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For this example we’ll use the Eunomia synthetic data from the CDMConnector package.
con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
cdm <- CDMConnector::cdmFromCon(con, cdmSchema = "main",
writeSchema = "main", writePrefix = "my_study_")
Let’s start by creating two drug cohorts, one for users of diclofenac and another for users of acetaminophen.
cdm$medications <- conceptCohort(cdm = cdm,
conceptSet = list("diclofenac" = 1124300,
"acetaminophen" = 1127433),
name = "medications")
cohortCount(cdm$medications)
#> # A tibble: 2 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
#> 1 1 9365 2580
#> 2 2 830 830
settings(cdm$medications)
#> # A tibble: 2 × 4
#> cohort_definition_id cohort_name cdm_version vocabulary_version
#> <int> <chr> <chr> <chr>
#> 1 1 acetaminophen 5.3 v5.0 18-JAN-19
#> 2 2 diclofenac 5.3 v5.0 18-JAN-19
We can stratify cohorts based on specified columns using the function
stratifyCohorts()
. In this example, let’s stratify the
medications cohort by age and sex.
cdm$stratified <- cdm$medications |>
addAge(ageGroup = list("Child" = c(0,17), "18 to 65" = c(18,64), "65 and Over" = c(65, Inf))) |>
addSex(name = "stratified") |>
stratifyCohorts(strata = list("sex", "age_group"), name = "stratified")
cohortCount(cdm$stratified)
#> # A tibble: 10 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
#> 1 1 4718 2264
#> 2 2 4647 2215
#> 3 3 435 435
#> 4 4 395 395
#> 5 5 5857 2331
#> 6 6 716 397
#> 7 7 2792 1751
#> 8 8 830 830
#> 9 9 0 0
#> 10 10 0 0
settings(cdm$stratified)
#> # A tibble: 10 × 10
#> cohort_definition_id cohort_name target_cohort_id target_cohort_name
#> <int> <chr> <int> <chr>
#> 1 1 acetaminophen_female 1 acetaminophen
#> 2 2 acetaminophen_male 1 acetaminophen
#> 3 3 diclofenac_female 2 diclofenac
#> 4 4 diclofenac_male 2 diclofenac
#> 5 5 acetaminophen_18_to… 1 acetaminophen
#> 6 6 acetaminophen_65_an… 1 acetaminophen
#> 7 7 acetaminophen_child 1 acetaminophen
#> 8 8 diclofenac_18_to_65 2 diclofenac
#> 9 9 diclofenac_65_and_o… 2 diclofenac
#> 10 10 diclofenac_child 2 diclofenac
#> # ℹ 6 more variables: cdm_version <chr>, vocabulary_version <chr>,
#> # target_cohort_table_name <chr>, strata_columns <chr>, sex <chr>,
#> # age_group <chr>
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.