teal Module: Forest Response Plot

This module produces a grid-style forest plot for response data with ADaM structure.

Usage

tm_g_forest_rsp(
  label,
  dataname,
  parentname = ifelse(inherits(arm_var, "data_extract_spec"),
    teal.transform::datanames_input(arm_var), "ADSL"),
  arm_var,
  arm_ref_comp = NULL,
  paramcd,
  aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
    "AVALC"), "AVALC", fixed = TRUE),
  subgroup_var,
  strata_var,
  stats = c("n_tot", "n", "n_rsp", "prop", "or", "ci"),
  riskdiff = NULL,
  fixed_symbol_size = TRUE,
  conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order =
    TRUE),
  default_responses = c("CR", "PR", "Y", "Complete Response (CR)",
    "Partial Response (PR)"),
  plot_height = c(500L, 200L, 2000L),
  plot_width = c(1500L, 800L, 3000L),
  rel_width_forest = c(25L, 0L, 100L),
  font_size = c(15L, 1L, 30L),
  pre_output = NULL,
  post_output = NULL,
  ggplot2_args = teal.widgets::ggplot2_args(),
  decorators = NULL
)

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.

arm_ref_comp

(list) optional,
if specified it must be a named list with each element corresponding to an arm variable in ADSL and the element must be another list (possibly with delayed teal.transform::variable_choices() or delayed teal.transform::value_choices() with the elements named ref and comp that the defined the default reference and comparison arms when the arm variable is changed.

paramcd

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

aval_var

(teal.transform::choices_selected())
object with all available choices and pre-selected option for the analysis variable.

subgroup_var

(teal.transform::choices_selected())
object with all available choices and preselected option for variable names that can be used as the default subgroups.

strata_var

(teal.transform::choices_selected())
names of the variables for stratified analysis.

stats

(character)
the names of statistics to be reported among:

n: Total number of observations per group.
n_rsp: Number of responders per group.
prop: Proportion of responders.
n_tot: Total number of observations.
or: Odds ratio.
ci : Confidence interval of odds ratio.
pval: p-value of the effect. Note, the statistics n_tot, or, and ci are required.

riskdiff

(list)
if a risk (proportion) difference column should be added, a list of settings to apply within the column. See tern::control_riskdiff() for details. If NULL, no risk difference column will be added.

fixed_symbol_size

(logical)
When (TRUE), the same symbol size is used for plotting each estimate. Otherwise, the symbol size will be proportional to the sample size in each each subgroup.

conf_level

(teal.transform::choices_selected())
object with all available choices and pre-selected option for the confidence level, each within range of (0, 1).

default_responses

(list or character)
defines the default codes for the response variable in the module per value of paramcd. A passed vector is transmitted for all paramcd values. A passed list must be named and contain arrays, each name corresponding to a single value of paramcd. Each array may contain default response values or named arrays rsp of default selected response values and levels of default level choices.

plot_height

(numeric) optional
vector of length three with c(value, min, max). Specifies the height of the main plot and renders a slider on the plot to interactively adjust the plot height.

plot_width

(numeric) optional
vector of length three with c(value, min, max). Specifies the width of the main plot and renders a slider on the plot to interactively adjust the plot width.

rel_width_forest

(proportion)
proportion of total width to allocate to the forest plot. Relative width of table is then 1 - rel_width_forest. If as_list = TRUE, this parameter is ignored.

font_size

(numeric(1))
font size.

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.

ggplot2_args

(ggplot2_args) optional
object created by teal.widgets::ggplot2_args() with settings for the module plot. For this module, this argument will only accept ggplot2_args object with labs list of following child elements: title, caption. No other elements would be taken into account. The argument is merged with option teal.ggplot2_args and with default module arguments (hard coded in the module body).

For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets").

decorators

" (list of teal_transform_module, named list of teal_transform_module or" NULL) optional, if not NULL, decorator for tables or plots included in the module. When a named list of teal_transform_module, the decorators are applied to the respective output objects.

Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.

See section "Decorating Module" below for more details.

Value

a teal_module object.

Decorating Module

This module generates the following objects, which can be modified in place using decorators:

plot (ggplot2)

For additional details and examples of decorators, refer to the vignette vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.

Examples in Shinylive

example-1: Open in Shinylive

Examples

library(nestcolor)
library(dplyr)

data <- teal_data()
data <- within(data, {
  ADSL <- tmc_ex_adsl
  ADRS <- tmc_ex_adrs %>%
    mutate(AVALC = d_onco_rsp_label(AVALC) %>%
      with_label("Character Result/Finding")) %>%
    filter(PARAMCD != "OVRINV" | AVISIT == "FOLLOW UP")
})
join_keys(data) <- default_cdisc_join_keys[names(data)]

ADSL <- data[["ADSL"]]
ADRS <- data[["ADRS"]]

arm_ref_comp <- list(
  ARM = list(
    ref = "B: Placebo",
    comp = c("A: Drug X", "C: Combination")
  ),
  ARMCD = list(
    ref = "ARM B",
    comp = c("ARM A", "ARM C")
  )
)

app <- init(
  data = data,
  modules = modules(
    tm_g_forest_rsp(
      label = "Forest Response",
      dataname = "ADRS",
      arm_var = choices_selected(
        variable_choices(ADSL, c("ARM", "ARMCD")),
        "ARMCD"
      ),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        value_choices(ADRS, "PARAMCD", "PARAM"),
        "INVET"
      ),
      subgroup_var = choices_selected(
        variable_choices(ADSL, names(ADSL)),
        c("BMRKR2", "SEX")
      ),
      strata_var = choices_selected(
        variable_choices(ADSL, c("STRATA1", "STRATA2")),
        "STRATA2"
      ),
      plot_height = c(600L, 200L, 2000L),
      default_responses = list(
        BESRSPI = list(
          rsp = c("Stable Disease (SD)", "Not Evaluable (NE)"),
          levels = c(
            "Complete Response (CR)", "Partial Response (PR)", "Stable Disease (SD)",
            "Progressive Disease (PD)", "Not Evaluable (NE)"
          )
        ),
        INVET = list(
          rsp = c("Complete Response (CR)", "Partial Response (PR)"),
          levels = c(
            "Complete Response (CR)", "Not Evaluable (NE)", "Partial Response (PR)",
            "Progressive Disease (PD)", "Stable Disease (SD)"
          )
        ),
        OVRINV = list(
          rsp = c("Progressive Disease (PD)", "Stable Disease (SD)"),
          levels = c("Progressive Disease (PD)", "Stable Disease (SD)", "Not Evaluable (NE)")
        )
      )
    )
  )
)
#> Initializing tm_g_forest_rsp
#> Initializing reporter_previewer_module
if (interactive()) {
  shinyApp(app$ui, app$server)
}