---
title: AET07
subtitle: Adverse Events Resulting in Death
---
------------------------------------------------------------------------
{{< include ../../_utils/envir_hook.qmd >}}
```{r setup, echo = FALSE, warning = FALSE, message = FALSE}
library(dplyr)
library(tern)
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_f <- adae %>%
mutate(
AESDTH = as.character(AESDTH), # characterizing AESDTH for next step
AESDTH = case_when(
ARM == "A: Drug X" ~ NA_character_, # For demonstration purpose only,
TRUE ~ AESDTH
), # make "A: Drug X" as the arm without AE leading to death
AESDTH = as.factor(AESDTH),
SOC_PT = factor(paste(AEBODSYS, "/", AEDECOD))
) %>%
filter(AESDTH == "Y") %>%
mutate(ARM = droplevels(ARM))
```
```{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(show_colcounts = TRUE) %>%
split_cols_by("ACTARM", split_fun = drop_split_levels) %>%
analyze_num_patients(
vars = "USUBJID",
.stats = "unique",
.labels = c(unique = "Total number of deaths"),
show_labels = "hidden"
) %>%
count_occurrences(
vars = "SOC_PT"
) %>%
append_topleft("MedDRA SOC and Preferred Term")
result <- build_table(
lyt = lyt,
df = adae_f,
alt_counts_df = adsl
) %>%
prune_table() %>%
sort_at_path(
path = "SOC_PT",
scorefun = score_occurrences,
decreasing = TRUE
)
result
```
```{r include = FALSE}
webr_code_labels <- c("variant1")
```
{{< include ../../_utils/webr.qmd >}}
:::
## Table with Fill-In of Treatment Groups without Deaths
::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview
```{r variant2, test = list(result_v2 = "result")}
lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by("ACTARM") %>%
analyze_num_patients(
vars = "USUBJID",
.stats = "unique",
.labels = c(unique = "Total number of deaths"),
show_labels = "hidden"
) %>%
count_occurrences(
vars = "SOC_PT"
) %>%
append_topleft("MedDRA SOC and Preferred Term")
result <- build_table(
lyt = lyt,
df = adae_f,
alt_counts_df = adsl
) %>%
prune_table() %>%
sort_at_path(
path = "SOC_PT",
scorefun = score_occurrences,
decreasing = TRUE
)
result
```
```{r include = FALSE}
webr_code_labels <- c("variant2")
```
{{< include ../../_utils/webr.qmd >}}
:::
## Data Setup
For illustrative purposes, we will pre-process `AESDTH` in ADAE so there are no deaths in arm A and concatenate `AEBODSYS` and `AEDECOD` as per GDSR output standards for AET07.
```{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
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)
ADSL <- ADSL %>%
mutate(
DTHFL = case_when(
!is.na(DTHDT) ~ "Y",
TRUE ~ ""
)
) %>%
col_relabel(
DTHFL = "Subject Death Flag"
)
ADAE <- ADAE %>%
mutate(
AESDTH = as.character(AESDTH), # characterizing AESDTH for next step
AESDTH = case_when(
ARM == "A: Drug X" ~ NA_character_, # For demonstration purpose only,
TRUE ~ AESDTH
), # make "A: Drug X" as the arm without AE leading to death
AESDTH = as.factor(AESDTH),
SOC_PT = factor(paste(AEBODSYS, "/", AEDECOD))
) %>%
filter(AESDTH == "Y") %>%
mutate(ARM = droplevels(ARM)) %>%
col_relabel(SOC_PT = "MedDRA SOC and Preferred Term")
})
datanames <- c("ADSL", "ADAE")
names(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]
## Reusable Configuration For Modules
ADAE <- data[["ADAE"]]
## Setup App
app <- init(
data = data,
modules = modules(
tm_t_events(
label = "Adverse Event Table",
dataname = "ADAE",
arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
llt = choices_selected(
choices = variable_choices(ADAE, c("AETERM", "AEDECOD", "SOC_PT")),
selected = c("SOC_PT")
),
hlt = choices_selected(
choices = variable_choices(ADAE, c("AETERM", "AEDECOD", "SOC_PT")),
selected = NULL
),
add_total = FALSE,
event_type = "adverse event"
)
)
)
shinyApp(app$ui, app$server)
```
{{< include ../../_utils/shinylive.qmd >}}
:::
{{< include ../../repro.qmd >}}
