inst/templates/ad_adlbhy.R

In Roche-GSK/admiral: ADaM in R Asset Library

# Name: ADLBHY
#
# Label: Lab Analysis Dataset for Hy's Law
#
# Input: adlb
library(admiral)
library(dplyr)
library(lubridate)

# Load source datasets ----

# Use e.g. haven::read_sas to read in .sas7bdat, or other suitable functions
# as needed and assign to the variables below.
# For illustration purposes read in admiral test data
# Using use_ad_template("adlb") and assigning the end object as admiral_adlb
# ADLBHY is a special dataset specifically used to check for potential drug induced liver injuries
# Please see "Hy's Law Implementation Guide" on the admiral website for additional information

adlb <- admiral::admiral_adlb

adlb_annotated <- adlb %>%
  filter(PARAMCD %in% c("AST", "ALT", "BILI") & is.na(DTYPE)) %>%
  # Assign flags for contribution to potential Hy's Law event
  slice_derivation(
    derive_vars_crit_flag,
    args = params(
      values_yn = TRUE
    ),
    derivation_slice(
      filter = PARAMCD %in% c("AST", "ALT"),
      args = params(
        condition = AVAL / ANRHI >= 3,
        description = paste(PARAMCD, ">=3xULN")
      )
    ),
    derivation_slice(
      filter = PARAMCD == "BILI",
      args = params(
        condition = AVAL / ANRHI >= 2,
        description = "BILI >= 2xULN"
      )
    )
  ) %>%
  select(STUDYID, USUBJID, TRT01A, PARAMCD, LBSEQ, ADT, AVISIT, ADY, AVAL, ANRHI, CRIT1, CRIT1FL)

# Subset Datasets
altast_records <- adlb_annotated %>%
  filter(PARAMCD %in% c("AST", "ALT"))

bili_records <- adlb_annotated %>%
  filter(PARAMCD %in% c("BILI"))

# Flag elevated AST/ALT values with a BILI elevation within 14 days
hylaw_records <- derive_vars_joined(
  dataset = altast_records,
  dataset_add = bili_records,
  by_vars = exprs(STUDYID, USUBJID),
  order = exprs(ADY),
  join_type = "all",
  filter_join = 0 <= ADT.join - ADT & ADT.join - ADT <= 14 & CRIT1FL == "Y" & CRIT1FL.join == "Y",
  new_vars = exprs(BILI_LBSEQ = LBSEQ, BILI_DT = ADT, BILI_CRITFL = CRIT1FL),
  mode = "first"
)

hylaw_records_pts_visits <- hylaw_records %>%
  select(STUDYID, USUBJID, TRT01A) %>% # add AVISIT, ADT for by visit
  distinct()

hylaw_records_fls <- hylaw_records %>%
  select(STUDYID, USUBJID, TRT01A, CRIT1FL, BILI_CRITFL) %>% # add AVISIT, ADT for by visit
  distinct()

# Create new parameters based on records that present potential case
hylaw_params <- derive_param_exist_flag(
  dataset_ref = hylaw_records_pts_visits,
  dataset_add = hylaw_records_fls,
  condition = CRIT1FL == "Y" & BILI_CRITFL == "Y",
  false_value = "N",
  missing_value = "N",
  by_vars = exprs(STUDYID, USUBJID, TRT01A), # add AVISIT, ADT for by visit
  set_values_to = exprs(
    PARAMCD = "HYSLAW",
    PARAM = "ALT/AST >= 3xULN and BILI >= 2xULN"
  )
)

# Row bind back to relevant adlb-like dataset
adlbhy <- adlb_annotated %>%
  bind_rows(hylaw_params)

# Change to whichever directory you want to save the dataset in
dir <- tools::R_user_dir("admiral_templates_data", which = "cache")
if (!file.exists(dir)) {
  # Create the folder
  dir.create(dir, recursive = TRUE, showWarnings = FALSE)
}
save(adlbhy, file = file.path(dir, "adlbhy.rda"), compress = "bzip2")