Overview of Treatment-Emergent Adverse Events

id: t-ae-overview
title: "Overview of Treatment-Emergent Adverse Events"
regulatory_id: AET01
type: table
dataset: adae
analysis_set: safety
denominator: adsl
group:
  - TRT01A
total: true
analyses:
  - name: n_events
    method: subject_count
    custom: ard_event_count
    label: "Number of treatment-emergent adverse events"
    filter: "TRTEMFL == 'Y'"
  - name: any_ae
    method: subject_count
    label: "Subjects with at least one treatment-emergent adverse event"
    variable: AEFL
    filter: "TRTEMFL == 'Y'"
  - name: serious_ae
    method: subject_count
    label: "Subjects with a serious adverse event"
    variable: AESERFL
    filter: "TRTEMFL == 'Y' & AESER == 'Y'"
  - name: fatal_ae
    method: subject_count
    label: "Subjects with a fatal adverse event"
    variable: AEFATFL
    filter: "TRTEMFL == 'Y' & AEOUT == 'FATAL'"
  - name: related_ae
    method: subject_count
    label: "Subjects with a related adverse event"
    variable: AERELFL
    filter: "TRTEMFL == 'Y' & AEREL %in% c('POSSIBLE', 'PROBABLE')"
  - name: sev_mild
    method: subject_count
    label: "Maximum severity mild"
    variable: AESEVFL
    filter: "TRTEMFL == 'Y' & AESEV == 'MILD'"
  - name: sev_moderate
    method: subject_count
    label: "Maximum severity moderate"
    variable: AESEVFL
    filter: "TRTEMFL == 'Y' & AESEV == 'MODERATE'"
  - name: sev_severe
    method: subject_count
    label: "Maximum severity severe"
    variable: AESEVFL
    filter: "TRTEMFL == 'Y' & AESEV == 'SEVERE'"

id: t-ae-overview
title: "Overview of Treatment-Emergent Adverse Events"
study: CDISCPILOT01
population_label: "Safety Analysis Set"
cutoff: "2014-07-01"
source: "Source: adae, adsl (pharmaverseadam). Data cut-off: 2014-07-01."
footnotes:
  - "A treatment-emergent adverse event is an event with TRTEMFL = 'Y'."
  - "Percentages are based on the number of subjects in the safety analysis set for each treatment group."
  - "Subjects reporting more than one event are counted once in each row they qualify for; severity rows count subjects with at least one event of that severity and therefore do not sum to the number of subjects with any event."
columns:
  order: [Placebo, "Xanomeline Low Dose", "Xanomeline High Dose", Total]
format:
  digits:
    p: 1
rows:
  - { label: "Adverse events", section: true }
  - { analysis: n_events, variable: AENUM, pattern: "n", label: "Number of events", indent: 1 }
  - { analysis: any_ae, label: "Subjects with ≥1 adverse event", pattern: n_pct, indent: 1 }
  - { analysis: serious_ae, label: "Subjects with a serious adverse event", pattern: n_pct, indent: 1 }
  - { analysis: fatal_ae, label: "Subjects with a fatal adverse event", pattern: n_pct, indent: 1 }
  - { analysis: related_ae, label: "Subjects with a related adverse event", pattern: n_pct, indent: 1 }
  - { label: "Subjects by severity, n (%)", section: true }
  - { analysis: sev_mild, label: "Mild", pattern: n_pct, indent: 1 }
  - { analysis: sev_moderate, label: "Moderate", pattern: n_pct, indent: 1 }
  - { analysis: sev_severe, label: "Severe", pattern: n_pct, indent: 1 }
variants:
  post_text: {}
  in_text:
    title: "Overview of Treatment-Emergent Adverse Events (Summary)"

# Display-specific statistics for t-ae-overview.
#
# The v0 method vocabulary (contract §2) counts *subjects*; an AE overview also
# has to report the number of *events*, which no built-in method provides. Rather
# than widen the vocabulary for one display, the analysis entry sets
# `custom: ard_event_count` and this function is dispatched instead.
#
# Contract: the function receives (data, spec, denominator) and returns a
# {cards}-shaped ARD. `spec` is the analysis entry, with `spec$group` holding the
# grouping variable actually in force — which is how the same function also
# produces the Total column (the engine re-runs it against a constant group).

#' Count adverse-event records per group
#'
#' @param data Analysis dataset, already restricted to the analysis set and to
#'   the analysis entry's `filter`.
#' @param spec The analysis entry (a list), including `spec$group`.
#' @param denominator Subject-level denominator dataset (unused: an event count
#'   has no denominator, and reporting a percentage of subjects against a count
#'   of events would be wrong).
#' @return A data frame carrying the `{cards}` ARD columns.
ard_event_count <- function(data, spec, denominator) {
  group <- spec$group
  levels <- if (length(group)) {
    lv <- levels(data[[group]])
    if (is.null(lv)) sort(unique(as.character(data[[group]]))) else lv
  } else {
    NA_character_
  }
  counts <- vapply(levels, function(lv) {
    if (is.na(lv)) nrow(data) else sum(as.character(data[[group]]) == lv, na.rm = TRUE)
  }, numeric(1))

  data.frame(
    group1 = if (length(group)) group else NA_character_,
    group1_level = as.character(levels),
    variable = "AENUM",
    variable_level = NA_character_,
    context = "event_count",
    stat_name = "n",
    stat_label = "Number of events",
    stat = unname(counts),
    warning = NA_character_,
    error = NA_character_,
    stringsAsFactors = FALSE
  )
}