Patient Profile plot teal module — tm_g_patient

Display patient profile plot as a shiny module

Usage

tm_g_patient_profile(
  label = "Patient Profile Plot",
  patient_id,
  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
)

Arguments

label: (character(1))
menu item label of the module in the teal app.
patient_id: (choices_seleced) unique subject ID variable
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: choices_selected study start date variable, usually set to treatment start date or randomization date
ex_var: choices_selected exposure variable to plot as each line
leave unspecified or set to NULL if exposure data is not available
ae_var: choices_selected 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: choices_selected variable 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: choices_selected response variable to plot as each line
leave unspecified or set to NULL if response data is not available
cm_var: choices_selected concomitant medication variable to plot as each line
leave unspecified or set to NULL if concomitant medications data is not available
lb_var: choices_selected 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.

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

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 <- teal_data() |>
  within({
    ADSL <- rADSL
    ADAE <- rADAE %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
    ADCM <- 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 <- rADRS %>% mutate(ADT = as.Date(ADTM))
    ADEX <- rADEX %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
    ADLB <- rADLB %>% mutate(ADT = as.Date(ADTM), LBSTRESN = as.numeric(LBSTRESC))
  })

datanames(data) <- c("ADSL", "ADAE", "ADCM", "ADRS", "ADEX", "ADLB")
join_keys(data) <- default_cdisc_join_keys[datanames(data)]

ADSL <- data[["ADSL"]]

app <- init(
  data = data,
  modules = modules(
    tm_g_patient_profile(
      label = "Patient Profile Plot",
      patient_id = choices_selected(
        choices = unique(ADSL$USUBJID),
        selected = unique(ADSL$USUBJID)[1]
      ),
      sl_dataname = "ADSL",
      ex_dataname = "ADEX",
      ae_dataname = "ADAE",
      rs_dataname = "ADRS",
      cm_dataname = "ADCM",
      lb_dataname = "ADLB",
      sl_start_date = choices_selected(
        selected = "TRTSDTM",
        choices = c("TRTSDTM", "RANDDT")
      ),
      ex_var = choices_selected(
        selected = "PARCAT2",
        choices = "PARCAT2"
      ),
      ae_var = choices_selected(
        selected = "AEDECOD",
        choices = c("AEDECOD", "AESOC")
      ),
      ae_line_col_var = choices_selected(
        selected = "AESER",
        choices = c("AESER", "AEREL")
      ),
      ae_line_col_opt = c("Y" = "red", "N" = "blue"),
      rs_var = choices_selected(
        selected = "PARAMCD",
        choices = "PARAMCD"
      ),
      cm_var = choices_selected(
        selected = "CMDECOD",
        choices = c("CMDECOD", "CMCAT")
      ),
      lb_var = choices_selected(
        selected = "LBTESTCD",
        choices = c("LBTESTCD", "LBCAT")
      ),
      x_limit = "-28, 750",
      plot_height = c(1200, 400, 5000)
    )
  )
)
#> Initializing reporter_previewer_module
if (interactive()) {
  shinyApp(app$ui, app$server)
}