TSIDS02

Subject Disposition

Output

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Code

# Program Name:              tsids02

# Prep environment:

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

# Define script level parameters:

tblid <- "TSIDS02"
fileid <- tblid
popfl <- "FASFL"
trtvar <- "TRT01P"
tab_titles <- get_titles_from_file(input_path = '../../_data/', tblid)
string_map <- default_str_map

# Process data:

adsl <- pharmaverseadamjnj::adsl

no_data_to_report <- function(df, var) {
  if (sum(is.na(df[[var]])) == length(df[[var]])) {
    df[[var]] <- factor(NA_character_, levels = "No data to report")
  }
  return(df)
}

adsl <- no_data_to_report(df = adsl, var = "DCTREAS")
adsl <- no_data_to_report(df = adsl, var = "DCSREAS")

adsl <- adsl %>%
  filter(!!rlang::sym(popfl) == "Y") %>%
  select(
    USUBJID,
    !!rlang::sym(trtvar),
    !!rlang::sym(popfl),
    SAFFL,
    PPROTFL,
    EOTSTT,
    DCTREAS,
    EOSSTT,
    DCSREAS,
    RACE
  ) %>%
  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
  ) %>%
  mutate(
    rrisk_header = "Risk Difference (%) 95% CI",
    rrisk_label = paste(!!rlang::sym(trtvar), "vs Placebo")
  )

# Define layout and build table:

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
)

totdf <- tribble(
  ~valname , ~label  , ~levelcombo                                                 , ~exargs ,
  "Total"  , "Total" , c("Xanomeline High Dose", "Xanomeline Low Dose", "Placebo") , list()
)

rr_method <- "wald"
ref_path <- c("colspan_trt", " ", trtvar, "Placebo")
extra_args_rr <- list(
  method = rr_method,
  ref_path = ref_path,
  .stats = c("count_unique_fraction")
)


lyt <- basic_table(
  show_colcounts = TRUE,
  colcount_format = "N=xx",
  top_level_section_div = " "
) %>%
  split_cols_by(
    "colspan_trt",
    split_fun = trim_levels_to_map(map = colspan_trt_map)
  ) %>%
  split_cols_by(trtvar) %>%
  split_cols_by(
    trtvar,
    split_fun = add_combo_levels(totdf, keep_levels = "Total"),
    nested = FALSE
  ) %>%
  split_cols_by("rrisk_header", nested = FALSE) %>%
  split_cols_by(
    trtvar,
    labels_var = "rrisk_label",
    split_fun = remove_split_levels("Placebo")
  ) %>%
  # Analysis sets
  analyze(
    popfl,
    var_labels = "Analysis set",
    afun = a_freq_j,
    extra_args = append(
      extra_args_rr,
      list(label = "Full", val = "Y", riskdiff = FALSE, NULL)
    ),
    show_labels = "visible"
  ) %>%
  analyze(
    "SAFFL",
    afun = a_freq_j,
    extra_args = append(
      extra_args_rr,
      list(label = "Safety", val = "Y", riskdiff = FALSE, NULL)
    ),
    show_labels = "hidden",
    indent_mod = 1
  ) %>%
  analyze(
    "PPROTFL",
    afun = a_freq_j,
    extra_args = append(
      extra_args_rr,
      list(
        label = "Per protocol",
        val = "Y",
        riskdiff = FALSE,
        extrablankline = TRUE,
        NULL
      )
    ),
    show_labels = "hidden",
    indent_mod = 1,
    na_str = " "
  ) %>%
  # Ongoing
  analyze(
    "EOSSTT",
    show_labels = "hidden",
    afun = a_freq_j,
    extra_args = append(
      extra_args_rr,
      list(
        label = "Subjects ongoing",
        val = "ONGOING",
        riskdiff = FALSE,
        extrablankline = TRUE,
        NULL
      )
    ),
    na_str = " "
  ) %>%
  # Treatment disposition
  analyze(
    "EOTSTT",
    table_names = "Compl_Trt",
    show_labels = "hidden",
    afun = a_freq_j,
    extra_args = append(
      extra_args_rr,
      list(label = "Completed treatment", val = "COMPLETED", NULL)
    )
  ) %>%
  analyze(
    "EOTSTT",
    table_names = "DC_Trt",
    show_labels = "hidden",
    afun = a_freq_j,
    extra_args = append(
      extra_args_rr,
      list(label = "Discontinued treatment", val = "DISCONTINUED", NULL)
    )
  ) %>%
  analyze(
    "DCTREAS",
    show_labels = "hidden",
    indent_mod = 1,
    afun = a_freq_j,
    na_str = " ",
    extra_args = append(extra_args_rr, list(extrablankline = TRUE))
  ) %>%
  # Study disposition
  analyze(
    "EOSSTT",
    table_names = "Compl_Study",
    show_labels = "hidden",
    afun = a_freq_j,
    extra_args = append(
      extra_args_rr,
      list(label = "Completed study", val = "COMPLETED", NULL)
    )
  ) %>%
  analyze(
    "EOSSTT",
    show_labels = "hidden",
    table_names = "DC_Study",
    afun = a_freq_j,
    extra_args = append(
      extra_args_rr,
      list(label = "Discontinued study", val = "DISCONTINUED", NULL)
    )
  ) %>%
  analyze(
    "DCSREAS",
    show_labels = "hidden",
    indent_mod = 1,
    afun = a_freq_j,
    extra_args = append(extra_args_rr, NULL)
  )

result <- build_table(lyt, adsl)

# Post-Processing

## Remove the N=xx column headers for the risk difference columns
result <- remove_col_count(result, span_label_var = "rrisk_header")

result <- result %>%
  sort_at_path(
    path = c(
      "ma_FASFL_SAFFL_PPROTFL_EOSSTT_Compl_Trt_DC_Trt_DCTREAS_Compl_Study_DC_Study_DCSREAS",
      "DCTREAS"
    ),
    scorefun = jj_complex_scorefun(colpath = "Total", lastcat = "Other")
  ) %>%
  sort_at_path(
    path = c(
      "ma_FASFL_SAFFL_PPROTFL_EOSSTT_Compl_Trt_DC_Trt_DCTREAS_Compl_Study_DC_Study_DCSREAS",
      "DCSREAS"
    ),
    scorefun = jj_complex_scorefun(colpath = "Total", lastcat = "Other")
  )

# Prune data driven output.
result <- result %>%
  safe_prune_table(prune_func = keep_rows(keep_non_null_rows)) %>%
  safe_prune_table(
    prune_func = count_pruner(
      cols = c("colspan_trt"),
      cat_exclude = c(
        "Completed study",
        "Completed treatment",
        "Discontinued study",
        "Discontinued treatment"
      )
    )
  )

# Prune data driven output.
result <- result %>%
  safe_prune_table(prune_func = keep_rows(keep_non_null_rows)) %>%
  safe_prune_table(
    prune_func = count_pruner(
      cols = c("colspan_trt"),
      cat_exclude = c(
        "Completed study",
        "Completed treatment",
        "Discontinued study",
        "Discontinued treatment"
      )
    )
  )

# 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")

TSIDS02: Subject Disposition; [Randomized/Enrolled] Analysis Set (Study jjcs - core)
	Active Study Agent				Risk Difference (%) 95% CI
	Xanomeline High Dose	Xanomeline Low Dose	Placebo	Total	Xanomeline High Dose vs Placebo	Xanomeline Low Dose vs Placebo
	N=84	N=84	N=86	N=254
Analysis set
Full	84 (100.0%)	84 (100.0%)	86 (100.0%)	254 (100.0%)
Safety	64 (76.2%)	62 (73.8%)	59 (68.6%)	185 (72.8%)
Per protocol	64 (76.2%)	62 (73.8%)	59 (68.6%)	185 (72.8%)

Subjects ongoing	18 (21.4%)	15 (17.9%)	14 (16.3%)	47 (18.5%)

Completed treatment	19 (22.6%)	21 (25.0%)	49 (57.0%)	89 (35.0%)	-34.4 (-48.1, -20.6)	-32.0 (-45.9, -18.0)
Discontinued treatment	49 (58.3%)	43 (51.2%)	22 (25.6%)	114 (44.9%)	32.8 (18.7, 46.8)	25.6 (11.5, 39.7)
Other	49 (58.3%)	43 (51.2%)	22 (25.6%)	114 (44.9%)	0.0 (0.0, 0.0)	0.0 (0.0, 0.0)

Completed study	22 (26.2%)	21 (25.0%)	48 (55.8%)	91 (35.8%)	-29.6 (-43.7, -15.5)	-30.8 (-44.8, -16.8)
Discontinued study	44 (52.4%)	48 (57.1%)	24 (27.9%)	116 (45.7%)	24.5 (10.2, 38.8)	29.2 (15.0, 43.4)
Other	44 (52.4%)	48 (57.1%)	24 (27.9%)	116 (45.7%)	0.0 (0.0, 0.0)	0.0 (0.0, 0.0)

Download RTF file

--- title: TSIDS02 subtitle: Subject Disposition --- ------------------------------------------------------------------------ {{< 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: tsids02 # Prep environment: library(envsetup) library(tern) library(dplyr) library(rtables) library(junco) # Define script level parameters: tblid <- "TSIDS02" fileid <- tblid popfl <- "FASFL" trtvar <- "TRT01P" tab_titles <- get_titles_from_file(input_path = '../../_data/', tblid) string_map <- default_str_map # Process data: adsl <- pharmaverseadamjnj::adsl no_data_to_report <- function(df, var) { if (sum(is.na(df[[var]])) == length(df[[var]])) { df[[var]] <- factor(NA_character_, levels = "No data to report") } return(df) } adsl <- no_data_to_report(df = adsl, var = "DCTREAS") adsl <- no_data_to_report(df = adsl, var = "DCSREAS") adsl <- adsl %>% filter(!!rlang::sym(popfl) == "Y") %>% select( USUBJID, !!rlang::sym(trtvar), !!rlang::sym(popfl), SAFFL, PPROTFL, EOTSTT, DCTREAS, EOSSTT, DCSREAS, RACE ) %>% 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 ) %>% mutate( rrisk_header = "Risk Difference (%) 95% CI", rrisk_label = paste(!!rlang::sym(trtvar), "vs Placebo") ) # Define layout and build table: 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 ) totdf <- tribble( ~valname , ~label , ~levelcombo , ~exargs , "Total" , "Total" , c("Xanomeline High Dose", "Xanomeline Low Dose", "Placebo") , list() ) rr_method <- "wald" ref_path <- c("colspan_trt", " ", trtvar, "Placebo") extra_args_rr <- list( method = rr_method, ref_path = ref_path, .stats = c("count_unique_fraction") ) lyt <- basic_table( show_colcounts = TRUE, colcount_format = "N=xx", top_level_section_div = " " ) %>% split_cols_by( "colspan_trt", split_fun = trim_levels_to_map(map = colspan_trt_map) ) %>% split_cols_by(trtvar) %>% split_cols_by( trtvar, split_fun = add_combo_levels(totdf, keep_levels = "Total"), nested = FALSE ) %>% split_cols_by("rrisk_header", nested = FALSE) %>% split_cols_by( trtvar, labels_var = "rrisk_label", split_fun = remove_split_levels("Placebo") ) %>% # Analysis sets analyze( popfl, var_labels = "Analysis set", afun = a_freq_j, extra_args = append( extra_args_rr, list(label = "Full", val = "Y", riskdiff = FALSE, NULL) ), show_labels = "visible" ) %>% analyze( "SAFFL", afun = a_freq_j, extra_args = append( extra_args_rr, list(label = "Safety", val = "Y", riskdiff = FALSE, NULL) ), show_labels = "hidden", indent_mod = 1 ) %>% analyze( "PPROTFL", afun = a_freq_j, extra_args = append( extra_args_rr, list( label = "Per protocol", val = "Y", riskdiff = FALSE, extrablankline = TRUE, NULL ) ), show_labels = "hidden", indent_mod = 1, na_str = " " ) %>% # Ongoing analyze( "EOSSTT", show_labels = "hidden", afun = a_freq_j, extra_args = append( extra_args_rr, list( label = "Subjects ongoing", val = "ONGOING", riskdiff = FALSE, extrablankline = TRUE, NULL ) ), na_str = " " ) %>% # Treatment disposition analyze( "EOTSTT", table_names = "Compl_Trt", show_labels = "hidden", afun = a_freq_j, extra_args = append( extra_args_rr, list(label = "Completed treatment", val = "COMPLETED", NULL) ) ) %>% analyze( "EOTSTT", table_names = "DC_Trt", show_labels = "hidden", afun = a_freq_j, extra_args = append( extra_args_rr, list(label = "Discontinued treatment", val = "DISCONTINUED", NULL) ) ) %>% analyze( "DCTREAS", show_labels = "hidden", indent_mod = 1, afun = a_freq_j, na_str = " ", extra_args = append(extra_args_rr, list(extrablankline = TRUE)) ) %>% # Study disposition analyze( "EOSSTT", table_names = "Compl_Study", show_labels = "hidden", afun = a_freq_j, extra_args = append( extra_args_rr, list(label = "Completed study", val = "COMPLETED", NULL) ) ) %>% analyze( "EOSSTT", show_labels = "hidden", table_names = "DC_Study", afun = a_freq_j, extra_args = append( extra_args_rr, list(label = "Discontinued study", val = "DISCONTINUED", NULL) ) ) %>% analyze( "DCSREAS", show_labels = "hidden", indent_mod = 1, afun = a_freq_j, extra_args = append(extra_args_rr, NULL) ) result <- build_table(lyt, adsl) # Post-Processing ## Remove the N=xx column headers for the risk difference columns result <- remove_col_count(result, span_label_var = "rrisk_header") result <- result %>% sort_at_path( path = c( "ma_FASFL_SAFFL_PPROTFL_EOSSTT_Compl_Trt_DC_Trt_DCTREAS_Compl_Study_DC_Study_DCSREAS", "DCTREAS" ), scorefun = jj_complex_scorefun(colpath = "Total", lastcat = "Other") ) %>% sort_at_path( path = c( "ma_FASFL_SAFFL_PPROTFL_EOSSTT_Compl_Trt_DC_Trt_DCTREAS_Compl_Study_DC_Study_DCSREAS", "DCSREAS" ), scorefun = jj_complex_scorefun(colpath = "Total", lastcat = "Other") ) # Prune data driven output. result <- result %>% safe_prune_table(prune_func = keep_rows(keep_non_null_rows)) %>% safe_prune_table( prune_func = count_pruner( cols = c("colspan_trt"), cat_exclude = c( "Completed study", "Completed treatment", "Discontinued study", "Discontinued treatment" ) ) ) # Prune data driven output. result <- result %>% safe_prune_table(prune_func = keep_rows(keep_non_null_rows)) %>% safe_prune_table( prune_func = count_pruner( cols = c("colspan_trt"), cat_exclude = c( "Completed study", "Completed treatment", "Discontinued study", "Discontinued treatment" ) ) ) # 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')`) ::::