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Add indication column(s) to a dataset

Source: R/add_ind.R
add_ind.Rd

[Experimental] Creates indication columns. in vigibase datasets (demo, link, adr, drug, or ind).

Usage

add_ind(.data, i_list, i_names = names(i_list), drug_data, ind_data)

Arguments

.data

The dataset used to identify individual reports (usually, it is demo)

i_list

A named list of indication terms. See Details.

i_names

A character vector. Names for indication columns (must be the same length as i_list), default to names(i_list)

drug_data

A data.frame containing the drug data (usually, it is drug)

ind_data

A data.frame containing the indication data (usually, it is ind)

Value

A dataset with the new indication columns. Each element of i_names will add a column with the same name in .data. The value can be

  • 0 The corresponding indication is absent.

  • 1 The indication is present in the case if .data is demo or adr, or "this row correspond to this indication", if .data is drug, link or ind).

  • NA There is no indication data for this case / drug.

Details

Indication terms are issued from either MedDRA or International Classification of Diseases (ICD) - you need to use both dictionaries, should you wish to capture all terms related to a specific disease. Indication terms are not translated into codes in VigiBase ECL, unlike drug or adr terms. Therefore, there is no get_* step to collect such codes. The terms are passed directly to i_list, which should still be a named list containing indication terms.

See also

add_adr(), add_drug()

Examples


# Set up a list of indication terms

i_list <-
  list(
    melanoma = c("Malignant melanoma", "Metastatic malignant melanoma"),
    lung_cancer = c("Non-small cell lung cancer", "Lung adenocarcinoma")
    )

 demo <-
   demo_ |>
   add_ind(i_list,
           drug_data = drug_,
           ind_data  = ind_)
#> ℹ `.data` detected as `demo` table.

 demo |> desc_facvar(names(i_list))
#> # A tibble: 4 × 4
#>   var         level value         n_avail
#>   <chr>       <chr> <chr>           <int>
#> 1 melanoma    0     574/660 (87%)     660
#> 2 melanoma    1     86/660 (13%)      660
#> 3 lung_cancer 0     582/660 (88%)     660
#> 4 lung_cancer 1     78/660 (12%)      660