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This module produces a table to summarize laboratory test results with highest grade post-baseline

Usage

tm_t_abnormality_by_worst_grade(
  label,
  dataname,
  parentname = ifelse(inherits(arm_var, "data_extract_spec"),
    teal.transform::datanames_input(arm_var), "ADSL"),
  arm_var,
  id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
    subset = "USUBJID"), selected = "USUBJID", fixed = TRUE),
  paramcd,
  atoxgr_var =
    teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset =
    "ATOXGR"), selected = "ATOXGR", fixed = TRUE),
  worst_high_flag_var =
    teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset =
    "WGRHIFL"), selected = "WGRHIFL", fixed = TRUE),
  worst_low_flag_var =
    teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset =
    "WGRLOFL"), selected = "WGRLOFL", fixed = TRUE),
  worst_flag_indicator = teal.transform::choices_selected("Y"),
  add_total = TRUE,
  total_label = default_total_label(),
  drop_arm_levels = TRUE,
  pre_output = NULL,
  post_output = NULL,
  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(s) in the results table. If there are two elements selected for arm_var, second variable will be nested under the first variable.

id_var

(teal.transform::choices_selected())
object specifying the variable name for subject id.

paramcd

(teal.transform::choices_selected())
object with all available choices and preselected option for the parameter code variable from dataname.

atoxgr_var

(teal.transform::choices_selected())
object with all available choices and preselected option for variable names that can be used as Analysis Toxicity Grade.

worst_high_flag_var

(teal.transform::choices_selected())
object with all available choices and preselected option for variable names that can be used as Worst High Grade flag.

worst_low_flag_var

(teal.transform::choices_selected())
object with all available choices and preselected option for variable names that can be used as Worst Low Grade flag.

worst_flag_indicator

(teal.transform::choices_selected())
value indicating worst grade.

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").

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

optional, (shiny.tag)
with text placed before the output to put the output into context. For example a title.

post_output

optional, (shiny.tag)
with text placed after the output to put the output into context. For example the shiny::helpText() elements are useful.

basic_table_args

optional, (basic_table_args)
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.

See also

The TLG Catalog where additional example apps implementing this module can be found.

Examples

library(dplyr)
library(formatters)

ADSL <- tmc_ex_adsl
ADLB <- tmc_ex_adlb %>%
  filter(!AVISIT %in% c("SCREENING", "BASELINE"))

app <- init(
  data = cdisc_data(
    ADSL = ADSL,
    ADLB = ADLB,
    code = "
      ADSL <- tmc_ex_adsl
      ADLB <- tmc_ex_adlb %>%
        filter(!AVISIT %in% c(\"SCREENING\", \"BASELINE\"))
    "
  ),
  modules = modules(
    tm_t_abnormality_by_worst_grade(
      label = "Laboratory Test Results with Highest Grade Post-Baseline",
      dataname = "ADLB",
      arm_var = choices_selected(
        choices = variable_choices(ADSL, subset = c("ARM", "ARMCD")),
        selected = "ARM"
      ),
      paramcd = choices_selected(
        choices = value_choices(ADLB, "PARAMCD", "PARAM"),
        selected = c("ALT", "CRP", "IGA")
      ),
      add_total = FALSE
    )
  ),
  filter = teal_slices(
    teal_slice("ADSL", "SAFFL", selected = "Y"),
    teal_slice("ADLB", "ONTRTFL", selected = "Y")
  )
)
#> [INFO] 2024-02-26 01:42:38.0553 pid:1518 token:[] teal.modules.clinical Initializing tm_t_abnormality_by_worst_grade
if (interactive()) {
  shinyApp(app$ui, app$server)
}