab_vals[[i]], ","))
adlb <- pharmaverseadamjnj::adlb %>%
filter(
TRTEMFL == "Y" &
PARAMCD == lab_params[[i]] &
!!rlang::sym(lab_var[[i]]) %in% filter_val
) %>%
mutate(criteria = lab_labels[[i]]) %>%
select(USUBJID, TRTEMFL, PARAMCD, all_of(lab_var[[i]]), criteria)
lbdata <- bind_rows(adlb, lbdata)
}
adlb <- lbdata %>%
group_by(USUBJID, TRTEMFL, PARAMCD, criteria) %>%
slice(1) %>%
ungroup()
# Create flag variable for each parameter that met the condition to merge back onto adsl
# Overall row
adlbparamall <- adlb %>%
filter(PARAMCD %in% lab_params) %>%
mutate(lab_flag = "Y") %>%
group_by(USUBJID) %>%
slice(1) %>%
ungroup() %>%
select(USUBJID, lab_flag)
adsl <- left_join(adsl, adlbparamall, by = c("USUBJID"))
# Loop through each parameter that the user has specified and merge flag variable onto adsl
for (i in 1:length(lab_params)) {
flagvar <- paste0("lab_flag", i)
adlbparam <- adlb %>%
filter(PARAMCD == lab_params[[i]] & criteria == lab_labels[[i]]) %>%
mutate(!!flagvar := lab_labels[[i]]) %>%
group_by(USUBJID) %>%
slice(1) %>%
ungroup() %>%
select(USUBJID, all_of(flagvar))
adsl <- left_join(adsl, adlbparam, by = c("USUBJID"))
}
}
adae <- pharmaverseadamjnj::adae %>%
filter(TRTEMFL == "Y" & !is.na(!!rlang::sym(special_interest_var))) %>%
select(
USUBJID,
TRTEMFL,
AEBODSYS,
AEDECOD,
AETOXGR,
all_of(special_interest_var),
AESER,
AEOUT,
all_of(aeactionvar),
all_of(aerelvar)
)
adsl$colspan_trt <- factor(
ifelse(adsl[[trtvar]] == "Placebo", " ", "Active Study Agent"),
levels = c("Active Study Agent", " ")
)
if (risk_diff == TRUE) {
adsl$rrisk_header <- "Risk Difference (%) (95% CI)"
adsl$rrisk_label <- paste(adsl[[trtvar]], paste("vs", ctrl_grp))
}
# join data together
ae <- adae %>% right_join(., adsl, by = c("USUBJID"))
# Keep only maximum toxicity for the particular AESI
ae <- ae %>%
mutate(
ATOXGR = factor(
ifelse(
is.na(AETOXGR),
"Missing",
as.character(paste0("Grade ", AETOXGR))
),
levels = c(
"Grade 5",
"Grade 4",
"Grade 3",
"Grade 2",
"Grade 1",
"Missing"
)
),
rowhead = "Maximum toxicity"
) %>%
arrange(USUBJID, special_interest_var, ATOXGR) %>%
group_by(USUBJID, .data[[special_interest_var]]) %>%
slice(1) %>%
ungroup()
# Remove Missing as a level since not required in table
levels(ae$ATOXGR)[levels(ae$ATOXGR) == "Missing"] <- NA
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
)
# Define layout and build table:
ref_path <- c("colspan_trt", " ", "TRT01A", "Placebo")
extra_args_rr <- list(
method = rr_method,
ref_path = ref_path,
.stats = c("count_unique_fraction")
)
lyt <- 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)
}
if (risk_diff == TRUE) {
lyt <- lyt %>%
split_cols_by("rrisk_header", nested = FALSE) %>%
split_cols_by(
trtvar,
labels_var = "rrisk_label",
split_fun = remove_split_levels("Placebo")
)
}
lyt <- lyt %>%
split_rows_by(
special_interest_var,
split_label = "",
split_fun = trim_levels_in_group("AEDECOD"),
label_pos = "topleft",
indent_mod = 0,
section_div = c(" ")
) %>%
summarize_row_groups(
special_interest_var,
cfun = a_freq_j,
extra_args = append(extra_args_rr, NULL)
) %>%
analyze(
"AEDECOD",
var_labels = "Preferred Term",
afun = a_freq_j,
indent_mod = 0,
show_labels = "visible",
extra_args = append(extra_args_rr, NULL)
) %>%
split_rows_by(
"rowhead",
split_label = "",
# ,split_fun = trim_levels_in_group("ATOXGR")
label_pos = "topleft",
indent_mod = 0,
section_div = c(" ")
) %>%
analyze(
"ATOXGR",
afun = a_freq_j,
indent_mod = 0,
extra_args = append(extra_args_rr, NULL)
) %>%
split_rows_by(
"AESER",
split_fun = keep_split_levels("Y"),
section_div = " "
) %>%
summarize_row_groups(
"AESER",
cfun = a_freq_j,
extra_args = append(extra_args_rr, list(label = "Serious", NULL))
) %>%
analyze(
"AEOUT",
afun = a_freq_j,
show_labels = "hidden",
extra_args = append(
extra_args_rr,
list(label = "Deaths", val = "FATAL", NULL)
)
) %>%
analyze(
aeactionvar,
afun = a_freq_j,
show_labels = "hidden",
nested = FALSE,
extra_args = append(
extra_args_rr,
list(
label = "Resulting in treatment discontinuation",
val = "DRUG WITHDRAWN",
NULL
)
)
) %>%
analyze(
aerelvar,
afun = a_freq_j,
show_labels = "hidden",
nested = FALSE,
extra_args = append(
extra_args_rr,
list(label = "Related~[super a]", val = "RELATED", NULL)
)
)
if (labsection == TRUE) {
lyt <- lyt %>%
analyze(
"lab_flag",
afun = a_freq_j,
show_labels = "hidden",
nested = FALSE,
extra_args = append(
extra_args_rr,
list(label = "Laboratory assessment~[super b]", NULL)
)
)
for (i in 1:length(lab_params)) {
aflagvar <- paste0("lab_flag", i)
lyt <- lyt %>%
analyze(
aflagvar,
afun = a_freq_j,
indent_mod = 1,
show_labels = "hidden",
nested = TRUE,
extra_args = append(extra_args_rr, NULL)
)
}
}
lyt <- lyt %>%
append_topleft("AESI Assessment, n (%)")
result <- build_table(lyt, ae, alt_counts_df = adsl)
## Remove the N=xx column headers for the risk difference columns
result <- remove_col_count(result)
## Remove any rogue null rows
result <- result %>%
safe_prune_table(prune_func = keep_rows(keep_non_null_rows))
# 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 = "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')`)
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