Admiral Adrs

library(admiral)
library(admiralonco)
library(dplyr)
library(lubridate)
library(pharmaversesdtm)

# Load RS domain
# For pharmaversesdtm test data: use rs_onco_recist (plain `rs` no longer exported)
rs   <- pharmaversesdtm::rs_onco_recist
adsl <- adsl  # assumed derived upstream; replace with path/load as needed

# Confirm RS has at least one record
stopifnot(nrow(rs) > 0)

rs <- rs |> select(-DOMAIN)

# REVIEW: Confirm which ADSL variables are required by the ADaM ADRS spec.
#   RANDDT is the conventional clinical benefit anchor date; TRTSDT is required
#   for ADY derivation. Add or remove population flags per the spec.
adrs <- rs |>
  derive_vars_merged(
    dataset_add = adsl,
    by_vars     = exprs(STUDYID, USUBJID),
    new_vars    = exprs(RANDDT, TRTSDT, TRT01P, TRT01PN, TRT01A, TRT01AN,
                        ITTFL, SAFFL)
  )

adrs <- adrs |>
  derive_vars_dt(
    dtc             = RSDTC,
    new_vars_prefix = "A",
    date_imputation = "first",
    flag_imputation = "auto"
  ) |>
  derive_vars_dy(
    reference_date = TRTSDT,
    source_vars    = exprs(ADT)
  )

# REVIEW: Confirm that RSSTRESC values in this study's RS domain align with the
#   RECIST 1.1 CT expected by aval_resp(). Non-standard categories (e.g.
#   "NON-CR/NON-PD" in lymphoma, iRECIST response categories) require a custom
#   lookup if aval_resp() does not map them — do not suppress the resulting NA.
adrs <- adrs |>
  mutate(
    AVALC = RSSTRESC,
    AVAL  = aval_resp(AVALC)
  )

# REVIEW: PARAMCD and PARAM values must match the ADaM ADRS spec exactly.
#   Adjust filter_source if the study uses a different assessor
#   (BICR: RSEVAL == "INDEPENDENT ASSESSOR") or a different RECIST version.
adrs <- adrs |>
  derive_param_response(
    dataset_adsl  = adsl,
    filter_source = RSEVAL == "INVESTIGATOR" & RSEVALID == "RECIST 1.1",
    source_var    = RSSTRESC,
    set_values_to = exprs(
      PARAMCD = "OVRLRESP",
      PARAM   = "Overall Response by Investigator"
    )
  )

adrs <- adrs |>
  derive_param_response(
    dataset_adsl  = adsl,
    filter_source = RSEVAL == "INVESTIGATOR" & RSEVALID == "RECIST 1.1",
    source_var    = RSSTRESC,
    resp_val      = c("CR", "PR"),
    set_values_to = exprs(
      PARAMCD = "RSP",
      PARAM   = "Response (Unconfirmed)"
    )
  )

# REVIEW: ref_confirm = 28 is the RECIST 1.1 standard for CR/PR confirmation.
#   Confirm this value against the study protocol and SAP — some programs specify
#   21 days, and regulatory precedent exists for other windows. A wrong value
#   silently inflates or deflates confirmed ORR.
adrs <- adrs |>
  derive_param_confirmed_resp(
    dataset_adsl  = adsl,
    filter_source = RSEVAL == "INVESTIGATOR" & RSEVALID == "RECIST 1.1",
    source_var    = RSSTRESC,
    ref_confirm   = 28,       # PLACEHOLDER — confirm from SAP
    set_values_to = exprs(
      PARAMCD = "CONFIRMED",
      PARAM   = "Confirmed Response"
    )
  )

# REVIEW: missing_as_ne controls how missing assessments are treated in BOR.
#   FALSE (default): missing assessments are ignored (excluded from BOR).
#   TRUE: missing assessments count as NE, which can worsen BOR for subjects
#   with gaps in the assessment schedule.
#   Confirm the per-protocol analysis population definition with the
#   statistical reviewer before committing to either value.
adrs <- adrs |>
  derive_param_confirmed_bor(
    dataset_adsl  = adsl,
    filter_source = RSEVAL == "INVESTIGATOR" & RSEVALID == "RECIST 1.1",
    source_var    = RSSTRESC,
    ref_confirm   = 28,       # must match Step 8
    missing_as_ne = FALSE,    # PLACEHOLDER — confirm from SAP
    set_values_to = exprs(
      PARAMCD = "BESTRESP",
      PARAM   = "Best Overall Response (Confirmed)"
    )
  )

# REVIEW: Two protocol-specific decisions are required here and must both be
#   confirmed from the protocol and SAP before use:
#
#   (1) reference_date — RANDDT is the conventional anchor. Some protocols
#       instead define the 42-day window from the date of the first qualifying
#       response (first SD, PR, or CR). If the protocol means "from first
#       qualifying assessment", compute per-subject first-assessment dates
#       and pass them as reference_date rather than a fixed ADSL variable.
#
#   (2) ref_start_window = 42 — RECIST standard for SD duration. Some studies
#       use 35 or 56 days. Confirm from the protocol.
adrs <- adrs |>
  derive_param_clinbenefit(
    dataset_adsl     = adsl,
    filter_source    = RSEVAL == "INVESTIGATOR" & RSEVALID == "RECIST 1.1",
    source_var       = RSSTRESC,
    reference_date   = RANDDT,    # PLACEHOLDER — confirm anchor from protocol
    ref_start_window = 42,        # PLACEHOLDER — confirm from protocol
    set_values_to    = exprs(
      PARAMCD = "CBRESPFL",
      PARAM   = "Clinical Benefit"
    )
  )

# Print response parameter summary for QC — include in script output log
response_summary <- adrs |>
  filter(PARAMCD %in% c("RSP", "CONFIRMED", "CBRESPFL")) |>
  count(PARAMCD, AVALC)
print(response_summary)

# Confirmed ORR must not exceed unconfirmed ORR
n_confirmed   <- sum(adrs$PARAMCD == "CONFIRMED" & adrs$AVALC == "Y", na.rm = TRUE)
n_unconfirmed <- sum(adrs$PARAMCD == "RSP"       & adrs$AVALC == "Y", na.rm = TRUE)
stopifnot(n_confirmed <= n_unconfirmed)

# PD is never a confirmed response
stopifnot(!any(
  adrs$PARAMCD == "CONFIRMED" & adrs$AVALC == "Y" &
  adrs$AVAL == aval_resp("PD"),
  na.rm = TRUE
))

# Required parameter coverage
required_params <- c("OVRLRESP", "RSP", "CONFIRMED", "BESTRESP", "CBRESPFL")
missing_params  <- setdiff(required_params, unique(adrs$PARAMCD))
if (length(missing_params) > 0) {
  stop("Missing required ADRS parameters: ", paste(missing_params, collapse = ", "))
}

# Uniqueness: one record per subject per subject-level parameter
dup_check <- adrs |>
  filter(PARAMCD %in% c("BESTRESP", "CONFIRMED", "RSP", "CBRESPFL")) |>
  count(STUDYID, USUBJID, PARAMCD) |>
  filter(n > 1)
if (nrow(dup_check) > 0) {
  stop("Duplicate subject-level parameter records found:\n",
       paste(paste(dup_check$USUBJID, dup_check$PARAMCD), collapse = "\n"))
}

# Required variable presence check
required_vars <- c(
  "STUDYID", "USUBJID", "PARAMCD", "PARAM",
  "ADT", "ADTF", "ADY", "AVAL", "AVALC", "TRTSDT"
)
missing_vars <- setdiff(required_vars, names(adrs))
if (length(missing_vars) > 0) {
  stop("Missing required ADRS variables: ", paste(missing_vars, collapse = ", "))
}