CohortGenerator (version 1.0.2)

addIndicationSubsetDefinition: Add Indication Subset Definition

Description

Utility pattern for creating an indication subset from a set of target cohorts. The approach applies this subset definition to an exposure (target cohort) or set of exposures (multiple target cohorts), requiring the individual to have a history of the indication cohort overlapping the start of the first exposure. The first exposure must have the `requiredPriorObservationTime` and `requiredFollowUpTime`. If specified, the first exposure must also fall within the `studyStartDate` and `studyEndDate` and also meet the age and gender criteria.

Additionally, the R attribute of "indicationSubsetDefinitions" is attached to the cohort definition set. This can be obtained by calling `getIndicationSubsetDefinitionIds`, which should return the set of subset definition ids that are associated with indications.

Usage

addIndicationSubsetDefinition(
  cohortDefinitionSet,
  targetCohortIds,
  indicationCohortIds,
  subsetDefinitionId,
  subsetDefinitionName,
  subsetCohortNameTemplate = "@baseCohortName - @subsetDefinitionName",
  cohortCombinationOperator = "any",
  lookbackWindowStart = -99999,
  lookbackWindowEnd = 0,
  lookForwardWindowStart = 0,
  lookForwardWindowEnd = 99999,
  genderConceptIds = NULL,
  ageMin = NULL,
  ageMax = NULL,
  studyStartDate = NULL,
  studyEndDate = NULL,
  requiredPriorObservationTime = 365,
  requiredFollowUpTime = 1
)

Arguments

cohortDefinitionSet

The cohortDefinitionSet argument must be a data frame with the following columns:

cohortId

The unique integer identifier of the cohort

cohortName

The cohort's name

sql

The OHDSI-SQL used to generate the cohort

Optionally, this data frame may contain:

json

The Circe JSON representation of the cohort

targetCohortIds

Set of integer cohort IDs. Must be within the cohort definition set.

indicationCohortIds

Set of integer cohort IDs. Must be within the cohort definition set.

subsetDefinitionId

Unique integer Id of the subset definition

subsetDefinitionName

name of the subset definition (used in resulting cohort definitions)

subsetCohortNameTemplate

template string format for naming resulting cohorts

cohortCombinationOperator

Logic for multiple indication cohort IDs: any (default) or all.

lookbackWindowStart

Start of lookback period.

lookbackWindowEnd

End of lookback period.

lookForwardWindowStart

When the indication can end relative to index; default is 0.

lookForwardWindowEnd

When the indication can end relative to index; default is 9999.

genderConceptIds

Gender concepts to require

ageMin

Minimum age at target index.

ageMax

Maximum age at target index.

studyStartDate

Exclude patients with index prior to this date (format "%Y%m%d").

studyEndDate

Exclude patients with index after this date (format "%Y%m%d").

requiredPriorObservationTime

Observation time prior to index; default 365.

requiredFollowUpTime

Observation time after index; default 1.

Examples

if (FALSE) {
library(CohortGenerator)

initialSet <- getCohortDefinitionSet(
  settingsFileName = "testdata/name/Cohorts.csv",
  jsonFolder = "testdata/name/cohorts",
  sqlFolder = "testdata/name/sql/sql_server",
  cohortFileNameFormat = "%s",
  cohortFileNameValue = c("cohortName"),
  packageName = "CohortGenerator",
  verbose = FALSE
)

print(initialSet[, c("cohortId", "cohortName")])

# Subset cohorts 1 & 2 by an "indication" cohort 3:
res <- addIndicationSubsetDefinition(
  cohortDefinitionSet = initialSet,
  targetCohortIds = c(1, 2),
  indicationCohortIds = c(3),
  subsetDefinitionId = 10
)

print(res[, c("cohortId", "cohortName", "subsetParent", "subsetDefinitionId", "isSubset")])

# Get all subset definitions that were created using the addIndicationSubsetDefinition:
subsetDefinitionId <- getIndicationSubsetDefinitionIds(res)

# Filter the cohortDefinitionSet to those cohorts defined using an indication subset definition:
newCohorts <- res |>
  dplyr::filter(subsetDefinitionId == subsetDefinitionId) |>
  dplyr::select(cohortId, cohortName, subsetParent, isSubset)
print(newCohorts)
}