This is used to do post processing for ADaM reactogenicity dataset, for the derived
SDTM level records, the corresponding values in FA variables will be NA
.
The input dataframe with NA
values in FA variables where the SDTM records modified for
ADaM derivation purpose.
library(dplyr)
library(admiral)
library(tibble)
input <- tribble(
~USUBJID, ~FAOBJ, ~FALAT, ~FACAT, ~FASCAT, ~FATPT, ~FATESTCD, ~PARAMCD, ~AVAL,
"ABC-1001", "FEVER", NA, "REACTO", "SYS", "DAY 1", "MAXTEMP", "MAXTEMP", 39.4,
"ABC-1001", "VOMITING", NA, "REACTO", "SYS", "DAY 4", "MAXSEV", "MAXVOMIT", 3,
"ABC-1001", "SWELLING", "LEFT", "REACTO", "ADMIN", "DAY 1", "MAXSEV", "MAXSWEL", 3,
"ABC-1001", "REDNESS", "LEFT", "REACTO", "ADMIN", "DAY 2", "DIAMATER", "DIARE", 10.3,
"ABC-1001", "FEVER", "LEFT", "REACTO", "SYS", "DAY 2", "OCCUR", "OCCFEV", NA
)
post_process_reacto(
dataset = input,
filter_dataset = FATESTCD %in% c("MAXSEV", "MAXTEMP") |
(FATESTCD == "OCCUR" & FAOBJ == "FEVER")
)
#> # A tibble: 5 × 9
#> USUBJID FAOBJ FALAT FACAT FASCAT FATPT FATESTCD PARAMCD AVAL
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 ABC-1001 NA NA NA NA NA NA MAXTEMP 39.4
#> 2 ABC-1001 NA NA NA NA NA NA MAXVOMIT 3
#> 3 ABC-1001 NA NA NA NA NA NA MAXSWEL 3
#> 4 ABC-1001 REDNESS LEFT REACTO ADMIN DAY 2 DIAMATER DIARE 10.3
#> 5 ABC-1001 NA NA NA NA NA NA OCCFEV NA