Helper Function to create a new SMQ variable in ADAE by stacking SMQ and/or CQ records.

Helper Function to create a new SMQ variable in ADAE that consists of all adverse events belonging to selected Standardized/Customized queries. The new dataset will only contain records of the adverse events belonging to any of the selected baskets.

Usage

h_stack_by_baskets(
  df,
  baskets = grep("^(SMQ|CQ).+NAM$", names(df), value = TRUE),
  smq_varlabel = "Standardized MedDRA Query",
  keys = c("STUDYID", "USUBJID", "ASTDTM", "AEDECOD", "AESEQ"),
  aag_summary = NULL,
  na_level = "<Missing>"
)

Arguments

df: (data.frame)
data set containing all analysis variables.
baskets: (character)
variable names of the selected Standardized/Customized queries.
smq_varlabel: (string)
a label for the new variable created.
keys: (character)
names of the key variables to be returned along with the new variable created.
aag_summary: (data.frame)
containing the SMQ baskets and the levels of interest for the final SMQ variable. This is useful when there are some levels of interest that are not observed in the df dataset. The two columns of this dataset should be named basket and basket_name.
na_level: (string)
string used to replace all NA or empty values in the output.

Value

data.frame with variables in keys taken from df and new variable SMQ containing records belonging to the baskets selected via the baskets argument.

Examples

adae <- tern_ex_adae[1:20, ] %>% df_explicit_na()
h_stack_by_baskets(df = adae)
#> # A tibble: 8 × 6
#>   STUDYID USUBJID               ASTDTM              AEDECOD       AESEQ SMQ     
#>   <fct>   <fct>                 <dttm>              <fct>         <int> <fct>   
#> 1 AB12345 AB12345-BRA-11-id-8   2021-12-05 02:02:07 dcd D.2.1.5.3     2 D.2.1.5…
#> 2 AB12345 AB12345-BRA-12-id-120 2020-02-05 01:42:29 dcd D.2.1.5.3     2 D.2.1.5…
#> 3 AB12345 AB12345-BRA-1-id-171  2022-11-29 12:18:31 dcd C.1.1.1.3     2 C.1.1.1…
#> 4 AB12345 AB12345-BRA-1-id-23   2020-07-10 07:32:49 dcd B.2.2.3.1     3 C.1.1.1…
#> 5 AB12345 AB12345-BRA-1-id-59   2021-10-10 23:54:46 dcd C.1.1.1.3     4 C.1.1.1…
#> 6 AB12345 AB12345-BRA-1-id-9    2021-06-01 14:39:09 dcd C.1.1.1.3     1 C.1.1.1…
#> 7 AB12345 AB12345-BRA-11-id-8   2021-12-21 02:02:07 dcd C.1.1.1.3     3 C.1.1.1…
#> 8 AB12345 AB12345-BRA-12-id-120 2020-10-01 01:42:29 dcd C.1.1.1.3     3 C.1.1.1…

aag <- data.frame(
  NAMVAR = c("CQ01NAM", "CQ02NAM", "SMQ01NAM", "SMQ02NAM"),
  REFNAME = c(
    "D.2.1.5.3/A.1.1.1.1 AESI", "X.9.9.9.9/Y.8.8.8.8 AESI",
    "C.1.1.1.3/B.2.2.3.1 AESI", "C.1.1.1.3/B.3.3.3.3 AESI"
  ),
  SCOPE = c("", "", "BROAD", "BROAD"),
  stringsAsFactors = FALSE
)

basket_name <- character(nrow(aag))
cq_pos <- grep("^(CQ).+NAM$", aag$NAMVAR)
smq_pos <- grep("^(SMQ).+NAM$", aag$NAMVAR)
basket_name[cq_pos] <- aag$REFNAME[cq_pos]
basket_name[smq_pos] <- paste0(
  aag$REFNAME[smq_pos], "(", aag$SCOPE[smq_pos], ")"
)

aag_summary <- data.frame(
  basket = aag$NAMVAR,
  basket_name = basket_name,
  stringsAsFactors = TRUE
)

result <- h_stack_by_baskets(df = adae, aag_summary = aag_summary)
#> Warning: There are 0 basket levels in common between aag_summary$basket_name and df.
all(levels(aag_summary$basket_name) %in% levels(result$SMQ))
#> [1] TRUE

h_stack_by_baskets(
  df = adae,
  aag_summary = NULL,
  keys = c("STUDYID", "USUBJID", "AEDECOD", "ARM"),
  baskets = "SMQ01NAM"
)
#> # A tibble: 6 × 5
#>   STUDYID USUBJID               AEDECOD       ARM            SMQ                
#>   <fct>   <fct>                 <fct>         <fct>          <fct>              
#> 1 AB12345 AB12345-BRA-1-id-171  dcd C.1.1.1.3 B: Placebo     C.1.1.1.3/B.2.2.3.…
#> 2 AB12345 AB12345-BRA-1-id-23   dcd B.2.2.3.1 A: Drug X      C.1.1.1.3/B.2.2.3.…
#> 3 AB12345 AB12345-BRA-1-id-59   dcd C.1.1.1.3 A: Drug X      C.1.1.1.3/B.2.2.3.…
#> 4 AB12345 AB12345-BRA-1-id-9    dcd C.1.1.1.3 C: Combination C.1.1.1.3/B.2.2.3.…
#> 5 AB12345 AB12345-BRA-11-id-8   dcd C.1.1.1.3 A: Drug X      C.1.1.1.3/B.2.2.3.…
#> 6 AB12345 AB12345-BRA-12-id-120 dcd C.1.1.1.3 A: Drug X      C.1.1.1.3/B.2.2.3.…