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  3. RMPT04
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  • Appendix
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  1. Tables
  2. Risk Management Plan
  3. RMPT04

RMPT04

Extent of Exposure by Ethnic Origin for Risk Management Plan


Output

  • Standard Table
  • Data Setup
  • Preview
  • Try this using WebR
Code
lyt <- basic_table(
  title = "Extent of Exposure by Ethnic Origin: Safety-Evaluable Patients",
  main_footer = "* Patient Time is the sum of exposure across all patients in days.",
  show_colcounts = TRUE
) %>%
  analyze_patients_exposure_in_cols(
    var = "ETHNIC",
    col_split = TRUE,
    add_total_level = TRUE,
    custom_label = "Total"
  ) %>%
  append_topleft(c("", "Ethnicity"))

result <- build_table(lyt, df = anl, alt_counts_df = adsl_f)
result
Extent of Exposure by Ethnic Origin: Safety-Evaluable Patients

——————————————————————————————————————————————————
                          Patients     Person time
Ethnicity                  (N=400)       (N=400)  
——————————————————————————————————————————————————
HISPANIC OR LATINO        28 (7.0%)       2423    
NOT HISPANIC OR LATINO   165 (41.2%)      15570   
NOT REPORTED              18 (4.5%)       2085    
UNKNOWN                   6 (1.5%)         563    
Total                    217 (54.2%)      20641   
——————————————————————————————————————————————————

* Patient Time is the sum of exposure across all patients in days.
Experimental use!

WebR is a tool allowing you to run R code in the web browser. Modify the code below and click run to see the results. Alternatively, copy the code and click here to open WebR in a new tab.

Code
library(tern)
library(dplyr)

adsl <- random.cdisc.data::cadsl
adex <- random.cdisc.data::cadex

# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.
adsl <- df_explicit_na(adsl)
adex <- df_explicit_na(adex)

# Simulate ADEX records with PARAMCD == "TDURD" as they are not in sample random.cdisc.data dataset.
set.seed(1, kind = "Mersenne-Twister")
adex2 <- adex %>%
  distinct(USUBJID, .keep_all = TRUE) %>%
  mutate(
    PARAMCD = "TDURD",
    PARAM = "Overall duration (days)",
    AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE)
  ) %>%
  bind_rows(adex)


# Now pre-processing steps are carried out.
anl <- adex2 %>%
  filter(
    PARAMCD == "TDURD",
    PARCAT2 == "Drug A",
    SAFFL == "Y"
  )

adsl_f <- adsl %>% filter(adsl$SAFFL == "Y")

teal App

  • Preview
  • Try this using shinylive
Code
library(teal.modules.clinical)

## Data reproducible code
data <- teal_data()
data <- within(data, {
  library(dplyr)

  ADSL <- random.cdisc.data::cadsl
  ADEX <- random.cdisc.data::cadex

  labels <- col_labels(ADEX)
  set.seed(1, kind = "Mersenne-Twister")

  labels <- col_labels(ADEX)
  ADEX <- ADEX %>%
    distinct(USUBJID, .keep_all = TRUE) %>%
    mutate(
      PARAMCD = "TDURD",
      PARAM = "Overall duration (days)",
      AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE),
      AVALU = "Days"
    ) %>%
    bind_rows(ADEX)

  col_labels(ADEX) <- labels
})
datanames <- c("ADSL", "ADEX")
datanames(data) <- datanames
Warning: `datanames<-()` was deprecated in teal.data 0.7.0.
ℹ invalid to use `datanames()<-` or `names()<-` on an object of class
  `teal_data`. See ?names.teal_data
Code
join_keys(data) <- default_cdisc_join_keys[datanames]

## Reusable Configuration For Modules
ADEX <- data[["ADEX"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_exposure(
      label = "Duration of Exposure Table",
      dataname = "ADEX",
      paramcd = choices_selected(
        choices = value_choices(ADEX, "PARAMCD", "PARAM"),
        selected = "TDURD"
      ),
      col_by_var = choices_selected(
        choices = variable_choices(ADEX, subset = c("ARM")),
        selected = "ARM"
      ),
      row_by_var = choices_selected(
        choices = variable_choices(ADEX, subset = c("ETHNIC", "SEX")),
        selected = "ETHNIC"
      ),
      parcat = choices_selected(
        choices = value_choices(ADEX, "PARCAT2"),
        selected = "Drug A"
      ),
      add_total = FALSE
    )
  ),
  filter = teal_slices(teal_slice("ADSL", "SAFFL", selected = "Y"))
)

shinyApp(app$ui, app$server)

Experimental use!

shinylive allow you to modify to run shiny application entirely in the web browser. Modify the code below and click re-run the app to see the results. The performance is slighly worse and some of the features (e.g. downloading) might not work at all.

#| '!! shinylive warning !!': |
#|   shinylive does not work in self-contained HTML documents.
#|   Please set `embed-resources: false` in your metadata.
#| standalone: true
#| viewerHeight: 800
#| editorHeight: 200
#| components: [viewer, editor]
#| layout: vertical

# -- WEBR HELPERS --
options(webr_pkg_repos = c("r-universe" = "https://insightsengineering.r-universe.dev", getOption("webr_pkg_repos")))

# -- APP CODE --
library(teal.modules.clinical)

## Data reproducible code
data <- teal_data()
data <- within(data, {
  library(dplyr)

  ADSL <- random.cdisc.data::cadsl
  ADEX <- random.cdisc.data::cadex

  labels <- col_labels(ADEX)
  set.seed(1, kind = "Mersenne-Twister")

  labels <- col_labels(ADEX)
  ADEX <- ADEX %>%
    distinct(USUBJID, .keep_all = TRUE) %>%
    mutate(
      PARAMCD = "TDURD",
      PARAM = "Overall duration (days)",
      AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE),
      AVALU = "Days"
    ) %>%
    bind_rows(ADEX)

  col_labels(ADEX) <- labels
})
datanames <- c("ADSL", "ADEX")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]

## Reusable Configuration For Modules
ADEX <- data[["ADEX"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_exposure(
      label = "Duration of Exposure Table",
      dataname = "ADEX",
      paramcd = choices_selected(
        choices = value_choices(ADEX, "PARAMCD", "PARAM"),
        selected = "TDURD"
      ),
      col_by_var = choices_selected(
        choices = variable_choices(ADEX, subset = c("ARM")),
        selected = "ARM"
      ),
      row_by_var = choices_selected(
        choices = variable_choices(ADEX, subset = c("ETHNIC", "SEX")),
        selected = "ETHNIC"
      ),
      parcat = choices_selected(
        choices = value_choices(ADEX, "PARCAT2"),
        selected = "Drug A"
      ),
      add_total = FALSE
    )
  ),
  filter = teal_slices(teal_slice("ADSL", "SAFFL", selected = "Y"))
)

shinyApp(app$ui, app$server)

Reproducibility

Timestamp

[1] "2025-07-05 17:42:41 UTC"

Session Info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.5.0 (2025-04-11)
 os       Ubuntu 24.04.2 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2025-07-05
 pandoc   3.7.0.2 @ /usr/bin/ (via rmarkdown)
 quarto   1.7.32 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 package               * version  date (UTC) lib source
 backports               1.5.0    2024-05-23 [1] RSPM
 brio                    1.1.5    2024-04-24 [1] RSPM
 broom                   1.0.8    2025-03-28 [1] RSPM
 bslib                   0.9.0    2025-01-30 [1] RSPM
 cachem                  1.1.0    2024-05-16 [1] RSPM
 callr                   3.7.6    2024-03-25 [1] RSPM
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 emmeans                 1.11.1   2025-05-04 [1] RSPM
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 farver                  2.1.2    2024-05-13 [1] RSPM
 fastmap                 1.2.0    2024-05-15 [1] RSPM
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 ggplot2                 3.5.2    2025-04-09 [1] RSPM
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 MASS                    7.3-65   2025-02-28 [2] CRAN (R 4.5.0)
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 R6                      2.6.1    2025-02-15 [1] RSPM
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 stringr                 1.5.1    2023-11-14 [1] RSPM
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 teal                  * 0.16.0   2025-02-23 [1] RSPM
 teal.code             * 0.6.1    2025-02-14 [1] RSPM
 teal.data             * 0.7.0    2025-01-28 [1] RSPM
 teal.logger             0.3.2    2025-02-14 [1] RSPM
 teal.modules.clinical * 0.10.0   2025-02-28 [1] RSPM
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 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library
 [3] /github/home/R/x86_64-pc-linux-gnu-library/4.5
 * ── Packages attached to the search path.

──────────────────────────────────────────────────────────────────────────────

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RMPT03
RMPT05
Source Code
---
title: RMPT04
subtitle: Extent of Exposure by Ethnic Origin for Risk Management Plan
---

------------------------------------------------------------------------

{{< include ../../_utils/envir_hook.qmd >}}

```{r setup, echo = FALSE, warning = FALSE, message = FALSE}
library(tern)
library(dplyr)

adsl <- random.cdisc.data::cadsl
adex <- random.cdisc.data::cadex

# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.
adsl <- df_explicit_na(adsl)
adex <- df_explicit_na(adex)

# Simulate ADEX records with PARAMCD == "TDURD" as they are not in sample random.cdisc.data dataset.
set.seed(1, kind = "Mersenne-Twister")
adex2 <- adex %>%
  distinct(USUBJID, .keep_all = TRUE) %>%
  mutate(
    PARAMCD = "TDURD",
    PARAM = "Overall duration (days)",
    AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE)
  ) %>%
  bind_rows(adex)


# Now pre-processing steps are carried out.
anl <- adex2 %>%
  filter(
    PARAMCD == "TDURD",
    PARCAT2 == "Drug A",
    SAFFL == "Y"
  )

adsl_f <- adsl %>% filter(adsl$SAFFL == "Y")
```

```{r include = FALSE}
webr_code_labels <- c("setup")
```

{{< include ../../_utils/webr_no_include.qmd >}}

## Output

:::: panel-tabset
## Standard Table

::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview

```{r variant1, test = list(result_v1 = "result")}
lyt <- basic_table(
  title = "Extent of Exposure by Ethnic Origin: Safety-Evaluable Patients",
  main_footer = "* Patient Time is the sum of exposure across all patients in days.",
  show_colcounts = TRUE
) %>%
  analyze_patients_exposure_in_cols(
    var = "ETHNIC",
    col_split = TRUE,
    add_total_level = TRUE,
    custom_label = "Total"
  ) %>%
  append_topleft(c("", "Ethnicity"))

result <- build_table(lyt, df = anl, alt_counts_df = adsl_f)
result
```

```{r include = FALSE}
webr_code_labels <- c("variant1")
```

{{< include ../../_utils/webr.qmd >}}
:::

## Data Setup

```{r setup}
#| code-fold: show
```
::::

{{< include ../../_utils/save_results.qmd >}}

## `teal` App

::: {.panel-tabset .nav-justified}
## {{< fa regular file-lines fa-sm fa-fw >}} Preview

```{r teal, opts.label = c("skip_if_testing", "app")}
library(teal.modules.clinical)

## Data reproducible code
data <- teal_data()
data <- within(data, {
  library(dplyr)

  ADSL <- random.cdisc.data::cadsl
  ADEX <- random.cdisc.data::cadex

  labels <- col_labels(ADEX)
  set.seed(1, kind = "Mersenne-Twister")

  labels <- col_labels(ADEX)
  ADEX <- ADEX %>%
    distinct(USUBJID, .keep_all = TRUE) %>%
    mutate(
      PARAMCD = "TDURD",
      PARAM = "Overall duration (days)",
      AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE),
      AVALU = "Days"
    ) %>%
    bind_rows(ADEX)

  col_labels(ADEX) <- labels
})
datanames <- c("ADSL", "ADEX")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]

## Reusable Configuration For Modules
ADEX <- data[["ADEX"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_exposure(
      label = "Duration of Exposure Table",
      dataname = "ADEX",
      paramcd = choices_selected(
        choices = value_choices(ADEX, "PARAMCD", "PARAM"),
        selected = "TDURD"
      ),
      col_by_var = choices_selected(
        choices = variable_choices(ADEX, subset = c("ARM")),
        selected = "ARM"
      ),
      row_by_var = choices_selected(
        choices = variable_choices(ADEX, subset = c("ETHNIC", "SEX")),
        selected = "ETHNIC"
      ),
      parcat = choices_selected(
        choices = value_choices(ADEX, "PARCAT2"),
        selected = "Drug A"
      ),
      add_total = FALSE
    )
  ),
  filter = teal_slices(teal_slice("ADSL", "SAFFL", selected = "Y"))
)

shinyApp(app$ui, app$server)
```

{{< include ../../_utils/shinylive.qmd >}}
:::

{{< include ../../repro.qmd >}}

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