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Derive ATC Class Variables

Source: R/derive_vars_transposed.R
derive_vars_atc.Rd

Add Anatomical Therapeutic Chemical class variables from FACM to ADCM.

Note: This is a wrapper function for the more generic derive_vars_transposed().

Usage

derive_vars_atc(
  dataset,
  dataset_facm,
  by_vars = exprs(!!!get_admiral_option("subject_keys"), CMREFID = FAREFID),
  id_vars = NULL,
  value_var = FASTRESC
)

Arguments

dataset

Input dataset

The variables specified by the by_vars argument are expected to be in the dataset.

dataset_facm

FACM dataset

The variables specified by the by_vars and value_var parameters, FAGRPID and FATESTCD are required

by_vars

Grouping variables

Keys used to merge dataset_facm with dataset.

id_vars

ID variables

Variables (excluding by_vars) that uniquely identify each observation in dataset_merge.

Permitted Values: list of variables created by exprs() e.g. exprs(USUBJID, VISIT)

value_var

The variable of dataset_facm containing the values of the transposed variables

Default: FASTRESC

Value

The input dataset with ATC variables added

See also

OCCDS Functions: derive_var_trtemfl(), derive_vars_query(), get_terms_from_db()

Examples

library(tibble)

cm <- tribble(
  ~STUDYID,  ~USUBJID,       ~CMGRPID, ~CMREFID,  ~CMDECOD,
  "STUDY01", "BP40257-1001", "14",     "1192056", "PARACETAMOL",
  "STUDY01", "BP40257-1001", "18",     "2007001", "SOLUMEDROL",
  "STUDY01", "BP40257-1002", "19",     "2791596", "SPIRONOLACTONE"
)
facm <- tribble(
  ~STUDYID,  ~USUBJID,       ~FAGRPID, ~FAREFID,  ~FATESTCD,  ~FASTRESC,
  "STUDY01", "BP40257-1001", "1",      "1192056", "CMATC1CD", "N",
  "STUDY01", "BP40257-1001", "1",      "1192056", "CMATC2CD", "N02",
  "STUDY01", "BP40257-1001", "1",      "1192056", "CMATC3CD", "N02B",
  "STUDY01", "BP40257-1001", "1",      "1192056", "CMATC4CD", "N02BE",
  "STUDY01", "BP40257-1001", "1",      "2007001", "CMATC1CD", "D",
  "STUDY01", "BP40257-1001", "1",      "2007001", "CMATC2CD", "D10",
  "STUDY01", "BP40257-1001", "1",      "2007001", "CMATC3CD", "D10A",
  "STUDY01", "BP40257-1001", "1",      "2007001", "CMATC4CD", "D10AA",
  "STUDY01", "BP40257-1001", "2",      "2007001", "CMATC1CD", "D",
  "STUDY01", "BP40257-1001", "2",      "2007001", "CMATC2CD", "D07",
  "STUDY01", "BP40257-1001", "2",      "2007001", "CMATC3CD", "D07A",
  "STUDY01", "BP40257-1001", "2",      "2007001", "CMATC4CD", "D07AA",
  "STUDY01", "BP40257-1001", "3",      "2007001", "CMATC1CD", "H",
  "STUDY01", "BP40257-1001", "3",      "2007001", "CMATC2CD", "H02",
  "STUDY01", "BP40257-1001", "3",      "2007001", "CMATC3CD", "H02A",
  "STUDY01", "BP40257-1001", "3",      "2007001", "CMATC4CD", "H02AB",
  "STUDY01", "BP40257-1002", "1",      "2791596", "CMATC1CD", "C",
  "STUDY01", "BP40257-1002", "1",      "2791596", "CMATC2CD", "C03",
  "STUDY01", "BP40257-1002", "1",      "2791596", "CMATC3CD", "C03D",
  "STUDY01", "BP40257-1002", "1",      "2791596", "CMATC4CD", "C03DA"
)

derive_vars_atc(cm, facm)
#> Warning: Values from `FASTRESC` are not uniquely identified; output will contain
#> list-cols.
#> • Use `values_fn = list` to suppress this warning.
#> • Use `values_fn = {summary_fun}` to summarise duplicates.
#> • Use the following dplyr code to identify duplicates.
#>   {data} |>
#>   dplyr::summarise(n = dplyr::n(), .by = c(STUDYID, USUBJID, FAREFID,
#>   FATESTCD)) |>
#>   dplyr::filter(n > 1L)
#> # A tibble: 3 × 9
#>   STUDYID USUBJID      CMGRPID CMREFID CMDECOD       ATC1CD ATC2CD ATC3CD ATC4CD
#>   <chr>   <chr>        <chr>   <chr>   <chr>         <list> <list> <list> <list>
#> 1 STUDY01 BP40257-1001 14      1192056 PARACETAMOL   <chr>  <chr>  <chr>  <chr> 
#> 2 STUDY01 BP40257-1001 18      2007001 SOLUMEDROL    <chr>  <chr>  <chr>  <chr> 
#> 3 STUDY01 BP40257-1002 19      2791596 SPIRONOLACTO… <chr>  <chr>  <chr>  <chr>