Generate a set of drug cohorts based on ATC classification

Adds a new cohort table to the cdm reference with individuals who have drug exposure records that belong to the specified Anatomical Therapeutic Chemical (ATC) classification. Cohort start and end dates will be based on drug record start and end dates, respectively. Records that overlap or have fewer days between them than the specified gap era will be concatenated into a single cohort entry.

Usage

generateAtcCohortSet(
  cdm,
  name,
  atcName = NULL,
  level = c("ATC 1st"),
  doseForm = NULL,
  gapEra = 1,
  durationRange = lifecycle::deprecated(),
  imputeDuration = lifecycle::deprecated(),
  priorUseWashout = lifecycle::deprecated(),
  priorObservation = lifecycle::deprecated(),
  cohortDateRange = lifecycle::deprecated(),
  limit = lifecycle::deprecated()
)

Arguments

cdm

A cdm reference.

name

The name of the new cohort table to add to the cdm reference.

atcName

Names of ATC classification of interest.

level

ATC level. Can be one or more of "ATC 1st", "ATC 2nd", "ATC 3rd", "ATC 4th", and "ATC 5th"

doseForm

Only descendants codes with the specified dose form will be returned. If NULL, descendant codes will be returned regardless of dose form.

gapEra

Number of days between two continuous exposures to be considered in the same era. Records that have fewer days between them than this gap will be concatenated into the same cohort record.

durationRange

Deprecated.

imputeDuration

Deprecated.

priorUseWashout

Deprecated

priorObservation

Deprecated.

cohortDateRange

Deprecated.

limit

Deprecated.

Value

The function returns the cdm reference provided with the addition of the new cohort table.

Examples

# \donttest{
library(DrugUtilisation)
library(dplyr)

cdm <- mockDrugUtilisation()
#> Warning: ! 6 column in person do not match expected column type:
#> • `gender_concept_id` is numeric but expected integer
#> • `race_concept_id` is numeric but expected integer
#> • `ethnicity_concept_id` is numeric but expected integer
#> • `location_id` is numeric but expected integer
#> • `provider_id` is numeric but expected integer
#> • `care_site_id` is numeric but expected integer
#> Warning: ! 1 column in observation_period do not match expected column type:
#> • `period_type_concept_id` is numeric but expected integer
#> Warning: ! 2 column in visit_occurrence do not match expected column type:
#> • `visit_concept_id` is numeric but expected integer
#> • `visit_type_concept_id` is numeric but expected integer
#> Warning: ! 10 column in condition_occurrence do not match expected column type:
#> • `condition_concept_id` is numeric but expected integer
#> • `condition_type_concept_id` is numeric but expected integer
#> • `condition_status_concept_id` is numeric but expected integer
#> • `stop_reason` is logical but expected character
#> • `provider_id` is logical but expected integer
#> • `visit_occurrence_id` is logical but expected integer
#> • `visit_detail_id` is logical but expected integer
#> • `condition_source_value` is logical but expected character
#> • `condition_source_concept_id` is logical but expected integer
#> • `condition_status_source_value` is logical but expected character
#> Warning: ! 2 column in drug_exposure do not match expected column type:
#> • `drug_concept_id` is numeric but expected integer
#> • `drug_type_concept_id` is numeric but expected integer
#> Warning: ! 2 column in observation do not match expected column type:
#> • `observation_concept_id` is numeric but expected integer
#> • `observation_type_concept_id` is numeric but expected integer
#> Warning: ! 4 column in concept do not match expected column type:
#> • `concept_id` is numeric but expected integer
#> • `valid_start_date` is character but expected date
#> • `valid_end_date` is character but expected date
#> • `invalid_reason` is logical but expected character
#> Warning: ! 2 column in concept_relationship do not match expected column type:
#> • `concept_id_1` is numeric but expected integer
#> • `concept_id_2` is numeric but expected integer
#> Warning: ! 4 column in concept_ancestor do not match expected column type:
#> • `ancestor_concept_id` is numeric but expected integer
#> • `descendant_concept_id` is numeric but expected integer
#> • `min_levels_of_separation` is numeric but expected integer
#> • `max_levels_of_separation` is numeric but expected integer
#> Warning: ! 9 column in drug_strength do not match expected column type:
#> • `drug_concept_id` is numeric but expected integer
#> • `ingredient_concept_id` is numeric but expected integer
#> • `amount_unit_concept_id` is numeric but expected integer
#> • `numerator_unit_concept_id` is numeric but expected integer
#> • `denominator_unit_concept_id` is numeric but expected integer
#> • `box_size` is logical but expected integer
#> • `valid_start_date` is character but expected date
#> • `valid_end_date` is character but expected date
#> • `invalid_reason` is logical but expected character
#> Warning: ! 6 column in person do not match expected column type:
#> • `gender_concept_id` is numeric but expected integer
#> • `race_concept_id` is numeric but expected integer
#> • `ethnicity_concept_id` is numeric but expected integer
#> • `location_id` is numeric but expected integer
#> • `provider_id` is numeric but expected integer
#> • `care_site_id` is numeric but expected integer
#> Warning: ! 1 column in observation_period do not match expected column type:
#> • `period_type_concept_id` is numeric but expected integer

cdm <- generateAtcCohortSet(
  cdm = cdm,
  atcName = "alimentary tract and metabolism",
  name = "drugs"
)
#> Warning: ! `codelist` contains numeric values, they are casted to integers.
#> Warning: cohort_name must be snake case and have less than 100 characters, the following
#> cohorts will be renamed:
#> • A_alimentary_tract_and_metabolism -> a_alimentary_tract_and_metabolism

cdm$drugs |>
  glimpse()
#> Rows: ??
#> Columns: 4
#> Database: DuckDB v1.1.2 [unknown@Linux 6.5.0-1025-azure:R 4.4.2/:memory:]
#> $ cohort_definition_id <int> 
#> $ subject_id           <int> 
#> $ cohort_start_date    <date> 
#> $ cohort_end_date      <date> 
# }