TLG Catalog - Stable
  • Stable
    • Dev
  1. Tables
  2. Disclosures
  3. EUDRAT01
  • Introduction

  • Tables
    • ADA
      • ADAT01
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      • LBT01
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      • LBT10_BL
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      • LBT11_BL
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      • LBT12_BL
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    • Safety
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  • Listings
    • ADA
      • ADAL02
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      • AEL03
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    • Concomitant Medications
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    • Development Safety Update Report
      • DSUR4
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      • DSL02
    • ECG
      • EGL01
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      • ONCL01
    • Exposure
      • EXL01
    • Lab Results
      • LBL01
      • LBL01_RLS
      • LBL02A
      • LBL02A_RLS
      • LBL02B
    • Medical History
      • MHL01
    • Pharmacokinetic
      • ADAL01
      • PKCL01
      • PKCL02
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      • PKPL04
    • Vital Signs
      • VSL01
  • Graphs
    • Efficacy
      • FSTG01
      • FSTG02
      • KMG01
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    • Other
      • BRG01
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    • Pharmacokinetic
      • PKCG01
      • PKCG02
      • PKCG03
      • PKPG01
      • PKPG02
      • PKPG03
      • PKPG04
      • PKPG06

  • Appendix
    • Reproducibility

  • Index

On this page

  • Output
  • Reproducibility
    • Timestamp
    • Session Info
    • .lock file
  • Edit this page
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  1. Tables
  2. Disclosures
  3. EUDRAT01

EUDRAT01

Non-Serious Adverse Events Reported in \(\geq\) 5% of Patients in Any Treatment Group – Patients and Events


Output

  • Standard Table
  • Data Setup
  • Preview
  • Try this using WebR
Code
# Define the split function
split_fun <- drop_split_levels

lyt <- basic_table() %>%
  split_cols_by("ARM") %>%
  summarize_patients_events_in_cols(
    custom_label = "Total number of patients with at least one non-serious adverse event occuring at a relative frequency of >=5% and number of events" 
  ) %>%
  split_rows_by("AEBODSYS",
    nested = FALSE,
    split_fun = split_fun,
    indent_mod = -1L,
    label_pos = "topleft",
    split_label = obj_label(adae_trim$AEBODSYS)
  ) %>%
  split_rows_by("AEDECOD", split_fun = split_fun, label_pos = "topleft", split_label = obj_label(adae_trim$AEDECOD)) %>%
  summarize_patients_events_in_cols(
    col_split = FALSE
  )

result <- build_table(lyt, adae_trim)
result
Body System or Organ Class                                                                                                                     A: Drug X                      B: Placebo                    C: Combination        
  Dictionary-Derived Term                                                                                                            Patients (All)   Events (All)   Patients (All)   Events (All)   Patients (All)   Events (All)
——————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
Total number of patients with at least one non-serious adverse event occuring at a relative frequency of >=5% and number of events        106             360             112             367             112             421     
cl A.1                                                                                                                                                                                                                            
  dcd A.1.1.1.1                                                                                                                            50              64              45              62              63              88     
cl B.2                                                                                                                                                                                                                            
  dcd B.2.1.2.1                                                                                                                            49              65              44              62              52              66     
cl C.1                                                                                                                                                                                                                            
  dcd C.1.1.1.3                                                                                                                            43              55              46              63              43              64     
cl C.2                                                                                                                                                                                                                            
  dcd C.2.1.2.1                                                                                                                            35              48              48              53              55              65     
cl D.1                                                                                                                                                                                                                            
  dcd D.1.1.4.2                                                                                                                            48              66              42              55              50              64     
cl D.2                                                                                                                                                                                                                            
  dcd D.2.1.5.3                                                                                                                            47              62              58              72              57              74     
Experimental use!

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Define a trimming function get_adae_trimmed to filter for AEs of greater than 5% incidence rate.

Code
library(tern)
library(dplyr)

adsl <- random.cdisc.data::cadsl
adae <- random.cdisc.data::cadae

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

adae_nonser <- adae %>% filter(AESER != "Y", SAFFL == "Y")

get_adae_trimmed <- function(adsl, adae, cutoff_rate) {
  n_per_arm <- adsl %>%
    dplyr::count(ARM)

  anl_terms <- adae %>%
    dplyr::group_by(ARM, AEBODSYS, AEDECOD) %>%
    dplyr::count(
      unique_terms = n_distinct(USUBJID)
    ) %>%
    dplyr::select(-n) %>%
    dplyr::ungroup()

  anl_terms <- dplyr::left_join(
    anl_terms,
    n_per_arm,
    by = "ARM"
  ) %>%
    dplyr::mutate(
      ae_rate = unique_terms / n
    ) %>%
    dplyr::filter(ae_rate >= cutoff_rate) %>%
    dplyr::select(AEDECOD) %>%
    unique()

  anl <- dplyr::left_join(
    anl_terms,
    adae,
    by = "AEDECOD"
  )
  anl
}

adae_trim <- get_adae_trimmed(adsl, adae_nonser, cutoff_rate = 0.05)

Reproducibility

Timestamp

[1] "2025-07-05 17:33:43 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
 checkmate           2.3.2   2024-07-29 [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                6.4.0   2025-06-22 [1] RSPM
 dichromat           2.0-0.1 2022-05-02 [1] CRAN (R 4.5.0)
 digest              0.6.37  2024-08-19 [1] RSPM
 dplyr             * 1.1.4   2023-11-17 [1] RSPM
 evaluate            1.0.4   2025-06-18 [1] RSPM
 farver              2.1.2   2024-05-13 [1] RSPM
 fastmap             1.2.0   2024-05-15 [1] RSPM
 forcats             1.0.0   2023-01-29 [1] RSPM
 formatters        * 0.5.11  2025-04-09 [1] RSPM
 generics            0.1.4   2025-05-09 [1] RSPM
 ggplot2             3.5.2   2025-04-09 [1] RSPM
 glue                1.8.0   2024-09-30 [1] RSPM
 gtable              0.3.6   2024-10-25 [1] RSPM
 htmltools           0.5.8.1 2024-04-04 [1] RSPM
 htmlwidgets         1.6.4   2023-12-06 [1] RSPM
 jsonlite            2.0.0   2025-03-27 [1] RSPM
 knitr               1.50    2025-03-16 [1] RSPM
 lattice             0.22-7  2025-04-02 [2] CRAN (R 4.5.0)
 lifecycle           1.0.4   2023-11-07 [1] RSPM
 magrittr          * 2.0.3   2022-03-30 [1] RSPM
 Matrix              1.7-3   2025-03-11 [1] CRAN (R 4.5.0)
 nestcolor           0.1.3   2025-01-21 [1] RSPM
 pillar              1.11.0  2025-07-04 [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
 ps                  1.9.1   2025-04-12 [1] RSPM
 purrr               1.0.4   2025-02-05 [1] RSPM
 R6                  2.6.1   2025-02-15 [1] RSPM
 random.cdisc.data   0.3.16  2024-10-10 [1] RSPM
 rbibutils           2.3     2024-10-04 [1] RSPM
 RColorBrewer        1.1-3   2022-04-03 [1] RSPM
 Rdpack              2.6.4   2025-04-09 [1] RSPM
 rlang               1.1.6   2025-04-11 [1] RSPM
 rmarkdown           2.29    2024-11-04 [1] RSPM
 rtables           * 0.6.13  2025-06-19 [1] RSPM
 scales              1.4.0   2025-04-24 [1] RSPM
 sessioninfo         1.2.3   2025-02-05 [1] any (@1.2.3)
 stringi             1.8.7   2025-03-27 [1] RSPM
 stringr             1.5.1   2023-11-14 [1] RSPM
 survival            3.8-3   2024-12-17 [2] CRAN (R 4.5.0)
 tern              * 0.9.9   2025-06-20 [1] RSPM
 testthat            3.2.3   2025-01-13 [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
 withr               3.0.2   2024-10-28 [1] RSPM
 xfun                0.52    2025-04-02 [1] RSPM
 yaml                2.3.10  2024-07-26 [1] RSPM

 [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.

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DISCLOSUREST01
EUDRAT02
Source Code
---
title: EUDRAT01
subtitle: Non-Serious Adverse Events Reported in $\geq$ 5% of Patients in Any Treatment Group -- Patients and Events
---

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

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

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

adsl <- random.cdisc.data::cadsl
adae <- random.cdisc.data::cadae

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

adae_nonser <- adae %>% filter(AESER != "Y", SAFFL == "Y")

get_adae_trimmed <- function(adsl, adae, cutoff_rate) {
  n_per_arm <- adsl %>%
    dplyr::count(ARM)

  anl_terms <- adae %>%
    dplyr::group_by(ARM, AEBODSYS, AEDECOD) %>%
    dplyr::count(
      unique_terms = n_distinct(USUBJID)
    ) %>%
    dplyr::select(-n) %>%
    dplyr::ungroup()

  anl_terms <- dplyr::left_join(
    anl_terms,
    n_per_arm,
    by = "ARM"
  ) %>%
    dplyr::mutate(
      ae_rate = unique_terms / n
    ) %>%
    dplyr::filter(ae_rate >= cutoff_rate) %>%
    dplyr::select(AEDECOD) %>%
    unique()

  anl <- dplyr::left_join(
    anl_terms,
    adae,
    by = "AEDECOD"
  )
  anl
}

adae_trim <- get_adae_trimmed(adsl, adae_nonser, cutoff_rate = 0.05)
```

```{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")}
# Define the split function
split_fun <- drop_split_levels

lyt <- basic_table() %>%
  split_cols_by("ARM") %>%
  summarize_patients_events_in_cols(
    custom_label = "Total number of patients with at least one non-serious adverse event occuring at a relative frequency of >=5% and number of events" # nolint: line_length.
  ) %>%
  split_rows_by("AEBODSYS",
    nested = FALSE,
    split_fun = split_fun,
    indent_mod = -1L,
    label_pos = "topleft",
    split_label = obj_label(adae_trim$AEBODSYS)
  ) %>%
  split_rows_by("AEDECOD", split_fun = split_fun, label_pos = "topleft", split_label = obj_label(adae_trim$AEDECOD)) %>%
  summarize_patients_events_in_cols(
    col_split = FALSE
  )

result <- build_table(lyt, adae_trim)
result
```

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

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

## Data Setup

Define a trimming function `get_adae_trimmed` to filter for AEs of greater than 5% incidence rate.

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

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

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

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