getPlpData: Extract the patient level prediction data from the server

In OHDSI/PatientLevelPrediction: Develop Clinical Prediction Models Using the Common Data Model

Extract the patient level prediction data from the server

Description

This function executes a large set of SQL statements against the database in OMOP CDM format to extract the data needed to perform the analysis.

Usage

getPlpData(databaseDetails, covariateSettings, restrictPlpDataSettings = NULL)

Arguments

databaseDetails	The cdm database details created using createDatabaseDetails()
covariateSettings	An object of type covariateSettings or a list of such objects as created using the createCovariateSettings function in the FeatureExtraction package.
restrictPlpDataSettings	Extra settings to apply to the target population while extracting data. Created using createRestrictPlpDataSettings(). This is optional.

Details

Based on the arguments, the at risk cohort data is retrieved, as well as outcomes occurring in these subjects. The at risk cohort is identified through user-defined cohorts in a cohort table either inside the CDM instance or in a separate schema. Similarly, outcomes are identified through user-defined cohorts in a cohort table either inside the CDM instance or in a separate schema. Covariates are automatically extracted from the appropriate tables within the CDM. If you wish to exclude concepts from covariates you will need to manually add the concept_ids and descendants to the excludedCovariateConceptIds of the covariateSettings argument.

Value

'r plpDataObjectDoc()'

Examples

 
 # use Eunomia database
 connectionDetails <- Eunomia::getEunomiaConnectionDetails()
 Eunomia::createCohorts(connectionDetails)
 outcomeId <- 3 # GIbleed
 databaseDetails <- createDatabaseDetails(
   connectionDetails = connectionDetails,
   cdmDatabaseSchema = "main",
   cdmDatabaseName = "main",
   cohortDatabaseSchema = "main",
   cohortTable = "cohort",
   outcomeDatabaseSchema = "main",
   outcomeTable = "cohort",
   targetId = 1,
   outcomeIds = outcomeId,
   cdmVersion = 5
 )

 covariateSettings <- FeatureExtraction::createCovariateSettings(
   useDemographicsAge = TRUE,
   useDemographicsGender = TRUE,
   useConditionOccurrenceAnyTimePrior = TRUE
 )

 plpData <- getPlpData(
   databaseDetails = databaseDetails,
   covariateSettings = covariateSettings,
   restrictPlpDataSettings = createRestrictPlpDataSettings()
 )

OHDSI/PatientLevelPrediction documentation built on Feb. 14, 2025, 9:44 a.m.