TSFAE24A

Overall Summary of Treatment-emergent Adverse Events by Severity

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# Program Name:              tsfae24a.R

# Prep environment:

library(envsetup)
library(tern)
library(dplyr)
library(rtables)
library(junco)

# Define script level parameters:

tblid <- "TSFAE24a"
fileid <- tblid
popfl <- "SAFFL"
trtvar <- "TRT01A"
tab_titles <- get_titles_from_file(input_path = '../../_data/', tblid)
string_map <- default_str_map

# Process data:

adsl <- pharmaverseadamjnj::adsl %>%
  filter(!!rlang::sym(popfl) == "Y") %>%
  create_colspan_var(
    non_active_grp = "Placebo",
    non_active_grp_span_lbl = " ",
    active_grp_span_lbl = "Active Study Agent",
    colspan_var = "colspan_trt",
    trt_var = trtvar
  ) %>%
  select(USUBJID, !!rlang::sym(trtvar), colspan_trt)

adae <- pharmaverseadamjnj::adae %>%
  filter(TRTEMFL == "Y") %>%
  mutate(
    ASEV = factor(
      ifelse(is.na(AESEV), "Missing", as.character(AESEV)),
      levels = c("Severe", "Moderate", "Mild", "Missing")
    )
  ) %>%
  select(USUBJID, TRTEMFL, ASEV)

ae <- inner_join(adae, adsl, by = c("USUBJID"))

# Keep maximum severity per subject.
ae <- ae %>%
  arrange(USUBJID, ASEV) %>%
  group_by(USUBJID) %>%
  slice(1) %>%
  ungroup()

# Define layout and build table:

extra_args_1 <- list(.stats = c("count_unique_fraction"))

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
)


lyt <- basic_table(
  show_colcounts = TRUE,
  colcount_format = "N=xx",
  top_level_section_div = " "
) %>%
  append_topleft("n (%)") %>%
  split_cols_by(
    "colspan_trt",
    split_fun = trim_levels_to_map(map = colspan_trt_map)
  ) %>%
  split_cols_by(trtvar) %>%
  analyze_num_patients(
    vars = "USUBJID",
    .stats = "unique",
    .formats = c("unique" = jjcsformat_count_fraction),
    .labels = "Subjects with >= 1 AE"
  ) %>%
  analyze(
    "ASEV",
    afun = a_freq_j,
    extra_args = extra_args_1,
    var_labels = "Severity",
    nested = FALSE,
    show_labels = "visible",
  )

result <- build_table(lyt, ae, alt_counts_df = adsl)

# Prune missing category if all zeros:

result <- safe_prune_table(
  result,
  prune_func = count_pruner(cat_include = "Missing")
)

# 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)

TSFAE24a: Overall Summary of [Treatment-emergent Adverse Events] by Severity; Safety Analysis Set (Study jjcs - core)
	Active Study Agent
	Xanomeline High Dose	Xanomeline Low Dose	Placebo
n (%)	N=53	N=73	N=59
Subjects with ≥ 1 AE	51 (96.2%)	62 (84.9%)	42 (71.2%)

Severity
Severe	3 (5.7%)	12 (16.4%)	3 (5.1%)
Moderate	31 (58.5%)	35 (47.9%)	16 (27.1%)
Mild	17 (32.1%)	15 (20.5%)	23 (39.0%)

Note: The worst severity event experienced by the subject is used. If a subject has all adverse events with missing severities, the subject is only counted as missing.

Download RTF file

--- title: TSFAE24A subtitle: Overall Summary of Treatment-emergent Adverse Events by Severity --- ------------------------------------------------------------------------ {{< 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: tsfae24a.R # Prep environment: library(envsetup) library(tern) library(dplyr) library(rtables) library(junco) # Define script level parameters: tblid <- "TSFAE24a" fileid <- tblid popfl <- "SAFFL" trtvar <- "TRT01A" tab_titles <- get_titles_from_file(input_path = '../../_data/', tblid) string_map <- default_str_map # Process data: adsl <- pharmaverseadamjnj::adsl %>% filter(!!rlang::sym(popfl) == "Y") %>% create_colspan_var( non_active_grp = "Placebo", non_active_grp_span_lbl = " ", active_grp_span_lbl = "Active Study Agent", colspan_var = "colspan_trt", trt_var = trtvar ) %>% select(USUBJID, !!rlang::sym(trtvar), colspan_trt) adae <- pharmaverseadamjnj::adae %>% filter(TRTEMFL == "Y") %>% mutate( ASEV = factor( ifelse(is.na(AESEV), "Missing", as.character(AESEV)), levels = c("Severe", "Moderate", "Mild", "Missing") ) ) %>% select(USUBJID, TRTEMFL, ASEV) ae <- inner_join(adae, adsl, by = c("USUBJID")) # Keep maximum severity per subject. ae <- ae %>% arrange(USUBJID, ASEV) %>% group_by(USUBJID) %>% slice(1) %>% ungroup() # Define layout and build table: extra_args_1 <- list(.stats = c("count_unique_fraction")) 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 ) lyt <- basic_table( show_colcounts = TRUE, colcount_format = "N=xx", top_level_section_div = " " ) %>% append_topleft("n (%)") %>% split_cols_by( "colspan_trt", split_fun = trim_levels_to_map(map = colspan_trt_map) ) %>% split_cols_by(trtvar) %>% analyze_num_patients( vars = "USUBJID", .stats = "unique", .formats = c("unique" = jjcsformat_count_fraction), .labels = "Subjects with >= 1 AE" ) %>% analyze( "ASEV", afun = a_freq_j, extra_args = extra_args_1, var_labels = "Severity", nested = FALSE, show_labels = "visible", ) result <- build_table(lyt, ae, alt_counts_df = adsl) # Prune missing category if all zeros: result <- safe_prune_table( result, prune_func = count_pruner(cat_include = "Missing") ) # 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) ``` ```{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')`) ::::