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Patient Profile plot teal module

Source: R/tm_g_patient_profile.R
tm_g_patient_profile.Rd

Display patient profile plot as a shiny module

Usage 

tm_g_patient_profile(
  label = "Patient Profile Plot",
  patient_id = teal.picks::variables(choices = dplyr::starts_with("USUBJ"), selected =
    1L),
  sl_dataname,
  ex_dataname = NA,
  ae_dataname = NA,
  rs_dataname = NA,
  cm_dataname = NA,
  lb_dataname = NA,
  sl_start_date,
  ex_var = NULL,
  ae_var = NULL,
  ae_line_col_var = NULL,
  ae_line_col_opt = NULL,
  rs_var = NULL,
  cm_var = NULL,
  lb_var = NULL,
  x_limit = "-28, 365",
  plot_height = c(1200L, 400L, 5000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  transformators = list(),
  decorators = list()
)

Arguments

label

(character(1)) Label shown in the navigation item for the module or module group. For modules() defaults to "root". See Details.

patient_id

Either a teal.picks::variables() object, a full teal.picks::picks() object, or a variables() object. choices_selected() is being deprecated as an argument type and will be removed in the future. Describing the unique subject ID selection.

sl_dataname

(character) subject level dataset name, needs to be available in the list passed to the data argument of teal::init()

ex_dataname, ae_dataname, rs_dataname, cm_dataname, lb_dataname

(character(1)) names of exposure, adverse events, response, concomitant medications, and labs datasets, respectively; must be available in the list passed to the data argument of teal::init()
set to NA (default) to omit from analysis

sl_start_date

Either a teal.picks::variables() object, a full teal.picks::picks() object, or a variables() object. choices_selected() is being deprecated as an argument type and will be removed in the future. For the study start date variable, usually set to treatment start date or randomization date.

ex_var

Either a teal.picks::variables() object, a full teal.picks::picks() object, or a variables() object. choices_selected() is being deprecated as an argument type and will be removed in the future. For the exposure variable to plot as each line. Leave unspecified or set to NULL if exposure data is not available.

ae_var

Either a teal.picks::variables() object, a full teal.picks::picks() object, or a variables() object. choices_selected() is being deprecated as an argument type and will be removed in the future. For the adverse event variable to plot as each line. Leave unspecified or set to NULL if adverse events data is not available.

ae_line_col_var

Either a teal.picks::variables() object, a full teal.picks::picks() object, or a variables() object. choices_selected() is being deprecated as an argument type and will be removed in the future. For coloring AE lines. Leave unspecified or set to NULL if adverse events data is not available.

ae_line_col_opt

aesthetic values to map color values (named vector to map color values to each name). If not NULL, please make sure this contains all possible values for ae_line_col_var values.
leave unspecified or set to NULL if adverse events data is not available

rs_var

Either a teal.picks::variables() object, a full teal.picks::picks() object, or a variables() object. choices_selected() is being deprecated as an argument type and will be removed in the future. For the response variable to plot as each line. Leave unspecified or set to NULL if response data is not available.

cm_var

Either a teal.picks::variables() object, a full teal.picks::picks() object, or a variables() object. choices_selected() is being deprecated as an argument type and will be removed in the future. For the concomitant medication variable to plot as each line. Leave unspecified or set to NULL if concomitant medications data is not available.

lb_var

Either a teal.picks::variables() object, a full teal.picks::picks() object, or a variables() object. choices_selected() is being deprecated as an argument type and will be removed in the future. For the lab variable to plot as each line. Leave unspecified or set to NULL if labs data is not available.

x_limit

a single character string with two numbers separated by a comma indicating the x-axis limit, default is "-28, 365"

plot_height

(numeric(3))
vector to indicate default value, minimum and maximum values.

plot_width

(numeric(3))
vector to indicate default value, minimum and maximum values.

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.

transformators

(list of teal_transform_module) that will be applied to transform module's data input. To learn more check vignette("transform-input-data", package = "teal").

decorators

[Experimental] (named list of teal_transform_module) optional, decorators for the module plot output.

Value

the teal::module() object.

Details

As the patient profile module plots different domains in one plot, the study day (x-axis) is derived for consistency based the start date of user's choice in the app (for example, ADSL.RANDDT or ADSL.TRTSDT):

  • In ADAE, ADEX, and ADCM, it would be study day based on ASTDT and/or AENDT in reference to the start date

  • In ADRS and ADLB, it would be study day based on ADT in reference to the start date

For every variable domain defined (i.e ae_var) please set its corresponding analysis dataset (i.e ae_dataset)

Decorating Module

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

  • plot (grob)

A Decorator is applied to the specific output using a named list of teal_transform_module objects. The name of this list corresponds to the name of the output to which the decorator is applied. See code snippet below:

tm_g_patient_profile(
   ..., # arguments for module
   decorators = list(
     plot = teal_transform_module(...), # applied to the `plot` output
   )
)

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

To learn more please refer to the vignette vignette("transform-module-output", package = "teal") or the teal::teal_transform_module() documentation.

Reporting

This module returns an object of class teal_module, that contains a server function. Since the server function returns a teal_report object, this makes this module reportable, which means that the reporting functionality will be turned on automatically by the teal framework.

For more information on reporting in teal, see the vignettes:

Author

Xuefeng Hou (houx14) houx14@gene.com

Tina Cho (chot) tina.cho@roche.com

Molly He (hey59) hey59@gene.com

Ting Qi (qit3) qit3@gene.com

Examples 

data <- within(teal_data(), {
  library(nestcolor)
  library(dplyr)
  ADSL <- teal.data::rADSL
  ADAE <- teal.data::rADAE %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
  ADCM <- teal.data::rADCM %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
  # The step below is to pre-process ADCM to legacy standard
  ADCM <- ADCM %>%
    select(-starts_with("ATC")) %>%
    unique()
  ADRS <- teal.data::rADRS %>% mutate(ADT = as.Date(ADTM))
  ADEX <- teal.data::rADEX %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
  ADLB <- teal.data::rADLB %>% mutate(ADT = as.Date(ADTM), LBSTRESN = as.numeric(LBSTRESC))
})

join_keys(data) <- default_cdisc_join_keys[names(data)]

app <- init(
  data = data,
  modules = modules(
    tm_g_patient_profile(
      label = "Patient Profile Plot",
      patient_id = variables(
        choices = "USUBJID",
        selected = "USUBJID"
      ),
      sl_dataname = "ADSL",
      ex_dataname = "ADEX",
      ae_dataname = "ADAE",
      rs_dataname = "ADRS",
      cm_dataname = "ADCM",
      lb_dataname = "ADLB",
      sl_start_date = variables(
        selected = "TRTSDTM",
        choices = c("TRTSDTM", "RANDDT")
      ),
      ex_var = variables(
        selected = "PARCAT2",
        choices = "PARCAT2"
      ),
      ae_var = variables(
        selected = "AEDECOD",
        choices = c("AEDECOD", "AESOC")
      ),
      ae_line_col_var = variables(
        selected = "AESER",
        choices = c("AESER", "AEREL")
      ),
      ae_line_col_opt = c("Y" = "red", "N" = "blue"),
      rs_var = variables(
        selected = "PARAMCD",
        choices = "PARAMCD"
      ),
      cm_var = variables(
        selected = "CMDECOD",
        choices = c("CMDECOD", "CMCAT")
      ),
      lb_var = variables(
        selected = "LBTESTCD",
        choices = c("LBTESTCD", "LBCAT")
      ),
      x_limit = "-28, 750",
      plot_height = c(1200, 400, 5000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}