Characterization

Characterization is part of HADES.

Introduction

Characterization is an R package for performing characterization of a target and a comparator cohort.

Features

• Compute time to event
• Compute dechallenge and rechallenge
• Computer characterization of target cohort with and without occurring in an outcome cohort during some time at risk
• Run multiple characterization analyses efficiently
• upload results to database
• export results as csv files

Examples

library(Eunomia)
library(Characterization)

connectionDetails <- Eunomia::getEunomiaConnectionDetails()
Eunomia::createCohorts(connectionDetails = connectionDetails)

targetIds <- c(1,2,4)
  outcomeIds <- c(3)

  timeToEventSettings1 <- createTimeToEventSettings(
    targetIds = 1,
    outcomeIds = c(3,4)
  )
  timeToEventSettings2 <- createTimeToEventSettings(
    targetIds = 2,
    outcomeIds = c(3,4)
  )

  dechallengeRechallengeSettings <- createDechallengeRechallengeSettings(
    targetIds = targetIds,
    outcomeIds = outcomeIds,
    dechallengeStopInterval = 30,
    dechallengeEvaluationWindow = 31
  )

  aggregateCovariateSettings1 <- createAggregateCovariateSettings(
    targetIds = targetIds,
    outcomeIds = outcomeIds,
    riskWindowStart = 1,
    startAnchor = 'cohort start',
    riskWindowEnd = 365,
    endAnchor = 'cohort start',
    covariateSettings = FeatureExtraction::createCovariateSettings(
      useDemographicsGender = T,
      useDemographicsAge = T,
      useDemographicsRace = T
    )
  )

  aggregateCovariateSettings2 <- createAggregateCovariateSettings(
    targetIds = targetIds,
    outcomeIds = outcomeIds,
    riskWindowStart = 1,
    startAnchor = 'cohort start',
    riskWindowEnd = 365,
    endAnchor = 'cohort start',
    covariateSettings = FeatureExtraction::createCovariateSettings(
      useConditionOccurrenceLongTerm = T
    )
  )

  characterizationSettings <- createCharacterizationSettings(
    timeToEventSettings = list(
      timeToEventSettings1,
      timeToEventSettings2
      ),
    dechallengeRechallengeSettings = list(
      dechallengeRechallengeSettings
    ),
    aggregateCovariateSettings = list(
      aggregateCovariateSettings1,
      aggregateCovariateSettings2
      )
  )
  
runCharacterizationAnalyses(
  connectionDetails = connectionDetails,
  cdmDatabaseSchema = 'main',
  targetDatabaseSchema = 'main',
  targetTable = 'cohort',
  outcomeDatabaseSchema = 'main',
  outcomeTable = 'cohort',
  characterizationSettings = characterizationSettings,   
  outputDirectory = file.path(tempdir(), 'example', 'results'),
  executionPath = file.path(tempdir(), 'example', 'execution'),
  csvFilePrefix = 'c_',
  databaseId = 'Eunomia'
)

Technology

Characterization is an R package.

System Requirements

Requires R (version 4.0.0 or higher). Libraries used in Characterization require Java.

Installation

1. See the instructions here for configuring your R environment, including Java.

2. In R, use the following commands to download and install Characterization:

install.packages("remotes")
remotes::install_github("ohdsi/Characterization")

User Documentation

Documentation can be found on the package website.

Support

• Developer questions/comments/feedback: OHDSI Forum
• We use the GitHub issue tracker for all bugs/issues/enhancements

Contributing

Read here how you can contribute to this package.

License

Characterization is licensed under Apache License 2.0

Development

Characterization is being developed in R Studio.