TSFAE08

Subjects With Treatment-emergent Adverse Events (Excluding Serious Adverse Events) With Frequency =5% in Any Treatment Group by System Organ Class and Preferred Term

Output

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Code

# Program Name:              tsfae08.R

# Prep Environment

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

# Define script level parameters:

# - Define output ID and file location

tblid <- "TSFAE08"
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))

adae <- pharmaverseadamjnj::adae %>%
  filter(TRTEMFL == "Y" & AESER == "N") %>%
  select(USUBJID, TRTEMFL, AEBODSYS, AEDECOD)

adsl$colspan_trt <- factor(
  ifelse(adsl[[trtvar]] == "Placebo", " ", "Active Study Agent"),
  levels = c("Active Study Agent", " ")
)

# join data together
ae <- adae %>% right_join(., adsl, by = c("USUBJID"))

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_args_1 <- list(
  denom = "n_altdf",
  .stats = c("count_unique_fraction")
)


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(
    "TRTEMFL",
    afun = a_freq_j,
    show_labels = "hidden",
    extra_args = append(
      extra_args_1,
      list(label = "Subjects with >=1 AE", val = "Y")
    )
  ) %>%
  split_rows_by(
    "AEBODSYS",
    child_labels = "hidden",
    split_label = "System Organ Class",
    label_pos = "topleft",
    split_fun = trim_levels_in_group("AEDECOD"),
    section_div = c(" "),
    indent_mod = 0L
  ) %>%
  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)

# If there is no data remove top row and display "No data to display" text
if (length(adae$TRTEMFL) == 0) {
  result <- safe_prune_table(
    result,
    prune_func = remove_rows(removerowtext = "Subjects with >=1 AE")
  )
}

# Post-Processing step to sort by descending count on chosen active treatment columns.

if (length(adae$TRTEMFL) != 0) {
  result <- sort_at_path(
    result,
    c("root", "AEBODSYS"),
    scorefun = jj_complex_scorefun()
  )
  result <- sort_at_path(
    result,
    c("root", "AEBODSYS", "*", "AEDECOD"),
    scorefun = jj_complex_scorefun()
  )

  ################################################################################
  # Prune table to only keep those that meet x% criteria, but top row is not subject to pruning
  ################################################################################
  result <- safe_prune_table(
    result,
    prune_func = bspt_pruner(
      fraction = 0.05,
      keeprowtext = "Subjects with >=1 AE",
      cols = c(trtvar)
    )
  )
}

# 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")

TSFAE08: Subjects With Treatment-emergent Adverse Events (Excluding Serious Adverse Events) With Frequency =[5]% in [Any Treatment Group] by System Organ Class and Preferred Term; Safety Analysis Set (Study jjcs - core)
	Active Study Agent
System Organ Class	Xanomeline High Dose	Xanomeline Low Dose	Combined	Placebo
Preferred Term, n (%)	N=53	N=73	N=126	N=59
Subjects with ≥1 AE	47 (88.7%)	54 (74.0%)	101 (80.2%)	34 (57.6%)

General disorders and administration site conditions	21 (39.6%)	26 (35.6%)	47 (37.3%)	10 (16.9%)
APPLICATION SITE PRURITUS	7 (13.2%)	12 (16.4%)	19 (15.1%)	3 (5.1%)
APPLICATION SITE ERYTHEMA	6 (11.3%)	7 (9.6%)	13 (10.3%)	1 (1.7%)
APPLICATION SITE IRRITATION	5 (9.4%)	5 (6.8%)	10 (7.9%)	1 (1.7%)
APPLICATION SITE DERMATITIS	1 (1.9%)	4 (5.5%)	5 (4.0%)	3 (5.1%)

Skin and subcutaneous tissue disorders	25 (47.2%)	21 (28.8%)	46 (36.5%)	10 (16.9%)
PRURITUS	13 (24.5%)	7 (9.6%)	20 (15.9%)	5 (8.5%)
ERYTHEMA	5 (9.4%)	4 (5.5%)	9 (7.1%)	2 (3.4%)
RASH	3 (5.7%)	6 (8.2%)	9 (7.1%)	3 (5.1%)
HYPERHIDROSIS	5 (9.4%)	1 (1.4%)	6 (4.8%)	0
SKIN IRRITATION	3 (5.7%)	3 (4.1%)	6 (4.8%)	1 (1.7%)

Nervous system disorders	13 (24.5%)	11 (15.1%)	24 (19.0%)	2 (3.4%)
DIZZINESS	6 (11.3%)	6 (8.2%)	12 (9.5%)	0
HEADACHE	4 (7.5%)	0	4 (3.2%)	1 (1.7%)

Cardiac disorders	8 (15.1%)	8 (11.0%)	16 (12.7%)	4 (6.8%)
SINUS BRADYCARDIA	5 (9.4%)	2 (2.7%)	7 (5.6%)	0

Gastrointestinal disorders	6 (11.3%)	6 (8.2%)	12 (9.5%)	4 (6.8%)
NAUSEA	3 (5.7%)	2 (2.7%)	5 (4.0%)	0
DIARRHOEA	0	1 (1.4%)	1 (0.8%)	3 (5.1%)

Respiratory, thoracic and mediastinal disorders	5 (9.4%)	5 (6.8%)	10 (7.9%)	4 (6.8%)
COUGH	1 (1.9%)	4 (5.5%)	5 (4.0%)	1 (1.7%)
NASAL CONGESTION	3 (5.7%)	0	3 (2.4%)	2 (3.4%)

Infections and infestations	4 (7.5%)	4 (5.5%)	8 (6.3%)	11 (18.6%)
UPPER RESPIRATORY TRACT INFECTION	1 (1.9%)	0	1 (0.8%)	3 (5.1%)

Note: Subjects are counted only once for any given event, regardless of the number of times they actually experienced the event.
Note: Adverse events are coded using MedDRA version 26.0.

Download RTF file

--- title: TSFAE08 subtitle: Subjects With Treatment-emergent Adverse Events (Excluding Serious Adverse Events) With Frequency =5% in Any Treatment Group by System Organ Class and Preferred Term --- ------------------------------------------------------------------------ {{< 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: tsfae08.R # Prep Environment library(envsetup) library(tern) library(dplyr) library(rtables) library(junco) # Define script level parameters: # - Define output ID and file location tblid <- "TSFAE08" 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)) adae <- pharmaverseadamjnj::adae %>% filter(TRTEMFL == "Y" & AESER == "N") %>% select(USUBJID, TRTEMFL, AEBODSYS, AEDECOD) adsl$colspan_trt <- factor( ifelse(adsl[[trtvar]] == "Placebo", " ", "Active Study Agent"), levels = c("Active Study Agent", " ") ) # join data together ae <- adae %>% right_join(., adsl, by = c("USUBJID")) colspan_trt_map <- create_colspan_map( adsl, non_active_grp = "Placebo", non_active_grp_span_lbl = " ", active_grp_span_lbl = "Active Study Agent", colspan_var = "colspan_trt", trt_var = trtvar ) # Define layout and build table: extra_args_1 <- list( denom = "n_altdf", .stats = c("count_unique_fraction") ) lyt <- rtables::basic_table( top_level_section_div = " ", show_colcounts = TRUE, colcount_format = "N=xx" ) %>% split_cols_by( "colspan_trt", split_fun = trim_levels_to_map(map = colspan_trt_map) ) if (combined_colspan_trt == TRUE) { lyt <- lyt %>% split_cols_by(trtvar, split_fun = mysplit) } else { lyt <- lyt %>% split_cols_by(trtvar) } lyt <- lyt %>% analyze( "TRTEMFL", afun = a_freq_j, show_labels = "hidden", extra_args = append( extra_args_1, list(label = "Subjects with >=1 AE", val = "Y") ) ) %>% split_rows_by( "AEBODSYS", child_labels = "hidden", split_label = "System Organ Class", label_pos = "topleft", split_fun = trim_levels_in_group("AEDECOD"), section_div = c(" "), indent_mod = 0L ) %>% summarize_row_groups( "AEBODSYS", cfun = a_freq_j, extra_args = extra_args_1 ) %>% analyze("AEDECOD", afun = a_freq_j, extra_args = extra_args_1) %>% append_topleft(" Preferred Term, n (%)") result <- build_table(lyt, ae, alt_counts_df = adsl) # If there is no data remove top row and display "No data to display" text if (length(adae$TRTEMFL) == 0) { result <- safe_prune_table( result, prune_func = remove_rows(removerowtext = "Subjects with >=1 AE") ) } # Post-Processing step to sort by descending count on chosen active treatment columns. if (length(adae$TRTEMFL) != 0) { result <- sort_at_path( result, c("root", "AEBODSYS"), scorefun = jj_complex_scorefun() ) result <- sort_at_path( result, c("root", "AEBODSYS", "*", "AEDECOD"), scorefun = jj_complex_scorefun() ) ################################################################################ # Prune table to only keep those that meet x% criteria, but top row is not subject to pruning ################################################################################ result <- safe_prune_table( result, prune_func = bspt_pruner( fraction = 0.05, keeprowtext = "Subjects with >=1 AE", cols = c(trtvar) ) ) } # 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')`) ::::