DTHT01

Deaths

Code
lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARM", split_fun = add_overall_level("All Patients", first = FALSE)) %>%
  count_values(
    "DTHFL",
    values = "Y",
    .labels = c(count_fraction = "Total number of deaths"),
    .formats = c(count_fraction = "xx (xx.x%)")
  ) %>%
  analyze_vars(vars = c("DTHCAT"), var_labels = c("Primary Cause of Death"))

result <- build_table(lyt, df = adsl)
result
                         A: Drug X    B: Placebo   C: Combination   All Patients
                          (N=134)      (N=134)        (N=132)         (N=400)   
————————————————————————————————————————————————————————————————————————————————
Total number of deaths   25 (18.7%)   23 (17.2%)     22 (16.7%)      70 (17.5%) 
Primary Cause of Death                                                          
  n                          25           23             22              70     
  ADVERSE EVENT           9 (36%)     7 (30.4%)      10 (45.5%)      26 (37.1%) 
  PROGRESSIVE DISEASE     8 (32%)     6 (26.1%)      6 (27.3%)       20 (28.6%) 
  OTHER                   8 (32%)     10 (43.5%)     6 (27.3%)       24 (34.3%)

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Code
lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARM", split_fun = add_overall_level("All Patients", first = FALSE)) %>%
  count_values(
    "DTHFL",
    values = "Y",
    .labels = c(count_fraction = "Total number of deaths"),
    .formats = c(count_fraction = "xx (xx.x%)")
  ) %>%
  analyze_vars(vars = c("DTHCAT"), var_labels = c("Primary Cause of Death")) %>%
  split_rows_by("DTHCAT", split_fun = keep_split_levels("OTHER"), child_labels = "hidden") %>%
  analyze_vars(
    "DTHCAUS",
    .stats = "count_fraction",
    .indent_mods = c("count_fraction" = 2L),
    show_labels = "hidden"
  ) %>%
  analyze_vars(
    vars = "LDDTHGR1",
    nested = FALSE,
    var_labels = "Days from last drug administration",
    show_labels = "visible"
  ) %>%
  split_rows_by(
    "LDDTHGR1",
    split_fun = remove_split_levels("<Missing>"),
    split_label = "Primary cause by days from last study drug administration",
    label_pos = "visible"
  ) %>%
  analyze_vars("DTHCAT")

result <- build_table(lyt, df = adsl) %>% prune_table()

result
                                                            A: Drug X    B: Placebo   C: Combination   All Patients
                                                             (N=134)      (N=134)        (N=132)         (N=400)   
———————————————————————————————————————————————————————————————————————————————————————————————————————————————————
Total number of deaths                                      25 (18.7%)   23 (17.2%)     22 (16.7%)      70 (17.5%) 
Primary Cause of Death                                                                                             
  n                                                             25           23             22              70     
  ADVERSE EVENT                                              9 (36%)     7 (30.4%)      10 (45.5%)      26 (37.1%) 
  PROGRESSIVE DISEASE                                        8 (32%)     6 (26.1%)      6 (27.3%)       20 (28.6%) 
  OTHER                                                      8 (32%)     10 (43.5%)     6 (27.3%)       24 (34.3%) 
    LOST TO FOLLOW UP                                        2 (25%)      2 (20%)       2 (33.3%)        6 (25%)   
    MISSING                                                  2 (25%)      3 (30%)       2 (33.3%)       7 (29.2%)  
    Post-study reporting of death                           1 (12.5%)     2 (20%)       1 (16.7%)       4 (16.7%)  
    SUICIDE                                                  2 (25%)      2 (20%)       1 (16.7%)       5 (20.8%)  
    UNKNOWN                                                 1 (12.5%)     1 (10%)           0            2 (8.3%)  
Days from last drug administration                                                                                 
  n                                                             25           23             22              70     
  <=30                                                       14 (56%)    11 (47.8%)     14 (63.6%)      39 (55.7%) 
  >30                                                        11 (44%)    12 (52.2%)     8 (36.4%)       31 (44.3%) 
Primary cause by days from last study drug administration                                                          
  <=30                                                                                                             
    n                                                           14           11             14              39     
    ADVERSE EVENT                                           4 (28.6%)    2 (18.2%)      6 (42.9%)       12 (30.8%) 
    PROGRESSIVE DISEASE                                     6 (42.9%)    3 (27.3%)      4 (28.6%)       13 (33.3%) 
    OTHER                                                   4 (28.6%)    6 (54.5%)      4 (28.6%)       14 (35.9%) 
  >30                                                                                                              
    n                                                           11           12             8               31     
    ADVERSE EVENT                                           5 (45.5%)    5 (41.7%)       4 (50%)        14 (45.2%) 
    PROGRESSIVE DISEASE                                     2 (18.2%)     3 (25%)        2 (25%)        7 (22.6%)  
    OTHER                                                   4 (36.4%)    4 (33.3%)       2 (25%)        10 (32.3%)

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Code
dthcaus_levels <- levels(adsl[adsl$DTHCAT == "OTHER", ]$DTHCAUS)

lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARM", split_fun = add_overall_level("All Patients", first = FALSE)) %>%
  count_values(
    "DTHFL",
    values = "Y",
    .labels = c(count_fraction = "Total number of deaths"),
    .formats = c(count_fraction = "xx (xx.x%)")
  ) %>%
  analyze_vars(
    vars = c("DTHCAT"),
    var_labels = c("Primary Cause of Death"),
    table_names = "primary_cause"
  ) %>%
  split_rows_by(
    "DTHCAT",
    split_fun = keep_split_levels("OTHER"),
    child_labels = "hidden"
  ) %>%
  count_values(
    "DTHCAUS",
    values = dthcaus_levels[5],
    .labels = c(count_fraction = "Post-study reportings of death"),
    .formats = c(count_fraction = "xx (xx.x%)"),
    .indent_mods = c(count_fraction = 2L),
    table_names = "post_study_deaths"
  ) %>%
  count_values(
    "DTHCAUS",
    values = dthcaus_levels[-5],
    .labels = c(count_fraction = "All other causes"),
    .formats = c(count_fraction = "xx (xx.x%)"),
    .indent_mods = c(count_fraction = 2L),
    table_names = "all_other_causes"
  )

result <- build_table(lyt, df = adsl)

result
                                     A: Drug X    B: Placebo   C: Combination   All Patients
                                      (N=134)      (N=134)        (N=132)         (N=400)   
————————————————————————————————————————————————————————————————————————————————————————————
Total number of deaths               25 (18.7%)   23 (17.2%)     22 (16.7%)      70 (17.5%) 
Primary Cause of Death                                                                      
  n                                      25           23             22              70     
  ADVERSE EVENT                       9 (36%)     7 (30.4%)      10 (45.5%)      26 (37.1%) 
  PROGRESSIVE DISEASE                 8 (32%)     6 (26.1%)      6 (27.3%)       20 (28.6%) 
  OTHER                               8 (32%)     10 (43.5%)     6 (27.3%)       24 (34.3%) 
    Post-study reportings of death   1 (12.5%)    2 (20.0%)      1 (16.7%)       4 (16.7%)  
    All other causes                 7 (87.5%)    8 (80.0%)      5 (83.3%)       20 (83.3%)

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Code
dthcaus_levels <- levels(adsl[adsl$DTHCAT == "OTHER", ]$DTHCAUS)

# create a helper variable DTHCAUS_other
adsl <- adsl %>%
  mutate(
    DTHCAUS_other = factor(ifelse(
      DTHCAT == "OTHER" & DTHCAUS != "Post-study reporting of death", as.character(DTHCAUS), NA
    ), levels = c("LOST TO FOLLOW UP", "SUICIDE", "UNKNOWN", "MISSING")) %>% explicit_na()
  )

lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARM", split_fun = add_overall_level("All Patients", first = FALSE)) %>%
  count_values(
    "DTHFL",
    values = "Y",
    .labels = c(count_fraction = "Total number of deaths"),
    .formats = c(count_fraction = "xx (xx.x%)")
  ) %>%
  analyze_vars(
    vars = c("DTHCAT"),
    var_labels = c("Primary Cause of Death"),
    table_names = "primary_cause"
  ) %>%
  split_rows_by("DTHCAT", split_fun = keep_split_levels("OTHER"), child_labels = "hidden") %>%
  count_values(
    "DTHCAUS",
    values = dthcaus_levels[5],
    .labels = c(count_fraction = "Post-study reportings of death"),
    .formats = c(count_fraction = "xx (xx.x%)"),
    .indent_mods = c(count_fraction = 2L),
    table_names = "post_study_deaths"
  ) %>%
  count_values(
    "DTHCAUS",
    values = dthcaus_levels[-5],
    .labels = c(count_fraction = "All other causes"),
    .formats = c(count_fraction = "xx (xx.x%)"),
    .indent_mods = c(count_fraction = 2L),
    table_names = "all_other_causes"
  ) %>%
  analyze_vars(
    "DTHCAUS_other",
    .stats = "count_fraction",
    .indent_mods = c("count_fraction" = 3L),
    show_labels = "hidden"
  )

result <- build_table(lyt, df = adsl)

result
                                     A: Drug X    B: Placebo   C: Combination   All Patients
                                      (N=134)      (N=134)        (N=132)         (N=400)   
————————————————————————————————————————————————————————————————————————————————————————————
Total number of deaths               25 (18.7%)   23 (17.2%)     22 (16.7%)      70 (17.5%) 
Primary Cause of Death                                                                      
  n                                      25           23             22              70     
  ADVERSE EVENT                       9 (36%)     7 (30.4%)      10 (45.5%)      26 (37.1%) 
  PROGRESSIVE DISEASE                 8 (32%)     6 (26.1%)      6 (27.3%)       20 (28.6%) 
  OTHER                               8 (32%)     10 (43.5%)     6 (27.3%)       24 (34.3%) 
    Post-study reportings of death   1 (12.5%)    2 (20.0%)      1 (16.7%)       4 (16.7%)  
    All other causes                 7 (87.5%)    8 (80.0%)      5 (83.3%)       20 (83.3%) 
      LOST TO FOLLOW UP              2 (28.6%)     2 (25%)        2 (40%)         6 (30%)   
      SUICIDE                        2 (28.6%)     2 (25%)        1 (20%)         5 (25%)   
      UNKNOWN                        1 (14.3%)    1 (12.5%)          0            2 (10%)   
      MISSING                        2 (28.6%)    3 (37.5%)       2 (40%)         7 (35%)

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Code
library(tern)
library(dplyr)

adsl <- random.cdisc.data::cadsl

# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.
adsl <- df_explicit_na(adsl) %>% filter(SAFFL == "Y")

# Reorder the levels in "DTHCAT" to put Other category at the end.
adsl$DTHCAT <- factor(adsl$DTHCAT, levels = c("ADVERSE EVENT", "PROGRESSIVE DISEASE", "OTHER", "<Missing>"))

Reproducibility

Timestamp

[1] "2024-11-02 18:01:11 UTC"

Session Info

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 system   x86_64, linux-gnu
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 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2024-11-02
 pandoc   3.4 @ /usr/bin/ (via rmarkdown)

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