Patient counts with abnormal range values

Primary analysis variable .var indicates the abnormal range result (character or factor) and additional analysis variables are id (character or factor) and baseline (character or factor). For each direction specified in abnormal (e.g. high or low) count patients in the numerator and denominator as follows:

num : The number of patients with this abnormality recorded while on treatment.
denom: The number of patients with at least one post-baseline assessment.

Usage

count_abnormal(
  lyt,
  var,
  abnormal = list(Low = "LOW", High = "HIGH"),
  variables = list(id = "USUBJID", baseline = "BNRIND"),
  exclude_base_abn = FALSE,
  na_str = default_na_str(),
  nested = TRUE,
  ...,
  table_names = var,
  .stats = NULL,
  .formats = NULL,
  .labels = NULL,
  .indent_mods = NULL
)

s_count_abnormal(
  df,
  .var,
  abnormal = list(Low = "LOW", High = "HIGH"),
  variables = list(id = "USUBJID", baseline = "BNRIND"),
  exclude_base_abn = FALSE
)

a_count_abnormal(
  df,
  .var,
  abnormal = list(Low = "LOW", High = "HIGH"),
  variables = list(id = "USUBJID", baseline = "BNRIND"),
  exclude_base_abn = FALSE
)

Arguments

lyt: (PreDataTableLayouts)
layout that analyses will be added to.
abnormal: (named list)
list identifying the abnormal range level(s) in var. Defaults to list(Low = "LOW", High = "HIGH") but you can also group different levels into the named list, for example, abnormal = list(Low = c("LOW", "LOW LOW"), High = c("HIGH", "HIGH HIGH")).
variables: (named list of string)
list of additional analysis variables.
exclude_base_abn: (flag)
whether to exclude subjects with baseline abnormality from numerator and denominator.
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("abnormal") 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.
.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() 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() to the table layout.

s_count_abnormal() returns the statistic fraction which is a vector with num and denom counts of patients.

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

Functions

count_abnormal(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper for rtables::analyze().
s_count_abnormal(): Statistics function which counts patients with abnormal range values for a single abnormal level.
a_count_abnormal(): Formatted analysis function which is used as afun in count_abnormal().

Note

count_abnormal() only works with a single variable containing multiple abnormal levels.
df should be filtered to include only post-baseline records.
the denominator includes patients that might have other abnormal levels at baseline, and patients with missing baseline. Patients with these abnormalities at baseline can be optionally excluded from numerator and denominator.

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following object is masked from ‘package:testthat’:
#> 
#>     matches
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

df <- data.frame(
  USUBJID = as.character(c(1, 1, 2, 2)),
  ANRIND = factor(c("NORMAL", "LOW", "HIGH", "HIGH")),
  BNRIND = factor(c("NORMAL", "NORMAL", "HIGH", "HIGH")),
  ONTRTFL = c("", "Y", "", "Y"),
  stringsAsFactors = FALSE
)

# Select only post-baseline records.
df <- df %>%
  filter(ONTRTFL == "Y")

# Layout creating function.
basic_table() %>%
  count_abnormal(var = "ANRIND", abnormal = list(high = "HIGH", low = "LOW")) %>%
  build_table(df)
#>         all obs 
#> ————————————————
#> high   1/2 (50%)
#> low    1/2 (50%)

# Passing of statistics function and formatting arguments.
df2 <- data.frame(
  ID = as.character(c(1, 1, 2, 2)),
  RANGE = factor(c("NORMAL", "LOW", "HIGH", "HIGH")),
  BL_RANGE = factor(c("NORMAL", "NORMAL", "HIGH", "HIGH")),
  ONTRTFL = c("", "Y", "", "Y"),
  stringsAsFactors = FALSE
)

# Select only post-baseline records.
df2 <- df2 %>%
  filter(ONTRTFL == "Y")

basic_table() %>%
  count_abnormal(
    var = "RANGE",
    abnormal = list(low = "LOW", high = "HIGH"),
    variables = list(id = "ID", baseline = "BL_RANGE")
  ) %>%
  build_table(df2)
#>         all obs 
#> ————————————————
#> low    1/2 (50%)
#> high   1/2 (50%)