computePathways

Compute treatment patterns according to the specified parameters within specified cohorts.

Usage

computePathways(
  cohorts,
  cohortTableName,
  cdm = NULL,
  connectionDetails = NULL,
  cdmSchema = NULL,
  resultSchema = NULL,
  analysisId = 1,
  description = "",
  tempEmulationSchema = NULL,
  startAnchor = "startDate",
  windowStart = 0,
  endAnchor = "endDate",
  windowEnd = 0,
  minEraDuration = 0,
  splitEventCohorts = NULL,
  splitTime = NULL,
  eraCollapseSize = 30,
  combinationWindow = 30,
  minPostCombinationDuration = 30,
  filterTreatments = "First",
  maxPathLength = 5,
  overlapMethod = "truncate",
  concatTargets = TRUE
)

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

cohortTableName

(character(1))
Cohort table name.

cdm

(CDMConnector::cdm_from_con(): NULL)
Optional; Ignores connectionDetails, cdmSchema, and resultSchema.

connectionDetails

(DatabaseConnector::createConnectionDetails(): NULL)
Optional; In congruence with cdmSchema and resultSchema. Ignores cdm.

cdmSchema

(character(1): NULL)
Optional; In congruence with connectionDetails and resultSchema. Ignores cdm.

resultSchema

(character(1): NULL)
Optional; In congruence with connectionDetails and cdmSchema. Ignores cdm.

analysisId

(character(1)) Identifier for the TreatmentPatterns analysis.

description

(character(1)) Description of the analysis.

tempEmulationSchema

Schema used to emulate temp tables

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.

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

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?

Value

(Andromeda::andromeda()) andromeda object containing non-sharable patient level data outcomes.

Examples

# \donttest{
ableToRun <- all(
  require("CirceR", character.only = TRUE, quietly = TRUE),
  require("CDMConnector", character.only = TRUE, quietly = TRUE),
  require("TreatmentPatterns", character.only = TRUE, quietly = TRUE),
  require("dplyr", character.only = TRUE, quietly = TRUE)
)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

if (ableToRun) {
  library(TreatmentPatterns)
  library(CDMConnector)
  library(dplyr)

  withr::local_envvar(
    R_USER_CACHE_DIR = tempfile(),
    EUNOMIA_DATA_FOLDER = Sys.getenv("EUNOMIA_DATA_FOLDER", unset = tempfile())
  )

  tryCatch(
    {
      if (Sys.getenv("skip_eunomia_download_test") != "TRUE") {
        CDMConnector::downloadEunomiaData(overwrite = TRUE)
      }
    },
    error = function(e) NA
  )

  con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
  cdm <- cdmFromCon(con, cdmSchema = "main", writeSchema = "main")

  cohortSet <- readCohortSet(
    path = system.file(package = "TreatmentPatterns", "exampleCohorts")
  )

  cdm <- generateCohortSet(
    cdm = cdm,
    cohortSet = cohortSet,
    name = "cohort_table"
  )

  cohorts <- cohortSet %>%
    # Remove 'cohort' and 'json' columns
    select(-"cohort", -"json") %>%
    mutate(type = c("event", "event", "event", "event", "exit", "event", "event", "target")) %>%
    rename(
      cohortId = "cohort_definition_id",
      cohortName = "cohort_name",
    ) %>%
    select("cohortId", "cohortName", "type")

  outputEnv <- computePathways(
    cohorts = cohorts,
    cohortTableName = "cohort_table",
    cdm = cdm
  )

  Andromeda::close(outputEnv)
  DBI::dbDisconnect(con, shutdown = TRUE)
}
#> 
#> Download completed!
#> Creating CDM database /tmp/RtmpxXotT2/file2a80159a4fc9/GiBleed_5.3.zip
#> ℹ Generating 8 cohorts
#> ℹ Generating cohort (1/8) - acetaminophen
#> ✔ Generating cohort (1/8) - acetaminophen [365ms]
#> 
#> ℹ Generating cohort (2/8) - amoxicillin
#> ✔ Generating cohort (2/8) - amoxicillin [181ms]
#> 
#> ℹ Generating cohort (3/8) - aspirin
#> ✔ Generating cohort (3/8) - aspirin [168ms]
#> 
#> ℹ Generating cohort (4/8) - clavulanate
#> ✔ Generating cohort (4/8) - clavulanate [187ms]
#> 
#> ℹ Generating cohort (5/8) - death
#> ✔ Generating cohort (5/8) - death [128ms]
#> 
#> ℹ Generating cohort (6/8) - doxylamine
#> ✔ Generating cohort (6/8) - doxylamine [150ms]
#> 
#> ℹ Generating cohort (7/8) - penicillinv
#> ✔ Generating cohort (7/8) - penicillinv [152ms]
#> 
#> ℹ Generating cohort (8/8) - viralsinusitis
#> ✔ Generating cohort (8/8) - viralsinusitis [239ms]
#> 
#> -- Qualifying records for cohort definitions: 1, 2, 3, 4, 5, 6, 7, 8
#> 	Records: 14041
#> 	Subjects: 2693
#> -- Removing records < minEraDuration (0)
#> 	Records: 11386
#> 	Subjects: 2159
#> >> Starting on target: 8 (viralsinusitis)
#> -- Removing events outside window (startDate: 0 | endDate: 0)
#> 	Records: 8366
#> 	Subjects: 2144
#> -- splitEventCohorts
#> 	Records: 8366
#> 	Subjects: 2144
#> -- Collapsing eras, eraCollapse (30)
#> 	Records: 8366
#> 	Subjects: 2144
#> -- Iteration 1: minPostCombinationDuration (30), combinatinoWindow (30)
#> 	Records: 558
#> 	Subjects: 512
#> -- Iteration 2: minPostCombinationDuration (30), combinatinoWindow (30)
#> 	Records: 554
#> 	Subjects: 512
#> -- After Combination
#> 	Records: 554
#> 	Subjects: 512
#> -- filterTreatments (First)
#> 	Records: 553
#> 	Subjects: 512
#> -- Max path length (5)
#> 	Records: 553
#> 	Subjects: 512
#> -- treatment construction done
#> 	Records: 553
#> 	Subjects: 512
# }