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Evaluate phenotypes with the DARWIN TreatmentPatterns Package

Source: R/Module-TreatmentPatterns.R
TreatmentPatternsModule.Rd

Characterization and description of patterns of events (cohorts). against the OMOP Common Data Model.

Super class

Strategus::StrategusModule -> TreatmentPatternsModule

Public fields

tablePrefix

The table prefix to append to the results tables

Methods

Public methods

Inherited methods

Method new()

Initialize the module

Usage

TreatmentPatternsModule$new()

Method execute()

Execute Treatment Patterns

Usage

TreatmentPatternsModule$execute(
  connectionDetails,
  analysisSpecifications,
  executionSettings
)

Arguments

connectionDetails

An object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

analysisSpecifications

An object of type AnalysisSpecifications as created by createEmptyAnalysisSpecificiations().

analysisSpecifications

An object of type AnalysisSpecifications as created by createEmptyAnalysisSpecificiations().

executionSettings

An object of type ExecutionSettings as created by createCdmExecutionSettings() or createResultsExecutionSettings().

Method createResultsDataModel()

Create the results data model for the module

Usage

TreatmentPatternsModule$createResultsDataModel(
  resultsConnectionDetails,
  resultsDatabaseSchema,
  tablePrefix = self$tablePrefix
)

Arguments

resultsConnectionDetails

The connection details to the results database which is an object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

resultsConnectionDetails

The connection details to the results database which is an object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

resultsDatabaseSchema

The schema in the results database that holds the results data model.

tablePrefix

A prefix to apply to the database table names (optional).

tablePrefix

A prefix to apply to the database table names (optional).

Method getResultsDataModelSpecification()

Get the results data model specification for the module

Usage

TreatmentPatternsModule$getResultsDataModelSpecification(tablePrefix = "")

Arguments

tablePrefix

A prefix to apply to the database table names (optional).

tablePrefix

A prefix to apply to the database table names (optional).

Method uploadResults()

Upload the results for TreatmentPatterns

Usage

TreatmentPatternsModule$uploadResults(
  resultsConnectionDetails,
  analysisSpecifications,
  resultsDataModelSettings
)

Arguments

resultsConnectionDetails

The connection details to the results database which is an object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

resultsConnectionDetails

The connection details to the results database which is an object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

analysisSpecifications

An object of type AnalysisSpecifications as created by createEmptyAnalysisSpecificiations().

analysisSpecifications

An object of type AnalysisSpecifications as created by createEmptyAnalysisSpecificiations().

resultsDataModelSettings

The results data model settings as created using [@seealso createResultsDataModelSettings()]

Method createModuleSpecifications()

Creates the TreatmentPatternsnModule Specifications

Usage

TreatmentPatternsModule$createModuleSpecifications(
  cohorts,
  includeTreatments = NULL,
  indexDateOffset = NULL,
  minEraDuration = 0,
  splitEventCohorts = NULL,
  splitTime = NULL,
  eraCollapseSize = 30,
  combinationWindow = 30,
  minPostCombinationDuration = 30,
  filterTreatments = "First",
  maxPathLength = 5,
  ageWindow = 5,
  minCellCount = 1,
  censorType = "minCellCount",
  overlapMethod = "truncate",
  concatTargets = TRUE,
  startAnchor = "startDate",
  windowStart = 0,
  endAnchor = "endDate",
  windowEnd = 0
)

Arguments

cohorts

(data.frame())
Data frame containing the following columns and data types:

cohortId numeric(1)

Cohort ID's of the cohorts to be used in the cohort table.

cohortName character(1)

Cohort names of the cohorts to be used in the cohort table.

type character(1) ["target", "event', "exit"]

Cohort type, describing if the cohort is a target, event, or exit cohort

includeTreatments

(character(1): "startDate")
DEPRECATED

"startDate"

Include treatments after the target cohort start date and onwards.

"endDate"

Include treatments before target cohort end date and before.

indexDateOffset

(integer(1): 0)
DEPRECATED Offset the index date of the Target cohort.

minEraDuration

(integer(1): 0)
Minimum time an event era should last to be included in analysis

splitEventCohorts

(character(n): "")
Specify event cohort to split in acute (< X days) and therapy (>= X days)

splitTime

(integer(1): 30)
Specify number of days (X) at which each of the split event cohorts should be split in acute and therapy

eraCollapseSize

(integer(1): 30)
Window of time between which two eras of the same event cohort are collapsed into one era

combinationWindow

(integer(1): 30)
Window of time two event cohorts need to overlap to be considered a combination treatment

minPostCombinationDuration

(integer(1): 30)
Minimum time an event era before or after a generated combination treatment should last to be included in analysis

filterTreatments

(character(1): "First" ["first", "Changes", "all"])
Select first occurrence of (‘First’); changes between (‘Changes’); or all event cohorts (‘All’).

maxPathLength

(integer(1): 5)
Maximum number of steps included in treatment pathway

ageWindow

(integer(n): 10)
Number of years to bin age groups into. It may also be a vector of integers. I.e. c(0, 18, 150) which will results in age group 0-18 which includes subjects < 19. And age group 18-150 which includes subjects > 18.

minCellCount

(integer(1): 5)
Minimum count required per pathway. Censors data below x as <x. This minimum value will carry over to the sankey diagram and sunburst plot.

censorType

(character(1))

"minCellCount"

Censors pathways <minCellCount to minCellCount.

"remove"

Censors pathways <minCellCount by removing them completely.

"mean"

Censors pathways <minCellCount to the mean of all frequencies below minCellCount

overlapMethod

(character(1): "truncate") Method to decide how to deal with overlap that is not significant enough for combination. "keep" will keep the dates as is. "truncate" truncates the first occurring event to the start date of the next event.

concatTargets

(logical(1): TRUE) Should multiple target cohorts for the same person be concatenated or not?

startAnchor

(character(1): "startDate") Start date anchor. One of: "startDate", "endDate"

windowStart

(numeric(1): 0) Offset for startAnchor in days.

endAnchor

(character(1): "endDate") End date anchor. One of: "startDate", "endDate"

windowEnd

(numeric(1): 0) Offset for endAnchor in days.

Method validateModuleSpecifications()

Validate the module specifications

Usage

TreatmentPatternsModule$validateModuleSpecifications(moduleSpecifications)

Arguments

moduleSpecifications

The CohortMethod module specifications

Method clone()

The objects of this class are cloneable with this method.

Usage

TreatmentPatternsModule$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.