Closes #292 add ader template

inst/templates/ad_ader.R

@@ -0,0 +1,213 @@
+# Name: ADER
+#
+# Label: Exposure Response Data
+#
+# Input: adsl, adrs, adtte, adlb, advs, adex
+library(admiral)
+library(admiralonco)
+# pharmaverseadam contains example datasets generated from the CDISC pilot
+# project SDTM ran through admiral templates
+library(pharmaverseadam)
+library(dplyr)
+library(lubridate)
+library(stringr)
+
+# 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
+
+data("admiral_adsl")
+data("admiral_adrs")
+data("country_code_lookup")
+
+adsl <- admiral_adsl
+adrs <- admiral_adrs
+
+adtte <- pharmaverseadam::adtte_onco
+adlb <- pharmaverseadam::adlb
+advs <- pharmaverseadam::advs
+adex <- pharmaverseadam::adex %>%
+  filter(PARCAT1 == "INDIVIDUAL")
+
+adpp <- pharmaverseadam::adpp
+
+
+# Derivations ----
+
+# For ADTTE censor variables add "IND" to PARAMCD
+adttei <- adtte %>%
+  mutate(PARAMCD = paste0(PARAMCD, "IND"))
+
+ader_tte <- adsl %>%
+  select(!!!get_admiral_option("subject_keys")) %>%
+  # Create OS and PFS variables from ADTTE
+  derive_vars_transposed(
+    dataset_merge = adtte,
+    by_vars = get_admiral_option("subject_keys"),
+    key_var = PARAMCD,
+    value_var = AVAL
+  ) %>%
+  # Create OS and PFS censor variables
+  derive_vars_transposed(
+    dataset_merge = adttei,
+    by_vars = get_admiral_option("subject_keys"),
+    key_var = PARAMCD,
+    value_var = CNSR
+  )
+
+# Derive Best Overall Response (BOR) variables from ADRS
+ader_bor <- ader_tte %>%
+  derive_vars_merged(
+    dataset_add = adrs,
+    filter_add = PARAMCD == "BOR" & ANL01FL == "Y",
+    by_vars = get_admiral_option("subject_keys"),
+    new_vars = exprs(BOR = AVAL, BORC = AVALC)
+  )
+
+# Add exposure metrics
+
+ader_auc <- ader_bor %>%
+  derive_vars_transposed(
+    dataset_merge = adpp,
+    filter = PARAMCD %in% c("AUCLST", "CMAX"),
+    by_vars = get_admiral_option("subject_keys"),
+    key_var = PARAMCD,
+    value_var = AVAL
+  ) %>%
+  rename(AUCSS = AUCLST, CMAXSS = CMAX)
+
+# Add Sequence number
+
+ader_aseq <- ader_auc %>%
+  derive_var_obs_number(
+    by_vars = get_admiral_option("subject_keys"),
+    check_type = "error"
+  )
+
+# ---- Derive Covariates ----
+# Include numeric values for STUDYIDN, USUBJIDN, SEXN, RACEN etc.
+
+covar <- adsl %>%
+  derive_vars_merged(
+    dataset_add = country_code_lookup,
+    new_vars = exprs(COUNTRYN = country_number, COUNTRYL = country_name),
+    by_vars = exprs(COUNTRY = country_code)
+  ) %>%
+  mutate(
+    STUDYIDN = as.numeric(word(USUBJID, 1, sep = fixed("-"))),
+    SITEIDN = as.numeric(word(USUBJID, 2, sep = fixed("-"))),
+    USUBJIDN = as.numeric(word(USUBJID, 3, sep = fixed("-"))),
+    SUBJIDN = as.numeric(SUBJID),
+    SEXN = case_when(
+      SEX == "M" ~ 1,
+      SEX == "F" ~ 2,
+      TRUE ~ 3
+    ),
+    RACEN = case_when(
+      RACE == "AMERICAN INDIAN OR ALASKA NATIVE" ~ 1,
+      RACE == "ASIAN" ~ 2,
+      RACE == "BLACK OR AFRICAN AMERICAN" ~ 3,
+      RACE == "NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER" ~ 4,
+      RACE == "WHITE" ~ 5,
+      TRUE ~ 6
+    ),
+    ETHNICN = case_when(
+      ETHNIC == "HISPANIC OR LATINO" ~ 1,
+      ETHNIC == "NOT HISPANIC OR LATINO" ~ 2,
+      TRUE ~ 3
+    ),
+    ARMN = case_when(
+      ARM == "Placebo" ~ 0,
+      ARM == "Xanomeline Low Dose" ~ 1,
+      ARM == "Xanomeline High Dose" ~ 2,
+      TRUE ~ 3
+    ),
+    ACTARMN = case_when(
+      ACTARM == "Placebo" ~ 0,
+      ACTARM == "Xanomeline Low Dose" ~ 1,
+      ACTARM == "Xanomeline High Dose" ~ 2,
+      TRUE ~ 3
+    ),
+    COHORT = ARMN,
+    COHORTC = ARM,
+    ROUTE = unique(adex$EXROUTE)[1],
+    ROUTEN = case_when(
+      ROUTE == "TRANSDERMAL" ~ 3,
+      TRUE ~ NA_real_
+    ),
+    FORM = unique(adex$EXDOSFRM)[1],
+    FORMN = case_when(
+      FORM == "PATCH" ~ 3,
+      TRUE ~ 4
+    )
+  ) %>%
+  select(
+    STUDYID, STUDYIDN, SITEID, SITEIDN, USUBJID, USUBJIDN,
+    SUBJID, SUBJIDN, AGE, SEX, SEXN, COHORT, COHORTC, ROUTE, ROUTEN,
+    RACE, RACEN, ETHNIC, ETHNICN, FORM, FORMN, COUNTRY, COUNTRYN, COUNTRYL
+  )
+
+# ---- Derive additional baselines from ADVS and ADLB ----
+
+labsbl <- adlb %>%
+  filter(ABLFL == "Y" & PARAMCD %in% c("CREAT", "ALT", "AST", "BILI")) %>%
+  mutate(PARAMCDB = paste0(PARAMCD, "BL")) %>%
+  select(STUDYID, USUBJID, PARAMCDB, AVAL)
+
+covar_vslb <- covar %>%
+  derive_vars_merged(
+    dataset_add = advs,
+    filter_add = PARAMCD == "HEIGHT" & ABLFL == "Y",
+    by_vars = exprs(STUDYID, USUBJID),
+    new_vars = exprs(HTBL = AVAL)
+  ) %>%
+  derive_vars_merged(
+    dataset_add = advs,
+    filter_add = PARAMCD == "WEIGHT" & ABLFL == "Y",
+    by_vars = exprs(STUDYID, USUBJID),
+    new_vars = exprs(WTBL = AVAL)
+  ) %>%
+  derive_vars_transposed(
+    dataset_merge = labsbl,
+    by_vars = exprs(STUDYID, USUBJID),
+    key_var = PARAMCDB,
+    value_var = AVAL
+  ) %>%
+  mutate(
+    BMIBL = compute_bmi(height = HTBL, weight = WTBL),
+    BSABL = compute_bsa(
+      height = HTBL,
+      weight = WTBL,
+      method = "Mosteller"
+    ),
+    CRCLBL = compute_egfr(
+      creat = CREATBL, creatu = "SI", age = AGE, weight = WTBL, sex = SEX,
+      method = "CRCL"
+    ),
+    EGFRBL = compute_egfr(
+      creat = CREATBL, creatu = "SI", age = AGE, weight = WTBL, sex = SEX,
+      method = "CKD-EPI"
+    )
+  ) %>%
+  rename(TBILBL = BILIBL)
+
+# Combine covariates with ADER data
+
+ader <- ader_aseq %>%
+  derive_vars_merged(
+    dataset_add = covar_vslb,
+    by_vars = exprs(STUDYID, USUBJID)
+  )
+
+# Save output ----
+
+# Change to whichever directory you want to save the dataset in
+dir <- tools::R_user_dir("admiralonco_templates_data", which = "cache")
+if (!file.exists(dir)) {
+  # Create the folder
+  dir.create(dir, recursive = TRUE, showWarnings = FALSE)
+}
+save(ader, file = file.path(dir, "ader.rda"), compress = "bzip2")
+

inst/templates/ad_adtte.R

@@ -7,7 +7,7 @@ library(admiral)
 library(admiralonco)
 # pharmaverseadam contains example datasets generated from the CDISC pilot
 # project SDTM ran through admiral templates
-library(pharmaverseadam)
+#library(pharmaverseadam)
 library(dplyr)
 library(lubridate)