runSelfControlledCohort: Run self-controlled cohort

In SelfControlledCohort: Self-Controlled Cohort Population-Level Estimation

Run self-controlled cohort

Description

runSelfControlledCohort generates population-level estimation by comparing exposed and unexposed time among exposed cohort.

Usage

runSelfControlledCohort(
  connectionDetails = NULL,
  cdmDatabaseSchema,
  connection = NULL,
  tempEmulationSchema = getOption("sqlRenderTempEmulationSchema"),
  exposureIds = NULL,
  outcomeIds = NULL,
  negativeControlPairs = NULL,
  controlType = "outcome",
  exposureDatabaseSchema = cdmDatabaseSchema,
  exposureTable = "drug_era",
  outcomeDatabaseSchema = cdmDatabaseSchema,
  outcomeTable = "condition_era",
  firstExposureOnly = TRUE,
  firstOutcomeOnly = TRUE,
  minAge = "",
  maxAge = "",
  studyStartDate = "",
  studyEndDate = "",
  addLengthOfExposureExposed = TRUE,
  riskWindowStartExposed = 1,
  riskWindowEndExposed = 30,
  addLengthOfExposureUnexposed = TRUE,
  riskWindowEndUnexposed = -1,
  riskWindowStartUnexposed = -30,
  hasFullTimeAtRisk = FALSE,
  washoutPeriod = 0,
  followupPeriod = 0,
  computeThreads = getOption("strategus.SelfControlledCohort.computeThreads", default =
    parallel::detectCores() - 1),
  riskWindowsTable = "#risk_windows",
  resultsTable = "#results",
  keepResultsTables = TRUE,
  extractResults = TRUE,
  resultsDatabaseSchema = NULL,
  resultExportPath = "scc_result",
  databaseId,
  analysisId = 1,
  analysisDescription = paste("SCC analysis", analysisId),
  resultExportManager = getDefaultExportManager(resultExportPath, databaseId),
  runDiagnostics = TRUE,
  diagnostics = c("all"),
  diagnosticThresholds = getDefaultDiagnosticThresholds()
)

Arguments

connectionDetails	An R object of type connectionDetails created using the function createConnectionDetails in the DatabaseConnector package.
cdmDatabaseSchema	Name of database schema that contains the OMOP CDM and vocabulary.
connection	DatabaseConnector connection instance
tempEmulationSchema	Some database platforms like Oracle and Impala do not truly support temp tables. To emulate temp tables, provide a schema with write privileges where temp tables can be created.
exposureIds	A vector containing the drug_concept_ids or cohort_definition_ids of the exposures of interest. If empty, all exposures in the exposure table will be included.
outcomeIds	The condition_concept_ids or cohort_definition_ids of the outcomes of interest. If empty, all the outcomes in the outcome table will be included.
negativeControlPairs	A list of vectors for pairs of negative control
controlType	Calibrate effect estimates with outcome (default) or exposure controls
exposureDatabaseSchema	The name of the database schema that is the location where the exposure data used to define the exposure cohorts is available. If exposureTable = DRUG_ERA, exposureDatabaseSchema is not used by assumed to be cdmSchema. Requires read permissions to this database.
exposureTable	The tablename that contains the exposure cohorts. If exposureTable <> DRUG_ERA, then expectation is exposureTable has format of COHORT table: cohort_concept_id, SUBJECT_ID, COHORT_START_DATE, COHORT_END_DATE.
outcomeDatabaseSchema	The name of the database schema that is the location where the data used to define the outcome cohorts is available. If exposureTable = CONDITION_ERA, exposureDatabaseSchema is not used by assumed to be cdmSchema. Requires read permissions to this database.
outcomeTable	The tablename that contains the outcome cohorts. If outcomeTable <> CONDITION_OCCURRENCE, then expectation is outcomeTable has format of COHORT table: COHORT_DEFINITION_ID, SUBJECT_ID, COHORT_START_DATE, COHORT_END_DATE.
firstExposureOnly	If TRUE, only use first occurrence of each drug concept id for each person
firstOutcomeOnly	If TRUE, only use first occurrence of each condition concept id for each person.
minAge	Integer for minimum allowable age.
maxAge	Integer for maximum allowable age.
studyStartDate	Date for minimum allowable data for index exposure. Date format is 'yyyymmdd'.
studyEndDate	Date for maximum allowable data for index exposure. Date format is 'yyyymmdd'.
addLengthOfExposureExposed	If TRUE, use the duration from drugEraStart -> drugEraEnd as part of timeAtRisk.
riskWindowStartExposed	Integer of days to add to drugEraStart for start of timeAtRisk (0 to include index date, 1 to start the day after).
riskWindowEndExposed	Additional window to add to end of exposure period (if addLengthOfExposureExposed = TRUE, then add to exposure end date, else add to exposure start date).
addLengthOfExposureUnexposed	If TRUE, use the duration from exposure start -> exposure end as part of timeAtRisk looking back before exposure start.
riskWindowEndUnexposed	Integer of days to add to exposure start for end of timeAtRisk (0 to include index date, -1 to end the day before).
riskWindowStartUnexposed	Additional window to add to start of exposure period (if addLengthOfExposureUnexposed = TRUE, then add to exposure end date, else add to exposure start date).
hasFullTimeAtRisk	If TRUE, restrict to people who have full time-at-risk exposed and unexposed.
washoutPeriod	Integer to define required time observed before exposure start.
followupPeriod	Integer to define required time observed after exposure start.
computeThreads	Number of parallel threads for computing IRRs with exact confidence intervals.
riskWindowsTable	String: optionally store the risk windows in a (non-temporary) table.
resultsTable	String: optionally store the summary results (number exposed/ unexposed patients per outcome-exposure pair) in a (non-temporary) table. Note that this table does not store the rate ratios, only the values required to calculate rate ratios.
keepResultsTables	Keep the results tables in place if they exist. This allows the data set to be added to with aditional targets and outcomes. (ignored if temporary tables are used, default)
extractResults	Export results to disk. In the case of very large exposure/outcome set pairs it is often more ideal to create a permanent results table with the @resultsTable parameter and extract and calibrate small subsets on demand. Performing calibration across the full set of outcome/exposure pairs can take a significant amount of time. If set to false, no relative risk ratios will be produced.
resultsDatabaseSchema	Schema to oputput results to. Ignored if resultsTable and riskWindowsTable are temporary.
resultExportPath	Folder where result files are exported
databaseId	Unique identifier for database - required
analysisId	An integer unique to this analysis
analysisDescription	A string description of the analysis (optional)
resultExportManager	ResultModelManager::ResultExportManager instance - customize this to implement an alternative mechanism for exporting results
runDiagnostics	If TRUE, run diagnostic tests on the results
diagnostics	Character vector specifying which diagnostics to run. Options: "all", "counts", "event_dependent", "pre_exposure", "window_balance", "cohort_stability". Default is "all".
diagnosticThresholds	Named list of diagnostic thresholds. See getDefaultDiagnosticThresholds()

Details

Population-level estimation method that estimates incidence rate comparison of exposed/unexposed time within an exposed cohort. If multiple exposureIds and outcomeIds are provided, estimates will be generated for every combination of exposure and outcome.

Value

An object of type sccResults containing the results of the analysis.

References

Ryan PB, Schuemie MJ, Madigan D.Empirical performance of a self-controlled cohort method: lessons for developing a risk identification and analysis system. Drug Safety 36 Suppl1:S95-106, 2013

Examples

if (interactive()) {
# Use Eunomia synthetic database for demonstration
connectionDetails <- Eunomia::getEunomiaConnectionDetails()

result <- runSelfControlledCohort(
  connectionDetails = connectionDetails,
  cdmDatabaseSchema = "main",
  exposureIds = c(1124300),
  outcomeIds = 444382,
  outcomeTable = "condition_era",
  databaseId = "Eunomia"
)
}

SelfControlledCohort documentation built on June 17, 2026, 5:07 p.m.