teal Module: Abnormality Summary Table

This module produces a table to summarize abnormality.

Usage

tm_t_abnormality(
  label,
  dataname,
  parentname = ifelse(inherits(arm_var, "data_extract_spec"),
    teal.transform::datanames_input(arm_var), "ADSL"),
  arm_var,
  by_vars,
  grade,
  abnormal = list(low = c("LOW", "LOW LOW"), high = c("HIGH", "HIGH HIGH")),
  id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
    subset = "USUBJID"), selected = "USUBJID", fixed = TRUE),
  baseline_var =
    teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset =
    "BNRIND"), selected = "BNRIND", fixed = TRUE),
  treatment_flag_var =
    teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset =
    "ONTRTFL"), selected = "ONTRTFL", fixed = TRUE),
  treatment_flag = teal.transform::choices_selected("Y"),
  add_total = TRUE,
  total_label = default_total_label(),
  exclude_base_abn = FALSE,
  drop_arm_levels = TRUE,
  pre_output = NULL,
  post_output = NULL,
  na_level = default_na_str(),
  basic_table_args = teal.widgets::basic_table_args()
)

Arguments

label: (character)
menu item label of the module in the teal app.
dataname: (character)
analysis data used in teal module.
parentname: (character)
parent analysis data used in teal module, usually this refers to ADSL.
arm_var: (teal.transform::choices_selected())
object with all available choices and preselected option for variable names that can be used as arm_var. It defines the grouping variable in the results table.
by_vars: (teal.transform::choices_selected())
object with all available choices and preselected option for variable names used to split the summary by rows.
grade: (teal.transform::choices_selected())
object with all available choices and preselected option for variable names that can be used to specify the abnormality grade. Variable must be factor.
abnormal: (named list)
defined by user to indicate what abnormalities are to be displayed.
id_var: (teal.transform::choices_selected())
object specifying the variable name for subject id.
baseline_var: (teal.transform::choices_selected())
variable for baseline abnormality grade.
treatment_flag_var: (teal.transform::choices_selected())
on treatment flag variable.
treatment_flag: (teal.transform::choices_selected())
value indicating on treatment records in treatment_flag_var.
add_total: (logical)
whether to include column with total number of patients.
total_label: (string)
string to display as total column/row label if column/row is enabled (see add_total). Defaults to "All Patients". To set a new default total_label to apply in all modules, run set_default_total_label("new_default").
exclude_base_abn: (logical)
whether to exclude patients who had abnormal values at baseline.
drop_arm_levels: (logical)
whether to drop unused levels of arm_var. If TRUE, arm_var levels are set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and user input for this parameter is ignored.
pre_output: (shiny.tag) optional,
with text placed before the output to put the output into context. For example a title.
post_output: (shiny.tag) optional,
with text placed after the output to put the output into context. For example the shiny::helpText() elements are useful.
na_level: (character)
the NA level in the input dataset, default to "<Missing>".
basic_table_args: (basic_table_args) optional
object created by teal.widgets::basic_table_args() with settings for the module table. The argument is merged with option teal.basic_table_args and with default module arguments (hard coded in the module body). For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets").

Value

a teal_module object.

Note

Patients with the same abnormality at baseline as on the treatment visit can be excluded in accordance with GDSR specifications by using exclude_base_abn.

Examples in Shinylive

example-1: Open in Shinylive

Examples

library(dplyr)

data <- teal_data()
data <- within(data, {
  ADSL <- tmc_ex_adsl
  ADLB <- tmc_ex_adlb %>%
    mutate(
      ONTRTFL = case_when(
        AVISIT %in% c("SCREENING", "BASELINE") ~ "",
        TRUE ~ "Y"
      ) %>% with_label("On Treatment Record Flag")
    )
})
join_keys(data) <- default_cdisc_join_keys[names(data)]

ADSL <- data[["ADSL"]]
ADLB <- data[["ADLB"]]

app <- init(
  data = data,
  modules = modules(
    tm_t_abnormality(
      label = "Abnormality Table",
      dataname = "ADLB",
      arm_var = choices_selected(
        choices = variable_choices(ADSL, subset = c("ARM", "ARMCD")),
        selected = "ARM"
      ),
      add_total = FALSE,
      by_vars = choices_selected(
        choices = variable_choices(ADLB, subset = c("LBCAT", "PARAM", "AVISIT")),
        selected = c("LBCAT", "PARAM"),
        keep_order = TRUE
      ),
      baseline_var = choices_selected(
        variable_choices(ADLB, subset = "BNRIND"),
        selected = "BNRIND", fixed = TRUE
      ),
      grade = choices_selected(
        choices = variable_choices(ADLB, subset = "ANRIND"),
        selected = "ANRIND",
        fixed = TRUE
      ),
      abnormal = list(low = "LOW", high = "HIGH"),
      exclude_base_abn = FALSE
    )
  )
)
#> Initializing tm_t_abnormality
#> Initializing reporter_previewer_module
if (interactive()) {
  shinyApp(app$ui, app$server)
}