R/main.R
In ohdsi-studies/TkrPredictSimple: Add the title of the package here
Defines functions
execute
Documented in
execute
# Copyright 2020 Observational Health Data Sciences and Informatics
#
# This file is part of CovidVulnerabilityIndex
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#' Execute the Study
#'
#' @details
#' This function executes the CovidVulnerabilityIndex Study.
#'
#' @param connectionDetails An object of type \code{connectionDetails} as created using the
#' \code{\link[DatabaseConnector]{createConnectionDetails}} function in the
#' DatabaseConnector package.
#' @param usePackageCohorts Whether to use the T and O cohorts in the package
#' @param newTargetCohortId The cohort id of a new target cohort (must be generated already)
#' @param newTargetCohortName The name of the new target cohort
#' @param newOutcomeCohortId The cohort id of a new outcome (must be generated already)
#' @param newOutcomeCohortName The name of the new outcome cohort
#' @param newCohortDatabaseSchema Schema name where the new cohorts are stored. Note that for SQL Server,
#' this should include both the database and schema name, for example 'cdm_data.dbo'.
#' @param newCohortTable The name of the table that contains the target population and outcome
#' cohorts.
#' @param cdmDatabaseSchema Schema name where your patient-level data in OMOP CDM format resides.
#' Note that for SQL Server, this should include both the database and
#' schema name, for example 'cdm_data.dbo'.
#' @param cdmDatabaseName Shareable name of the database
#' @param cohortDatabaseSchema Schema name where the cohorts and covariates are created. You will need to have
#' write priviliges in this schema. Note that for SQL Server, this should
#' include both the database and schema name, for example 'cdm_data.dbo'.
#' @param cohortTable The name of the table that will be created in the work database schema.
#' This table will hold the target, outcome and variable cohorts used in this study.
#' @param oracleTempSchema Should be used in Oracle to specify a schema where the user has write
#' priviliges for storing temporary tables.
#' @param sampleSize How many patients to sample from the target population
#' @param riskWindowStart The start of the risk window (in days) relative to the startAnchor.
#' @param startAnchor The anchor point for the start of the risk window. Can be "cohort start" or "cohort end".
#' @param riskWindowEnd The end of the risk window (in days) relative to the endAnchor parameter
#' @param endAnchor The anchor point for the end of the risk window. Can be "cohort start" or "cohort end".
#' @param firstExposureOnly Should only the first exposure per subject be included? Note that this is typically done in the createStudyPopulation function,
#' @param removeSubjectsWithPriorOutcome Remove subjects that have the outcome prior to the risk window start?
#' @param priorOutcomeLookback How many days should we look back when identifying prior outcomes?
#' @param requireTimeAtRisk Should subject without time at risk be removed?
#' @param minTimeAtRisk The minimum number of days at risk required to be included
#' @param includeAllOutcomes (binary) indicating whether to include people with outcomes who are not observed for the whole at risk period
#' @param endDay The end day relative to index for the custom covariates (default is -1)
#' @param outputFolder Name of local folder to place results; make sure to use forward slashes
#' (/). Do not use a folder on a network drive since this greatly impacts
#' performance.
#' @param createCohorts Create the cohortTable table with the cohorts
#' @param predictTkrSimple Run the model that predicts 90 day risk of mortality following TKR
#' @param packageResults Should results be packaged for later sharing?
#' @param minCellCount The minimum number of subjects contributing to a count before it can be included
#' in packaged results.
#' @param verbosity Sets the level of the verbosity. If the log level is at or higher in priority than the logger threshold, a message will print. The levels are:
#' \itemize{
#' \item{DEBUG}{Highest verbosity showing all debug statements}
#' \item{TRACE}{Showing information about start and end of steps}
#' \item{INFO}{Show informative information (Default)}
#' \item{WARN}{Show warning messages}
#' \item{ERROR}{Show error messages}
#' \item{FATAL}{Be silent except for fatal errors}
#' }
#' @param cdmVersion The version of the common data model
#'
#' @examples
#' \dontrun{
#' connectionDetails <- createConnectionDetails(dbms = "postgresql",
#' user = "joe",
#' password = "secret",
#' server = "myserver")
#'
#' execute(connectionDetails,
#' cdmDatabaseSchema = "cdm_data",
#' cdmDatabaseName = 'shareable name of the database'
#' cohortDatabaseSchema = "study_results",
#' cohortTable = "cohort",
#' outcomeId = 1,
#' oracleTempSchema = NULL,
#' riskWindowStart = 1,
#' startAnchor = 'cohort start',
#' riskWindowEnd = 365,
#' endAnchor = 'cohort start',
#' outputFolder = "c:/temp/study_results",
#' createCohorts = T,
#' predictTkrSimple = T,
#' packageResults = F,
#' minCellCount = 10,
#' verbosity = "INFO",
#' cdmVersion = 5)
#' }
#'
#' @export
execute <- function(connectionDetails,
usePackageCohorts = T,
newTargetCohortId = NULL,
newTargetCohortName = '',
newOutcomeCohortId = NULL,
newOutcomeCohortName = '',
newCohortDatabaseSchema = NULL,
newCohortTable = NULL,
cdmDatabaseSchema,
cdmDatabaseName = 'friendly database name',
cohortDatabaseSchema = cdmDatabaseSchema,
cohortTable = "cohort",
oracleTempSchema = cohortDatabaseSchema,
sampleSize = NULL,
riskWindowStart = 0,
startAnchor = 'cohort start',
riskWindowEnd = 30,
endAnchor = 'cohort start',
firstExposureOnly = F,
removeSubjectsWithPriorOutcome = F,
priorOutcomeLookback = 99999,
requireTimeAtRisk = F,
minTimeAtRisk = 1,
includeAllOutcomes = T,
endDay = -1,
outputFolder,
createCohorts = F,
runValidation = F,
predictTkrSimple = F,
packageResults = F,
minCellCount = 10,
verbosity = "INFO",
cdmVersion = 5) {
library(dplyr)
standardCovariates <- FeatureExtraction::createCovariateSettings(useDemographicsAgeGroup = T,
useDemographicsGender = T,
excludedCovariateConceptIds = 8532 )
if(usePackageCohorts){
if(!is.null(newTargetCohortId) | !is.null(newOutcomeCohortId)){
warning('Input new ids but also said to use package cohorts - new ids will be ignored...')
}
}
if (!file.exists(file.path(outputFolder,cdmDatabaseName)))
dir.create(file.path(outputFolder,cdmDatabaseName), recursive = TRUE)
ParallelLogger::addDefaultFileLogger(file.path(outputFolder,cdmDatabaseName, "log.txt"))
if (createCohorts) {
ParallelLogger::logInfo("Creating cohorts")
createCohorts(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
usePackageCohorts = usePackageCohorts,
newTargetCohortId = newTargetCohortId,
newOutcomeCohortId = newOutcomeCohortId,
newCohortDatabaseSchema = newCohortDatabaseSchema,
newCohortTable = newCohortTable,
oracleTempSchema = oracleTempSchema,
outputFolder = file.path(outputFolder, cdmDatabaseName))
}
studyAnalyses <- getSettings(predictTkrSimple = predictTkrSimple,
usePackageCohorts = usePackageCohorts)
if( nrow(studyAnalyses)!=0){
for(k in 1:nrow(studyAnalyses)){
sa <- studyAnalyses[k,]
result <- predictSimple(connectionDetails = connectionDetails,
cohortId = sa$cohortId,
outcomeIds = sa$outcomeId,
model = sa$model,
analysisId = sa$analysisId,
studyStartDate = sa$studyStartDate,
studyEndDate = sa$studyEndDate,
cdmDatabaseSchema = cdmDatabaseSchema,
cdmDatabaseName = cdmDatabaseName,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
oracleTempSchema = oracleTempSchema,
standardCovariates = standardCovariates,
endDay = -1,
sampleSize = sampleSize,
cdmVersion = cdmVersion,
riskWindowStart = riskWindowStart,
startAnchor = startAnchor,
riskWindowEnd = riskWindowEnd,
endAnchor = endAnchor,
firstExposureOnly = firstExposureOnly,
removeSubjectsWithPriorOutcome = removeSubjectsWithPriorOutcome,
priorOutcomeLookback = priorOutcomeLookback,
requireTimeAtRisk = requireTimeAtRisk,
minTimeAtRisk = minTimeAtRisk,
includeAllOutcomes = includeAllOutcomes)
if(!is.null(result)){
if(!dir.exists(file.path(outputFolder,cdmDatabaseName, paste0('Analysis_',sa$analysisId)))){
dir.create(file.path(outputFolder,cdmDatabaseName,paste0('Analysis_',sa$analysisId)), recursive = T)
}
ParallelLogger::logInfo("Saving results")
saveRDS(result, file.path(outputFolder,cdmDatabaseName,paste0('Analysis_',sa$analysisId),'validationResult.rds'))
ParallelLogger::logInfo(paste0("Results saved to:",file.path(outputFolder,cdmDatabaseName,paste0('Analysis_',sa$analysisId),'validationResults.rds')))
}
}
}
if(runValidation){
ParallelLogger::logInfo("Validating Models")
# for each model externally validate
analysesLocation <- system.file("plp_models",
package = "oxfordKneeValidation")
val <- PatientLevelPrediction::evaluateMultiplePlp(analysesLocation = analysesLocation,
outputLocation = outputFolder,
connectionDetails = connectionDetails,
validationSchemaTarget = cohortDatabaseSchema,
validationSchemaOutcome = cohortDatabaseSchema,
validationSchemaCdm = cdmDatabaseSchema,
oracleTempSchema = oracleTempSchema,
databaseNames = cdmDatabaseName,
validationTableTarget = cohortTable,
validationTableOutcome = cohortTable,
sampleSize = sampleSize,
verbosity = verbosity)
}
if (packageResults) {
ParallelLogger::logInfo("Packaging results")
packageResults(outputFolder = outputFolder,
cdmDatabaseName = cdmDatabaseName,
minCellCount = minCellCount)
}
return(TRUE)
}
ohdsi-studies/TkrPredictSimple documentation built on Sept. 10, 2020, 8:17 p.m.
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Defines functions execute
Documented in execute
# Copyright 2020 Observational Health Data Sciences and Informatics
#
# This file is part of CovidVulnerabilityIndex
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#' Execute the Study
#'
#' @details
#' This function executes the CovidVulnerabilityIndex Study.
#'
#' @param connectionDetails An object of type \code{connectionDetails} as created using the
#' \code{\link[DatabaseConnector]{createConnectionDetails}} function in the
#' DatabaseConnector package.
#' @param usePackageCohorts Whether to use the T and O cohorts in the package
#' @param newTargetCohortId The cohort id of a new target cohort (must be generated already)
#' @param newTargetCohortName The name of the new target cohort
#' @param newOutcomeCohortId The cohort id of a new outcome (must be generated already)
#' @param newOutcomeCohortName The name of the new outcome cohort
#' @param newCohortDatabaseSchema Schema name where the new cohorts are stored. Note that for SQL Server,
#' this should include both the database and schema name, for example 'cdm_data.dbo'.
#' @param newCohortTable The name of the table that contains the target population and outcome
#' cohorts.
#' @param cdmDatabaseSchema Schema name where your patient-level data in OMOP CDM format resides.
#' Note that for SQL Server, this should include both the database and
#' schema name, for example 'cdm_data.dbo'.
#' @param cdmDatabaseName Shareable name of the database
#' @param cohortDatabaseSchema Schema name where the cohorts and covariates are created. You will need to have
#' write priviliges in this schema. Note that for SQL Server, this should
#' include both the database and schema name, for example 'cdm_data.dbo'.
#' @param cohortTable The name of the table that will be created in the work database schema.
#' This table will hold the target, outcome and variable cohorts used in this study.
#' @param oracleTempSchema Should be used in Oracle to specify a schema where the user has write
#' priviliges for storing temporary tables.
#' @param sampleSize How many patients to sample from the target population
#' @param riskWindowStart The start of the risk window (in days) relative to the startAnchor.
#' @param startAnchor The anchor point for the start of the risk window. Can be "cohort start" or "cohort end".
#' @param riskWindowEnd The end of the risk window (in days) relative to the endAnchor parameter
#' @param endAnchor The anchor point for the end of the risk window. Can be "cohort start" or "cohort end".
#' @param firstExposureOnly Should only the first exposure per subject be included? Note that this is typically done in the createStudyPopulation function,
#' @param removeSubjectsWithPriorOutcome Remove subjects that have the outcome prior to the risk window start?
#' @param priorOutcomeLookback How many days should we look back when identifying prior outcomes?
#' @param requireTimeAtRisk Should subject without time at risk be removed?
#' @param minTimeAtRisk The minimum number of days at risk required to be included
#' @param includeAllOutcomes (binary) indicating whether to include people with outcomes who are not observed for the whole at risk period
#' @param endDay The end day relative to index for the custom covariates (default is -1)
#' @param outputFolder Name of local folder to place results; make sure to use forward slashes
#' (/). Do not use a folder on a network drive since this greatly impacts
#' performance.
#' @param createCohorts Create the cohortTable table with the cohorts
#' @param predictTkrSimple Run the model that predicts 90 day risk of mortality following TKR
#' @param packageResults Should results be packaged for later sharing?
#' @param minCellCount The minimum number of subjects contributing to a count before it can be included
#' in packaged results.
#' @param verbosity Sets the level of the verbosity. If the log level is at or higher in priority than the logger threshold, a message will print. The levels are:
#' \itemize{
#' \item{DEBUG}{Highest verbosity showing all debug statements}
#' \item{TRACE}{Showing information about start and end of steps}
#' \item{INFO}{Show informative information (Default)}
#' \item{WARN}{Show warning messages}
#' \item{ERROR}{Show error messages}
#' \item{FATAL}{Be silent except for fatal errors}
#' }
#' @param cdmVersion The version of the common data model
#'
#' @examples
#' \dontrun{
#' connectionDetails <- createConnectionDetails(dbms = "postgresql",
#' user = "joe",
#' password = "secret",
#' server = "myserver")
#'
#' execute(connectionDetails,
#' cdmDatabaseSchema = "cdm_data",
#' cdmDatabaseName = 'shareable name of the database'
#' cohortDatabaseSchema = "study_results",
#' cohortTable = "cohort",
#' outcomeId = 1,
#' oracleTempSchema = NULL,
#' riskWindowStart = 1,
#' startAnchor = 'cohort start',
#' riskWindowEnd = 365,
#' endAnchor = 'cohort start',
#' outputFolder = "c:/temp/study_results",
#' createCohorts = T,
#' predictTkrSimple = T,
#' packageResults = F,
#' minCellCount = 10,
#' verbosity = "INFO",
#' cdmVersion = 5)
#' }
#'
#' @export
execute <- function(connectionDetails,
usePackageCohorts = T,
newTargetCohortId = NULL,
newTargetCohortName = '',
newOutcomeCohortId = NULL,
newOutcomeCohortName = '',
newCohortDatabaseSchema = NULL,
newCohortTable = NULL,
cdmDatabaseSchema,
cdmDatabaseName = 'friendly database name',
cohortDatabaseSchema = cdmDatabaseSchema,
cohortTable = "cohort",
oracleTempSchema = cohortDatabaseSchema,
sampleSize = NULL,
riskWindowStart = 0,
startAnchor = 'cohort start',
riskWindowEnd = 30,
endAnchor = 'cohort start',
firstExposureOnly = F,
removeSubjectsWithPriorOutcome = F,
priorOutcomeLookback = 99999,
requireTimeAtRisk = F,
minTimeAtRisk = 1,
includeAllOutcomes = T,
endDay = -1,
outputFolder,
createCohorts = F,
runValidation = F,
predictTkrSimple = F,
packageResults = F,
minCellCount = 10,
verbosity = "INFO",
cdmVersion = 5) {
library(dplyr)
standardCovariates <- FeatureExtraction::createCovariateSettings(useDemographicsAgeGroup = T,
useDemographicsGender = T,
excludedCovariateConceptIds = 8532 )
if(usePackageCohorts){
if(!is.null(newTargetCohortId) | !is.null(newOutcomeCohortId)){
warning('Input new ids but also said to use package cohorts - new ids will be ignored...')
}
}
if (!file.exists(file.path(outputFolder,cdmDatabaseName)))
dir.create(file.path(outputFolder,cdmDatabaseName), recursive = TRUE)
ParallelLogger::addDefaultFileLogger(file.path(outputFolder,cdmDatabaseName, "log.txt"))
if (createCohorts) {
ParallelLogger::logInfo("Creating cohorts")
createCohorts(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
usePackageCohorts = usePackageCohorts,
newTargetCohortId = newTargetCohortId,
newOutcomeCohortId = newOutcomeCohortId,
newCohortDatabaseSchema = newCohortDatabaseSchema,
newCohortTable = newCohortTable,
oracleTempSchema = oracleTempSchema,
outputFolder = file.path(outputFolder, cdmDatabaseName))
}
studyAnalyses <- getSettings(predictTkrSimple = predictTkrSimple,
usePackageCohorts = usePackageCohorts)
if( nrow(studyAnalyses)!=0){
for(k in 1:nrow(studyAnalyses)){
sa <- studyAnalyses[k,]
result <- predictSimple(connectionDetails = connectionDetails,
cohortId = sa$cohortId,
outcomeIds = sa$outcomeId,
model = sa$model,
analysisId = sa$analysisId,
studyStartDate = sa$studyStartDate,
studyEndDate = sa$studyEndDate,
cdmDatabaseSchema = cdmDatabaseSchema,
cdmDatabaseName = cdmDatabaseName,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
oracleTempSchema = oracleTempSchema,
standardCovariates = standardCovariates,
endDay = -1,
sampleSize = sampleSize,
cdmVersion = cdmVersion,
riskWindowStart = riskWindowStart,
startAnchor = startAnchor,
riskWindowEnd = riskWindowEnd,
endAnchor = endAnchor,
firstExposureOnly = firstExposureOnly,
removeSubjectsWithPriorOutcome = removeSubjectsWithPriorOutcome,
priorOutcomeLookback = priorOutcomeLookback,
requireTimeAtRisk = requireTimeAtRisk,
minTimeAtRisk = minTimeAtRisk,
includeAllOutcomes = includeAllOutcomes)
if(!is.null(result)){
if(!dir.exists(file.path(outputFolder,cdmDatabaseName, paste0('Analysis_',sa$analysisId)))){
dir.create(file.path(outputFolder,cdmDatabaseName,paste0('Analysis_',sa$analysisId)), recursive = T)
}
ParallelLogger::logInfo("Saving results")
saveRDS(result, file.path(outputFolder,cdmDatabaseName,paste0('Analysis_',sa$analysisId),'validationResult.rds'))
ParallelLogger::logInfo(paste0("Results saved to:",file.path(outputFolder,cdmDatabaseName,paste0('Analysis_',sa$analysisId),'validationResults.rds')))
}
}
}
if(runValidation){
ParallelLogger::logInfo("Validating Models")
# for each model externally validate
analysesLocation <- system.file("plp_models",
package = "oxfordKneeValidation")
val <- PatientLevelPrediction::evaluateMultiplePlp(analysesLocation = analysesLocation,
outputLocation = outputFolder,
connectionDetails = connectionDetails,
validationSchemaTarget = cohortDatabaseSchema,
validationSchemaOutcome = cohortDatabaseSchema,
validationSchemaCdm = cdmDatabaseSchema,
oracleTempSchema = oracleTempSchema,
databaseNames = cdmDatabaseName,
validationTableTarget = cohortTable,
validationTableOutcome = cohortTable,
sampleSize = sampleSize,
verbosity = verbosity)
}
if (packageResults) {
ParallelLogger::logInfo("Packaging results")
packageResults(outputFolder = outputFolder,
cdmDatabaseName = cdmDatabaseName,
minCellCount = minCellCount)
}
return(TRUE)
}
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