TLG Catalog - Stable
  • Stable
    • Dev
  1. Tables
  2. Risk Management Plan
  3. RMPT01
  • Introduction

  • Tables
    • ADA
      • ADAT01
      • ADAT02
      • ADAT03
      • ADAT04A
      • ADAT04B
    • Adverse Events
      • AET01
      • AET01_AESI
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      • AET02_SMQ
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      • AET04_PI
      • AET05
      • AET05_ALL
      • AET06
      • AET06_SMQ
      • AET07
      • AET09
      • AET09_SMQ
      • AET10
    • Concomitant Medications
      • CMT01
      • CMT01A
      • CMT01B
      • CMT02_PT
    • Deaths
      • DTHT01
    • Demography
      • DMT01
    • Disclosures
      • DISCLOSUREST01
      • EUDRAT01
      • EUDRAT02
    • Disposition
      • DST01
      • PDT01
      • PDT02
    • ECG
      • EGT01
      • EGT02
      • EGT03
      • EGT04
      • EGT05_QTCAT
    • Efficacy
      • AOVT01
      • AOVT02
      • AOVT03
      • CFBT01
      • CMHT01
      • COXT01
      • COXT02
      • DORT01
      • LGRT02
      • MMRMT01
      • ONCT05
      • RATET01
      • RBMIT01
      • RSPT01
      • TTET01
    • Exposure
      • EXT01
    • Lab Results
      • LBT01
      • LBT02
      • LBT03
      • LBT04
      • LBT05
      • LBT06
      • LBT07
      • LBT08
      • LBT09
      • LBT10
      • LBT10_BL
      • LBT11
      • LBT11_BL
      • LBT12
      • LBT12_BL
      • LBT13
      • LBT14
      • LBT15
    • Medical History
      • MHT01
    • Pharmacokinetic
      • PKCT01
      • PKPT02
      • PKPT03
      • PKPT04
      • PKPT05
      • PKPT06
      • PKPT07
      • PKPT08
      • PKPT11
    • Risk Management Plan
      • RMPT01
      • RMPT03
      • RMPT04
      • RMPT05
      • RMPT06
    • Safety
      • ENTXX
    • Vital Signs
      • VST01
      • VST02
  • Listings
    • ADA
      • ADAL02
    • Adverse Events
      • AEL01
      • AEL01_NOLLT
      • AEL02
      • AEL02_ED
      • AEL03
      • AEL04
    • Concomitant Medications
      • CML01
      • CML02A_GL
      • CML02B_GL
    • Development Safety Update Report
      • DSUR4
    • Disposition
      • DSL01
      • DSL02
    • ECG
      • EGL01
    • Efficacy
      • ONCL01
    • Exposure
      • EXL01
    • Lab Results
      • LBL01
      • LBL01_RLS
      • LBL02A
      • LBL02A_RLS
      • LBL02B
    • Medical History
      • MHL01
    • Pharmacokinetic
      • ADAL01
      • PKCL01
      • PKCL02
      • PKPL01
      • PKPL02
      • PKPL04
    • Vital Signs
      • VSL01
  • Graphs
    • Efficacy
      • FSTG01
      • FSTG02
      • KMG01
      • MMRMG01
      • MMRMG02
    • Other
      • BRG01
      • BWG01
      • CIG01
      • IPPG01
      • LTG01
      • MNG01
    • Pharmacokinetic
      • PKCG01
      • PKCG02
      • PKCG03
      • PKPG01
      • PKPG02
      • PKPG03
      • PKPG04
      • PKPG06

  • Appendix
    • Reproducibility

  • Index

On this page

  • Output
  • teal App
  • Reproducibility
    • Timestamp
    • Session Info
    • .lock file
  • Edit this page
  • Report an issue
  1. Tables
  2. Risk Management Plan
  3. RMPT01

RMPT01

Duration of Exposure for Risk Management Plan


Output

  • Standard Table
  • Data Setup
  • Preview
  • Try this using WebR
Code
lyt <- basic_table(
  title = "Duration of Exposure: Safety-Evaluable Patients",
  main_footer = "* Patient Time is the sum of exposure across all patients in days.",
  show_colcounts = TRUE
) %>%
  summarize_patients_exposure_in_cols(
    var = "AVAL", col_split = TRUE,
    .labels = c(n_patients = "Number of Patients", sum_exposure = "Patient Time*"),
    custom_label = "Total Number of Patients and Patient Time"
  ) %>%
  analyze_patients_exposure_in_cols(
    var = "aval_months_cat",
    col_split = FALSE
  ) %>%
  append_topleft(c("", "Duration of exposure"))

result <- build_table(lyt, df = anl, alt_counts_df = adsl_f)
result
Duration of Exposure: Safety-Evaluable Patients

——————————————————————————————————————————————————————————————————————————————
                                            Number of Patients   Patient Time*
Duration of exposure                             (N=400)            (N=400)   
——————————————————————————————————————————————————————————————————————————————
Total Number of Patients and Patient Time      217 (54.2%)           20641    
  < 1 month                                     28 (7.0%)             504     
  1 to <3 months                                79 (19.8%)           4727     
  3 to <6 months                               101 (25.2%)           13690    
  >=6 months                                     9 (2.2%)            1720     
——————————————————————————————————————————————————————————————————————————————

* Patient Time is the sum of exposure across all patients in days.
WarningExperimental 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"
  ) %>%
  mutate(
    aval_months = day2month(AVAL),
    aval_months_cat = factor(case_when(
      aval_months < 1 ~ "< 1 month",
      aval_months >= 1 & aval_months < 3 ~ "1 to <3 months",
      aval_months >= 3 & aval_months < 6 ~ "3 to <6 months",
      TRUE ~ ">=6 months"
    ), levels = c("< 1 month", "1 to <3 months", "3 to <6 months", ">=6 months"))
  )

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")
  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)

  ADEX <- ADEX %>%
    mutate(
      aval_months = day2month(AVAL),
      aval_months_cat = factor(case_when(
        aval_months < 1 ~ "< 1 month",
        aval_months >= 1 & aval_months < 3 ~ "1 to <3 months",
        aval_months >= 3 & aval_months < 6 ~ "3 to <6 months",
        TRUE ~ ">=6 months"
      ), levels = c("< 1 month", "1 to <3 months", "3 to <6 months", ">=6 months")) %>% with_label("Overall duration")
    ) %>%
    select(-aval_months)
})
datanames <- c("ADSL", "ADEX")
names(data) <- datanames
Warning: `names<-.teal_data()` 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("aval_months_cat", "RACE", "STRATA1", "SEX")),
        selected = "aval_months_cat"
      ),
      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)

WarningExperimental 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")
  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)

  ADEX <- ADEX %>%
    mutate(
      aval_months = day2month(AVAL),
      aval_months_cat = factor(case_when(
        aval_months < 1 ~ "< 1 month",
        aval_months >= 1 & aval_months < 3 ~ "1 to <3 months",
        aval_months >= 3 & aval_months < 6 ~ "3 to <6 months",
        TRUE ~ ">=6 months"
      ), levels = c("< 1 month", "1 to <3 months", "3 to <6 months", ">=6 months")) %>% with_label("Overall duration")
    ) %>%
    select(-aval_months)
})
datanames <- c("ADSL", "ADEX")
names(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("aval_months_cat", "RACE", "STRATA1", "SEX")),
        selected = "aval_months_cat"
      ),
      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] "2025-12-06 17:29:49 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     2025-12-06
 pandoc   3.7.0.2 @ /usr/bin/ (via rmarkdown)
 quarto   1.8.26 @ /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                   1.0.11  2025-12-04 [1] RSPM
 bsicons                 0.1.2   2023-11-04 [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
 checkmate               2.3.3   2025-08-18 [1] RSPM
 chromote                0.5.1   2025-04-24 [1] RSPM
 cli                     3.6.5   2025-04-23 [1] RSPM
 codetools               0.2-20  2024-03-31 [2] CRAN (R 4.5.0)
 curl                    7.0.0   2025-08-19 [1] RSPM
 dichromat               2.0-0.1 2022-05-02 [1] CRAN (R 4.5.0)
 digest                  0.6.39  2025-11-19 [1] RSPM
 dplyr                 * 1.1.4   2023-11-17 [1] RSPM
 evaluate                1.0.5   2025-08-27 [1] RSPM
 farver                  2.1.2   2024-05-13 [1] RSPM
 fastmap                 1.2.0   2024-05-15 [1] RSPM
 fontawesome             0.5.3   2024-11-16 [1] RSPM
 forcats                 1.0.1   2025-09-25 [1] RSPM
 formatR                 1.14    2023-01-17 [1] CRAN (R 4.5.0)
 formatters            * 0.5.11  2025-04-09 [1] RSPM
 fs                      1.6.6   2025-04-12 [1] RSPM
 generics                0.1.4   2025-05-09 [1] RSPM
 ggplot2                 4.0.1   2025-11-14 [1] RSPM
 glue                    1.8.0   2024-09-30 [1] RSPM
 gtable                  0.3.6   2024-10-25 [1] RSPM
 htmltools               0.5.9   2025-12-04 [1] RSPM
 htmlwidgets             1.6.4   2023-12-06 [1] RSPM
 httpuv                  1.6.16  2025-04-16 [1] RSPM
 jquerylib               0.1.4   2021-04-26 [1] RSPM
 jsonlite                2.0.0   2025-03-27 [1] RSPM
 knitr                   1.50    2025-03-16 [1] RSPM
 later                   1.4.4   2025-08-27 [1] RSPM
 lattice                 0.22-7  2025-04-02 [2] CRAN (R 4.5.0)
 lifecycle               1.0.4   2023-11-07 [1] RSPM
 logger                  0.4.1   2025-09-11 [1] RSPM
 magrittr              * 2.0.4   2025-09-12 [1] RSPM
 Matrix                  1.7-4   2025-08-28 [1] RSPM
 memoise                 2.0.1   2021-11-26 [1] RSPM
 mime                    0.13    2025-03-17 [1] RSPM
 nestcolor               0.1.3   2025-01-21 [1] RSPM
 otel                    0.2.0   2025-08-29 [1] RSPM
 pillar                  1.11.1  2025-09-17 [1] RSPM
 pkgcache                2.2.4   2025-05-26 [1] RSPM
 pkgconfig               2.0.3   2019-09-22 [1] RSPM
 processx                3.8.6   2025-02-21 [1] RSPM
 promises                1.5.0   2025-11-01 [1] RSPM
 ps                      1.9.1   2025-04-12 [1] RSPM
 purrr                   1.2.0   2025-11-04 [1] RSPM
 R6                      2.6.1   2025-02-15 [1] RSPM
 ragg                    1.5.0   2025-09-02 [1] RSPM
 random.cdisc.data       0.3.16  2024-10-10 [1] RSPM
 rbibutils               2.4     2025-11-07 [1] RSPM
 RColorBrewer            1.1-3   2022-04-03 [1] RSPM
 Rcpp                    1.1.0   2025-07-02 [1] RSPM
 Rdpack                  2.6.4   2025-04-09 [1] RSPM
 rlang                   1.1.6   2025-04-11 [1] RSPM
 rmarkdown               2.30    2025-09-28 [1] RSPM
 rtables               * 0.6.14  2025-11-18 [1] RSPM
 S7                      0.2.1   2025-11-14 [1] RSPM
 sass                    0.4.10  2025-04-11 [1] RSPM
 scales                  1.4.0   2025-04-24 [1] RSPM
 sessioninfo             1.2.3   2025-02-05 [1] any (@1.2.3)
 shiny                 * 1.12.0  2025-12-03 [1] RSPM
 shinycssloaders         1.1.0   2024-07-30 [1] RSPM
 shinyjs                 2.1.0   2021-12-23 [1] RSPM
 shinyvalidate           0.1.3   2023-10-04 [1] RSPM
 shinyWidgets            0.9.0   2025-02-21 [1] RSPM
 stringi                 1.8.7   2025-03-27 [1] RSPM
 stringr                 1.6.0   2025-11-04 [1] RSPM
 survival                3.8-3   2024-12-17 [2] CRAN (R 4.5.0)
 systemfonts             1.3.1   2025-10-01 [1] RSPM
 teal                  * 1.1.0   2025-11-17 [1] RSPM
 teal.code             * 0.7.0   2025-08-19 [1] RSPM
 teal.data             * 0.8.0   2025-08-19 [1] RSPM
 teal.logger             0.4.1   2025-12-02 [1] RSPM
 teal.modules.clinical * 0.12.0  2025-12-04 [1] RSPM
 teal.reporter           0.6.0   2025-11-15 [1] RSPM
 teal.slice            * 0.7.1   2025-12-02 [1] RSPM
 teal.transform        * 0.7.1   2025-12-03 [1] RSPM
 teal.widgets            0.5.1   2025-12-02 [1] RSPM
 tern                  * 0.9.9   2025-06-20 [1] RSPM
 testthat                3.3.1   2025-11-25 [1] RSPM
 textshaping             1.0.4   2025-10-10 [1] RSPM
 tibble                  3.3.0   2025-06-08 [1] RSPM
 tidyr                   1.3.1   2024-01-24 [1] RSPM
 tidyselect              1.2.1   2024-03-11 [1] RSPM
 vctrs                   0.6.5   2023-12-01 [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.

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

.lock file

Download the .lock file and use renv::restore() on it to recreate environment used to generate this website.

Download

PKPT11
RMPT03
Source Code
---
title: RMPT01
subtitle: Duration of Exposure 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"
  ) %>%
  mutate(
    aval_months = day2month(AVAL),
    aval_months_cat = factor(case_when(
      aval_months < 1 ~ "< 1 month",
      aval_months >= 1 & aval_months < 3 ~ "1 to <3 months",
      aval_months >= 3 & aval_months < 6 ~ "3 to <6 months",
      TRUE ~ ">=6 months"
    ), levels = c("< 1 month", "1 to <3 months", "3 to <6 months", ">=6 months"))
  )

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 = "Duration of Exposure: Safety-Evaluable Patients",
  main_footer = "* Patient Time is the sum of exposure across all patients in days.",
  show_colcounts = TRUE
) %>%
  summarize_patients_exposure_in_cols(
    var = "AVAL", col_split = TRUE,
    .labels = c(n_patients = "Number of Patients", sum_exposure = "Patient Time*"),
    custom_label = "Total Number of Patients and Patient Time"
  ) %>%
  analyze_patients_exposure_in_cols(
    var = "aval_months_cat",
    col_split = FALSE
  ) %>%
  append_topleft(c("", "Duration of exposure"))

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")
  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)

  ADEX <- ADEX %>%
    mutate(
      aval_months = day2month(AVAL),
      aval_months_cat = factor(case_when(
        aval_months < 1 ~ "< 1 month",
        aval_months >= 1 & aval_months < 3 ~ "1 to <3 months",
        aval_months >= 3 & aval_months < 6 ~ "3 to <6 months",
        TRUE ~ ">=6 months"
      ), levels = c("< 1 month", "1 to <3 months", "3 to <6 months", ">=6 months")) %>% with_label("Overall duration")
    ) %>%
    select(-aval_months)
})
datanames <- c("ADSL", "ADEX")
names(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("aval_months_cat", "RACE", "STRATA1", "SEX")),
        selected = "aval_months_cat"
      ),
      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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