Count patients with abnormal analysis range values by baseline status

The analyze function count_abnormal_by_baseline() creates a layout element to count patients with abnormal analysis range values, categorized by baseline status.

This function analyzes primary analysis variable var which indicates abnormal range results. Additional analysis variables that can be supplied as a list via the variables parameter are id (defaults to USUBJID), a variable to indicate unique subject identifiers, and baseline (defaults to BNRIND), a variable to indicate baseline reference ranges.

For each direction specified via the abnormal parameter (e.g. High or Low), we condition on baseline range result and count patients in the numerator and denominator as follows for each of the following categories:

Not <abnormality>
- num: The number of patients without abnormality at baseline (excluding those with missing baseline) and with at least one abnormality post-baseline.
- denom: The number of patients without abnormality at baseline (excluding those with missing baseline).
<Abnormality>
- num: The number of patients with abnormality as baseline and at least one abnormality post-baseline.
- denom: The number of patients with abnormality at baseline.
Total
- num: The number of patients with at least one post-baseline record and at least one abnormality post-baseline.
- denom: The number of patients with at least one post-baseline record.

This function assumes that df has been filtered to only include post-baseline records.

Usage

count_abnormal_by_baseline(
  lyt,
  var,
  abnormal,
  variables = list(id = "USUBJID", baseline = "BNRIND"),
  na_str = "<Missing>",
  nested = TRUE,
  ...,
  table_names = abnormal,
  .stats = NULL,
  .formats = NULL,
  .labels = NULL,
  .indent_mods = NULL
)

s_count_abnormal_by_baseline(
  df,
  .var,
  abnormal,
  na_str = "<Missing>",
  variables = list(id = "USUBJID", baseline = "BNRIND")
)

a_count_abnormal_by_baseline(
  df,
  .var,
  abnormal,
  na_str = "<Missing>",
  variables = list(id = "USUBJID", baseline = "BNRIND")
)

Arguments

lyt

(PreDataTableLayouts)
layout that analyses will be added to.

abnormal

(character)
values identifying the abnormal range level(s) in .var.

variables

(named list of string)
list of additional analysis variables.

na_str

(string)
the explicit na_level argument you used in the pre-processing steps (maybe with df_explicit_na()). The default is "<Missing>".

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.

Options are: 'fraction'

.formats

(named character or list)
formats for the statistics. See Details in analyze_vars for more information on the "auto" setting.

.labels

(named character)
labels for the statistics (without indent).

.indent_mods

(named integer)
indent modifiers for the labels. Defaults to 0, which corresponds to the unmodified default behavior. Can be negative.

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.

Value

count_abnormal_by_baseline() 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_abnormal_by_baseline() to the table layout.

s_count_abnormal_by_baseline() returns statistic fraction which is a named list with 3 labeled elements: not_abnormal, abnormal, and total. Each element contains a vector with num and denom patient counts.

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

Functions

count_abnormal_by_baseline(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper for rtables::analyze().
s_count_abnormal_by_baseline(): Statistics function for a single abnormal level.
a_count_abnormal_by_baseline(): Formatted analysis function which is used as afun in count_abnormal_by_baseline().

Note

df should be filtered to include only post-baseline records.
If the baseline variable or analysis variable contains NA records, it is expected that df has been pre-processed using df_explicit_na() or explicit_na().

Examples

df <- data.frame(
  USUBJID = as.character(c(1:6)),
  ANRIND = factor(c(rep("LOW", 4), "NORMAL", "HIGH")),
  BNRIND = factor(c("LOW", "NORMAL", "HIGH", NA, "LOW", "NORMAL"))
)
df <- df_explicit_na(df)

# Layout creating function.
basic_table() %>%
  count_abnormal_by_baseline(var = "ANRIND", abnormal = c(High = "HIGH")) %>%
  build_table(df)
#>                all obs  
#> ————————————————————————
#> High                    
#>   Not high    1/4 (25%) 
#>   High           0/1    
#>   Total      1/6 (16.7%)

# Passing of statistics function and formatting arguments.
df2 <- data.frame(
  ID = as.character(c(1, 2, 3, 4)),
  RANGE = factor(c("NORMAL", "LOW", "HIGH", "HIGH")),
  BLRANGE = factor(c("LOW", "HIGH", "HIGH", "NORMAL"))
)

basic_table() %>%
  count_abnormal_by_baseline(
    var = "RANGE",
    abnormal = c(Low = "LOW"),
    variables = list(id = "ID", baseline = "BLRANGE"),
    .formats = c(fraction = "xx / xx"),
    .indent_mods = c(fraction = 2L)
  ) %>%
  build_table(df2)
#>                 all obs
#> ———————————————————————
#> Low                    
#>       Not low    1 / 3 
#>       Low        0 / 1 
#>       Total      1 / 4