Count occurrences by grade

The analyze function count_occurrences_by_grade() creates a layout element to calculate occurrence counts by grade.

This function analyzes primary analysis variable var which indicates toxicity grades. The id variable is used to indicate unique subject identifiers (defaults to USUBJID). The user can also supply a list of custom groups of grades to analyze via the grade_groups parameter. The remove_single argument will remove single grades from the analysis so that only grade groups are analyzed.

If there are multiple grades recorded for one patient only the highest grade level is counted.

The summarize function summarize_occurrences_by_grade() performs the same function as count_occurrences_by_grade() except it creates content rows, not data rows, to summarize the current table row/column context and operates on the level of the latest row split or the root of the table if no row splits have occurred.

Usage

count_occurrences_by_grade(
  lyt,
  var,
  id = "USUBJID",
  grade_groups = list(),
  remove_single = TRUE,
  only_grade_groups = FALSE,
  var_labels = var,
  show_labels = "default",
  riskdiff = FALSE,
  na_str = default_na_str(),
  nested = TRUE,
  ...,
  table_names = var,
  .stats = NULL,
  .formats = NULL,
  .indent_mods = NULL,
  .labels = NULL
)

summarize_occurrences_by_grade(
  lyt,
  var,
  id = "USUBJID",
  grade_groups = list(),
  remove_single = TRUE,
  only_grade_groups = FALSE,
  na_str = default_na_str(),
  ...,
  .stats = NULL,
  .formats = NULL,
  .indent_mods = NULL,
  .labels = NULL
)

s_count_occurrences_by_grade(
  df,
  .var,
  .N_col,
  id = "USUBJID",
  grade_groups = list(),
  remove_single = TRUE,
  only_grade_groups = FALSE,
  labelstr = ""
)

a_count_occurrences_by_grade(
  df,
  .var,
  .N_col,
  id = "USUBJID",
  grade_groups = list(),
  remove_single = TRUE,
  only_grade_groups = FALSE,
  labelstr = ""
)

Arguments

lyt: (PreDataTableLayouts)
layout that analyses will be added to.
id: (string)
subject variable name.
grade_groups: (named list of character)
list containing groupings of grades.
remove_single: (flag)
TRUE to not include the elements of one-element grade groups in the the output list; in this case only the grade groups names will be included in the output. If only_grade_groups is set to TRUE this argument is ignored.
only_grade_groups: (flag)
whether only the specified grade groups should be included, with individual grade rows removed (TRUE), or all grades and grade groups should be displayed (FALSE).
var_labels: (character)
variable labels.
show_labels: (string)
label visibility: one of "default", "visible" and "hidden".
riskdiff: (flag)
whether a risk difference column is present. When set to TRUE, add_riskdiff() must be used as split_fun in the prior column split of the table layout, specifying which columns should be compared. See stat_propdiff_ci() for details on risk difference calculation.
na_str: (string)
string used to replace all NA or empty values in the output.
nested: (flag)
whether this layout instruction should be applied within the existing layout structure _if possible (TRUE, the default) or as a new top-level element (FALSE). Ignored if it would nest a split. underneath analyses, which is not allowed.
...: additional arguments for the lower level functions.
table_names: (character)
this can be customized in the case that the same vars are analyzed multiple times, to avoid warnings from rtables.
.stats: (character)
statistics to select for the table. Run get_stats("count_occurrences_by_grade") to see available statistics for this function.
.formats: (named character or list)
formats for the statistics. See Details in analyze_vars for more information on the "auto" setting.
.indent_mods: (named integer)
indent modifiers for the labels. Defaults to 0, which corresponds to the unmodified default behavior. Can be negative.
.labels: (named character)
labels for the statistics (without indent).
df: (data.frame)
data set containing all analysis variables.
.var, var: (string)
single variable name that is passed by rtables when requested by a statistics function.
.N_col: (integer(1))
column-wise N (column count) for the full column being analyzed that is typically passed by rtables.
labelstr: (string)
label of the level of the parent split currently being summarized (must be present as second argument in Content Row Functions). See rtables::summarize_row_groups() for more information.

Value

count_occurrences_by_grade() returns a layout object suitable for passing to further layouting functions, or to rtables::build_table(). Adding this function to an rtable layout will add formatted rows containing the statistics from s_count_occurrences_by_grade() to the table layout.

summarize_occurrences_by_grade() returns a layout object suitable for passing to further layouting functions, or to rtables::build_table(). Adding this function to an rtable layout will add formatted content rows containing the statistics from s_count_occurrences_by_grade() to the table layout.

s_count_occurrences_by_grade() returns a list of counts and fractions with one element per grade level or grade level grouping.

a_count_occurrences_by_grade() returns the corresponding list with formatted rtables::CellValue().

Functions

count_occurrences_by_grade(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper for rtables::analyze().
summarize_occurrences_by_grade(): Layout-creating function which can take content function arguments and additional format arguments. This function is a wrapper for rtables::summarize_row_groups().
s_count_occurrences_by_grade(): Statistics function which counts the number of patients by highest grade.
a_count_occurrences_by_grade(): Formatted analysis function which is used as afun in count_occurrences_by_grade().

Examples

library(dplyr)

df <- data.frame(
  USUBJID = as.character(c(1:6, 1)),
  ARM = factor(c("A", "A", "A", "B", "B", "B", "A"), levels = c("A", "B")),
  AETOXGR = factor(c(1, 2, 3, 4, 1, 2, 3), levels = c(1:5)),
  AESEV = factor(
    x = c("MILD", "MODERATE", "SEVERE", "MILD", "MILD", "MODERATE", "SEVERE"),
    levels = c("MILD", "MODERATE", "SEVERE")
  ),
  stringsAsFactors = FALSE
)

df_adsl <- df %>%
  select(USUBJID, ARM) %>%
  unique()

# Layout creating function with custom format.
basic_table() %>%
  split_cols_by("ARM") %>%
  add_colcounts() %>%
  count_occurrences_by_grade(
    var = "AESEV",
    .formats = c("count_fraction" = "xx.xx (xx.xx%)")
  ) %>%
  build_table(df, alt_counts_df = df_adsl)
#>                  A               B      
#>                (N=3)           (N=3)    
#> ————————————————————————————————————————
#> MILD       0.00 (0.00%)    2.00 (66.67%)
#> MODERATE   1.00 (33.33%)   1.00 (33.33%)
#> SEVERE     2.00 (66.67%)   0.00 (0.00%) 

# Define additional grade groupings.
grade_groups <- list(
  "-Any-" = c("1", "2", "3", "4", "5"),
  "Grade 1-2" = c("1", "2"),
  "Grade 3-5" = c("3", "4", "5")
)

basic_table() %>%
  split_cols_by("ARM") %>%
  add_colcounts() %>%
  count_occurrences_by_grade(
    var = "AETOXGR",
    grade_groups = grade_groups,
    only_grade_groups = TRUE
  ) %>%
  build_table(df, alt_counts_df = df_adsl)
#>                 A           B    
#>               (N=3)       (N=3)  
#> —————————————————————————————————
#> -Any-       3 (100%)    3 (100%) 
#> Grade 1-2   1 (33.3%)   2 (66.7%)
#> Grade 3-5   2 (66.7%)   1 (33.3%)

# Layout creating function with custom format.
basic_table() %>%
  add_colcounts() %>%
  split_rows_by("ARM", child_labels = "visible", nested = TRUE) %>%
  summarize_occurrences_by_grade(
    var = "AESEV",
    .formats = c("count_fraction" = "xx.xx (xx.xx%)")
  ) %>%
  build_table(df, alt_counts_df = df_adsl)
#>                 all obs   
#>                  (N=6)    
#> ——————————————————————————
#> A                         
#>   MILD       0.00 (0.00%) 
#>   MODERATE   1.00 (16.67%)
#>   SEVERE     2.00 (33.33%)
#> B                         
#>   MILD       2.00 (33.33%)
#>   MODERATE   1.00 (16.67%)
#>   SEVERE     0.00 (0.00%) 

basic_table() %>%
  add_colcounts() %>%
  split_rows_by("ARM", child_labels = "visible", nested = TRUE) %>%
  summarize_occurrences_by_grade(
    var = "AETOXGR",
    grade_groups = grade_groups
  ) %>%
  build_table(df, alt_counts_df = df_adsl)
#>                all obs 
#>                 (N=6)  
#> ———————————————————————
#> A                      
#>   -Any-       3 (50.0%)
#>   Grade 1-2   1 (16.7%)
#>   1               0    
#>   2           1 (16.7%)
#>   Grade 3-5   2 (33.3%)
#>   3           2 (33.3%)
#>   4               0    
#>   5               0    
#> B                      
#>   -Any-       3 (50.0%)
#>   Grade 1-2   2 (33.3%)
#>   1           1 (16.7%)
#>   2           1 (16.7%)
#>   Grade 3-5   1 (16.7%)
#>   3               0    
#>   4           1 (16.7%)
#>   5               0    

s_count_occurrences_by_grade(
  df,
  .N_col = 10L,
  .var = "AETOXGR",
  id = "USUBJID",
  grade_groups = list("ANY" = levels(df$AETOXGR))
)
#> $count_fraction
#> $count_fraction$ANY
#> [1] 6.0 0.6
#> 
#> $count_fraction$`1`
#> [1] 1.0 0.1
#> 
#> $count_fraction$`2`
#> [1] 2.0 0.2
#> 
#> $count_fraction$`3`
#> [1] 2.0 0.2
#> 
#> $count_fraction$`4`
#> [1] 1.0 0.1
#> 
#> $count_fraction$`5`
#> [1] 0 0
#> 
#> 

#  We need to ungroup `count_fraction` first so that the `rtables` formatting
# function `format_count_fraction()` can be applied correctly.
afun <- make_afun(a_count_occurrences_by_grade, .ungroup_stats = "count_fraction")
afun(
  df,
  .N_col = 10L,
  .var = "AETOXGR",
  id = "USUBJID",
  grade_groups = list("ANY" = levels(df$AETOXGR))
)
#> RowsVerticalSection (in_rows) object print method:
#> ----------------------------
#>   row_name formatted_cell indent_mod row_label
#> 1      ANY      6 (60.0%)          0       ANY
#> 2        1      1 (10.0%)          0         1
#> 3        2      2 (20.0%)          0         2
#> 4        3      2 (20.0%)          0         3
#> 5        4      1 (10.0%)          0         4
#> 6        5              0          0         5

Usage

Arguments

Value

Functions

See also

Examples