AEs Leading to Study Drug Discontinuation

Treatment-Emergent AEs Leading to Discontinuation by SOC and PT

Setup

See Prerequisites for installation instructions.

library(arframe)
library(pharmaverseadam)
library(dplyr, warn.conflicts = FALSE)
library(tidyr)
library(cards)

adsl_saf <- pharmaverseadam::adsl |>
  blank_to_na() |>
  filter(SAFFL == "Y", TRT01A != "Screen Failure")

# AEs where outcome was fatal or serious — proxy for discontinuation
# pharmaverseadam AEACN is all NA, so we use AESER as proxy
adae_disc <- pharmaverseadam::adae |>
  blank_to_na() |>
  filter(SAFFL == "Y", TRTEMFL == "Y", AESER == "Y")

arm_levels <- c("Placebo", "Xanomeline Low Dose", "Xanomeline High Dose")
arm_n <- adsl_saf |>
  filter(TRT01A %in% arm_levels) |>
  count(TRT01A) |>
  pull(n, name = TRT01A)
arm_n <- arm_n[arm_levels]
N_total <- nrow(adsl_saf)
n_vec <- c(arm_n, Total = N_total)

Data Preparation

n_pct <- function(n, denom) sprintf("%d (%.1f)", n, n / denom * 100)

# ── Overall row ──
any_disc_arm <- adae_disc |>
  distinct(USUBJID, TRT01A) |>
  count(TRT01A) |>
  filter(TRT01A %in% arm_levels) |>
  mutate(value = mapply(n_pct, n, arm_n[TRT01A])) |>
  select(TRT01A, value) |>
  pivot_wider(names_from = TRT01A, values_from = value)

any_disc_total <- n_distinct(adae_disc$USUBJID)

any_disc_row <- bind_cols(
  tibble(soc = "PATIENTS WITH AT LEAST ONE AE LEADING TO DISCONTINUATION",
         pt = "PATIENTS WITH AT LEAST ONE AE LEADING TO DISCONTINUATION",
         row_type = "overall"),
  any_disc_arm,
  tibble(Total = n_pct(any_disc_total, N_total))
)

# ── SOC-level ──
soc_arm <- adae_disc |>
  distinct(USUBJID, TRT01A, AEBODSYS) |>
  count(TRT01A, AEBODSYS) |>
  filter(TRT01A %in% arm_levels) |>
  mutate(value = mapply(n_pct, n, arm_n[TRT01A])) |>
  select(TRT01A, AEBODSYS, value) |>
  pivot_wider(names_from = TRT01A, values_from = value)

soc_total <- adae_disc |>
  distinct(USUBJID, AEBODSYS) |>
  count(AEBODSYS) |>
  mutate(Total = n_pct(n, N_total)) |>
  select(AEBODSYS, Total)

soc_wide <- left_join(soc_arm, soc_total, by = "AEBODSYS") |>
  mutate(soc = AEBODSYS, pt = AEBODSYS, row_type = "soc", .before = 1) |>
  select(-AEBODSYS)

# ── PT-level ──
pt_arm <- adae_disc |>
  distinct(USUBJID, TRT01A, AEBODSYS, AEDECOD) |>
  count(TRT01A, AEBODSYS, AEDECOD) |>
  filter(TRT01A %in% arm_levels) |>
  mutate(value = mapply(n_pct, n, arm_n[TRT01A])) |>
  select(TRT01A, AEBODSYS, AEDECOD, value) |>
  pivot_wider(names_from = TRT01A, values_from = value)

pt_total <- adae_disc |>
  distinct(USUBJID, AEBODSYS, AEDECOD) |>
  count(AEBODSYS, AEDECOD) |>
  mutate(Total = n_pct(n, N_total)) |>
  select(AEBODSYS, AEDECOD, Total)

pt_wide <- left_join(pt_arm, pt_total, by = c("AEBODSYS", "AEDECOD")) |>
  mutate(soc = AEBODSYS, pt = AEDECOD, row_type = "pt", .before = 1) |>
  select(-AEBODSYS, -AEDECOD)

# ── Sort and interleave ──
soc_order <- adae_disc |>
  distinct(USUBJID, AEBODSYS) |>
  count(AEBODSYS, name = "soc_n") |>
  arrange(desc(soc_n)) |>
  pull(AEBODSYS)

ae_disc_wide <- bind_rows(
  any_disc_row,
  bind_rows(lapply(soc_order, function(s) {
    bind_rows(
      filter(soc_wide, soc == s),
      filter(pt_wide, soc == s) |>
        left_join(
          adae_disc |> distinct(USUBJID, AEBODSYS, AEDECOD) |>
            count(AEBODSYS, AEDECOD, name = "pt_n"),
          by = c("soc" = "AEBODSYS", "pt" = "AEDECOD")
        ) |> arrange(desc(pt_n)) |> select(-pt_n)
    )
  }))
) |>
  mutate(across(where(is.character) & !c(soc, pt, row_type),
                ~ replace_na(.x, "0 (0.0)")))

# Ensure all arm columns exist
for (a in arm_levels) {
  if (!a %in% names(ae_disc_wide)) ae_disc_wide[[a]] <- "0 (0.0)"
}

disc_ard <- ard_stack_hierarchical(
  data        = adae_disc,
  variables   = c(AEBODSYS, AEDECOD),
  by          = TRT01A,
  denominator = adsl_saf,
  id          = USUBJID,
  overall     = TRUE,
  over_variables = TRUE
) |>
  sort_ard_hierarchical(sort = "descending")

ae_disc_cards <- fr_wide_ard(
  disc_ard,
  statistic = "{n} ({p}%)",
  decimals  = c(p = 1),
  label     = c(
    "..ard_hierarchical_overall.." = "PATIENTS WITH AT LEAST ONE AE LEADING TO DISCONTINUATION",
    AEBODSYS = "System Organ Class",
    AEDECOD  = "Preferred Term"
  )
)

arframe Pipeline

The rendered table below uses the dplyr data prep (ae_disc_wide). The cards tab produces an equivalent ae_disc_cards — swap it in to use the cards path instead.

ae_disc_wide |>
  fr_table() |>
  fr_titles(
    "Table 14.3.2",
    "Patients With Adverse Events Leading to Study Drug Discontinuation",
    "by System Organ Class and Preferred Term",
    "Safety Population"
  ) |>
  fr_cols(
    soc      = fr_col(visible = FALSE),
    pt       = fr_col("System Organ Class\n  Preferred Term", width = 3.5),
    row_type = fr_col(visible = FALSE),
    !!!setNames(
      lapply(arm_levels, function(a) fr_col(a, align = "decimal")),
      arm_levels
    ),
    Total = fr_col("Total", align = "decimal"),
    .n = n_vec
  ) |>
  fr_header(bold = TRUE, align = "center") |>
  fr_rows(
    group_by  = "soc",
    indent_by = "pt"
  ) |>
  fr_styles(
    fr_row_style(rows = fr_rows_matches("row_type", value = "soc"), bold = TRUE),
    fr_row_style(rows = fr_rows_matches("row_type", value = "overall"), bold = TRUE)
  ) |>
  fr_footnotes(
    "Subjects counted once per SOC and once per PT.",
    "Percentages based on N per treatment arm (Safety Population).",
    "SOC sorted by descending frequency; PT sorted within SOC by descending frequency.",
    "Note: AEACN unavailable in this dataset; SAEs used as proxy for discontinuation."
  )

Rendered Table

Table 14.3.2

Patients With Adverse Events Leading to Study Drug Discontinuation

by System Organ Class and Preferred Term

Safety Population

System Organ Class Preferred Term	Xanomeline High Dose (N=72)	Xanomeline Low Dose (N=96)	Total (N=254)
PATIENTS WITH AT LEAST ONE AE LEADING TO DISCONTINUATION	1 (1.4)	2 (2.1)	3 (1.2)
NERVOUS SYSTEM DISORDERS	1 (1.4)	2 (2.1)	3 (1.2)
SYNCOPE	0	2 (2.1)	2 (0.8)
PARTIAL SEIZURES WITH SECONDARY GENERALISATION	1 (1.4)	0	1 (0.4)

Subjects counted once per SOC and once per PT.

Percentages based on N per treatment arm (Safety Population).

SOC sorted by descending frequency; PT sorted within SOC by descending frequency.

Note: AEACN unavailable in this dataset; SAEs used as proxy for discontinuation.

/opt/quarto/share/rmd/rmd.R 01APR2026 09:51:50

--- title: "AEs Leading to Study Drug Discontinuation" subtitle: "Treatment-Emergent AEs Leading to Discontinuation by SOC and PT" execute: echo: true eval: true --- ```{r} #| label: prereqs #| include: false library(arframe) fr_theme(hlines = "header", font_family = "Courier New") blank_to_na <- function(df) { df[] <- lapply(df, function(x) { if (is.character(x)) x[x == ""] <- NA_character_ x }) df } ``` ## Setup See [Prerequisites](../install.qmd) for installation instructions. ```{r} #| label: setup library(arframe) library(pharmaverseadam) library(dplyr, warn.conflicts = FALSE) library(tidyr) library(cards) adsl_saf <- pharmaverseadam::adsl |> blank_to_na() |> filter(SAFFL == "Y", TRT01A != "Screen Failure") # AEs where outcome was fatal or serious — proxy for discontinuation # pharmaverseadam AEACN is all NA, so we use AESER as proxy adae_disc <- pharmaverseadam::adae |> blank_to_na() |> filter(SAFFL == "Y", TRTEMFL == "Y", AESER == "Y") arm_levels <- c("Placebo", "Xanomeline Low Dose", "Xanomeline High Dose") arm_n <- adsl_saf |> filter(TRT01A %in% arm_levels) |> count(TRT01A) |> pull(n, name = TRT01A) arm_n <- arm_n[arm_levels] N_total <- nrow(adsl_saf) n_vec <- c(arm_n, Total = N_total) ``` ## Data Preparation ::: {.panel-tabset} ### dplyr ```{r} #| label: dplyr-code n_pct <- function(n, denom) sprintf("%d (%.1f)", n, n / denom * 100) # ── Overall row ── any_disc_arm <- adae_disc |> distinct(USUBJID, TRT01A) |> count(TRT01A) |> filter(TRT01A %in% arm_levels) |> mutate(value = mapply(n_pct, n, arm_n[TRT01A])) |> select(TRT01A, value) |> pivot_wider(names_from = TRT01A, values_from = value) any_disc_total <- n_distinct(adae_disc$USUBJID) any_disc_row <- bind_cols( tibble(soc = "PATIENTS WITH AT LEAST ONE AE LEADING TO DISCONTINUATION", pt = "PATIENTS WITH AT LEAST ONE AE LEADING TO DISCONTINUATION", row_type = "overall"), any_disc_arm, tibble(Total = n_pct(any_disc_total, N_total)) ) # ── SOC-level ── soc_arm <- adae_disc |> distinct(USUBJID, TRT01A, AEBODSYS) |> count(TRT01A, AEBODSYS) |> filter(TRT01A %in% arm_levels) |> mutate(value = mapply(n_pct, n, arm_n[TRT01A])) |> select(TRT01A, AEBODSYS, value) |> pivot_wider(names_from = TRT01A, values_from = value) soc_total <- adae_disc |> distinct(USUBJID, AEBODSYS) |> count(AEBODSYS) |> mutate(Total = n_pct(n, N_total)) |> select(AEBODSYS, Total) soc_wide <- left_join(soc_arm, soc_total, by = "AEBODSYS") |> mutate(soc = AEBODSYS, pt = AEBODSYS, row_type = "soc", .before = 1) |> select(-AEBODSYS) # ── PT-level ── pt_arm <- adae_disc |> distinct(USUBJID, TRT01A, AEBODSYS, AEDECOD) |> count(TRT01A, AEBODSYS, AEDECOD) |> filter(TRT01A %in% arm_levels) |> mutate(value = mapply(n_pct, n, arm_n[TRT01A])) |> select(TRT01A, AEBODSYS, AEDECOD, value) |> pivot_wider(names_from = TRT01A, values_from = value) pt_total <- adae_disc |> distinct(USUBJID, AEBODSYS, AEDECOD) |> count(AEBODSYS, AEDECOD) |> mutate(Total = n_pct(n, N_total)) |> select(AEBODSYS, AEDECOD, Total) pt_wide <- left_join(pt_arm, pt_total, by = c("AEBODSYS", "AEDECOD")) |> mutate(soc = AEBODSYS, pt = AEDECOD, row_type = "pt", .before = 1) |> select(-AEBODSYS, -AEDECOD) # ── Sort and interleave ── soc_order <- adae_disc |> distinct(USUBJID, AEBODSYS) |> count(AEBODSYS, name = "soc_n") |> arrange(desc(soc_n)) |> pull(AEBODSYS) ae_disc_wide <- bind_rows( any_disc_row, bind_rows(lapply(soc_order, function(s) { bind_rows( filter(soc_wide, soc == s), filter(pt_wide, soc == s) |> left_join( adae_disc |> distinct(USUBJID, AEBODSYS, AEDECOD) |> count(AEBODSYS, AEDECOD, name = "pt_n"), by = c("soc" = "AEBODSYS", "pt" = "AEDECOD") ) |> arrange(desc(pt_n)) |> select(-pt_n) ) })) ) |> mutate(across(where(is.character) & !c(soc, pt, row_type), ~ replace_na(.x, "0 (0.0)"))) # Ensure all arm columns exist for (a in arm_levels) { if (!a %in% names(ae_disc_wide)) ae_disc_wide[[a]] <- "0 (0.0)" } ``` ### cards ```{r} #| label: cards-code disc_ard <- ard_stack_hierarchical( data = adae_disc, variables = c(AEBODSYS, AEDECOD), by = TRT01A, denominator = adsl_saf, id = USUBJID, overall = TRUE, over_variables = TRUE ) |> sort_ard_hierarchical(sort = "descending") ae_disc_cards <- fr_wide_ard( disc_ard, statistic = "{n} ({p}%)", decimals = c(p = 1), label = c( "..ard_hierarchical_overall.." = "PATIENTS WITH AT LEAST ONE AE LEADING TO DISCONTINUATION", AEBODSYS = "System Organ Class", AEDECOD = "Preferred Term" ) ) ``` ::: ## arframe Pipeline The rendered table below uses the **dplyr** data prep (`ae_disc_wide`). The cards tab produces an equivalent `ae_disc_cards` — swap it in to use the cards path instead. ```{r} #| label: pipeline #| eval: false ae_disc_wide |> fr_table() |> fr_titles( "Table 14.3.2", "Patients With Adverse Events Leading to Study Drug Discontinuation", "by System Organ Class and Preferred Term", "Safety Population" ) |> fr_cols( soc = fr_col(visible = FALSE), pt = fr_col("System Organ Class\n Preferred Term", width = 3.5), row_type = fr_col(visible = FALSE), !!!setNames( lapply(arm_levels, function(a) fr_col(a, align = "decimal")), arm_levels ), Total = fr_col("Total", align = "decimal"), .n = n_vec ) |> fr_header(bold = TRUE, align = "center") |> fr_rows( group_by = "soc", indent_by = "pt" ) |> fr_styles( fr_row_style(rows = fr_rows_matches("row_type", value = "soc"), bold = TRUE), fr_row_style(rows = fr_rows_matches("row_type", value = "overall"), bold = TRUE) ) |> fr_footnotes( "Subjects counted once per SOC and once per PT.", "Percentages based on N per treatment arm (Safety Population).", "SOC sorted by descending frequency; PT sorted within SOC by descending frequency.", "Note: AEACN unavailable in this dataset; SAEs used as proxy for discontinuation." ) ``` ## Rendered Table ```{r} #| label: table #| echo: false #| ref.label: pipeline ```