Manipulate codelists

## Introduction: Manipulate codelists This vignette introduces a set of functions designed to manipulate and explore codelists within an OMOP CDM. Specifically, we will learn how to:

First of all, we will load the required packages and connect to a mock database.

library(DBI)
library(duckdb)
library(dplyr)
library(CDMConnector)
library(CodelistGenerator)

# Download mock database
requireEunomia(datasetName = "synpuf-1k", cdmVersion = "5.3")

# Connect to the database and create the cdm object
con <- dbConnect(duckdb(), eunomiaDir("synpuf-1k", "5.3"))
cdm <- cdmFromCon(con = con, 
cdmName = "Eunomia Synpuf",
cdmSchema   = "main",
writeSchema = "main", 
achillesSchema = "main")

We will start by generating a codelist for acetaminophen using getDrugIngredientCodes()

acetaminophen <- getDrugIngredientCodes(cdm,
                                        name = "acetaminophen",
                                        nameStyle = "{concept_name}",
                                        type = "codelist")

Subsetting a Codelist

Subsetting a codelist will allow us to reduce a codelist to only those concepts that meet certain conditions.

Subset by Domain

We will now subset to those concepts that have domain = "Drug". Remember that, to see the domains available in your codelist, you can use associatedDomains().

acetaminophen_drug <- subsetOnDomain(acetaminophen, 
                                     cdm, 
                                     domain = "Drug")

acetaminophen_drug

We can use the negate argument to exclude concepts with a certain domain:

acetaminophen_no_drug <- subsetOnDomain(acetaminophen, 
                                        cdm, 
                                        domain = "Drug", 
                                        negate = TRUE)

acetaminophen_no_drug

Subset on vocabulary

We will now subset the codelist to only include concepts from RxNorm vocabulary. You can also use associatedVocabularies() to explore the vocabularies available in your codelist.

acetaminophen_rxnorm <- subsetOnVocabulary(acetaminophen_drug, 
                                           cdm, 
                                           c("RxNorm"))
acetaminophen_rxnorm

Subset on Dose Unit

We will now filter to only include concepts with specified dose units. Remember that you can use associatedDoseUnits() to explore the dose units available in your codelist.

acetaminophen_mg_unit <- subsetOnDoseUnit(acetaminophen_rxnorm, 
                                          cdm, 
                                          c("milligram", "unit"))
acetaminophen_mg_unit

As before, we can use argument negate = TRUE to exclude instead.

Subset on ingredient range

We can now subset on those drugs with 3 to 30 ingredients:

acetaminophen_ingredient <- subsetOnIngredientRange(acetaminophen_drug, 
                                                cdm,
                                                ingredientRange = c(3, 30))

acetaminophen_ingredient

Notice that negate = TRUE would keep all those concepts with less than 3 ingredients or more than 30 (without including those with 3 or 30 ingredients).

Subset on route category

We will now subset to those concepts that do not have an “unclassified_route” or “transmucosal_rectal”. See associatedRouteCategories() to explore route categories available in your codelist.

acetaminophen_route <- subsetOnRouteCategory(acetaminophen_mg_unit, 
                                             cdm, 
                                             c("transmucosal_rectal","unclassified_route"), 
                                             negate = TRUE)
acetaminophen_route

Subset on dose forms

We will now subset to those concepts with specific dose forms. See associatedDseForms() to explore dose forms available in your codelist.

# First, check which dose forms are available in our codelist
acetaminophen_drug |> 
  associatedDoseForms(cdm)
acetaminophen_oral <- subsetOnDoseForm(acetaminophen_drug, 
                                            cdm, 
                                            c("Oral Solution","Oral Capsule"))
acetaminophen_oral

Stratify codelist

Instead of filtering, stratification allows us to split a codelist into subgroups based on defined vocabulary properties.

Stratify by Dose Unit

acetaminophen_doses <- stratifyByDoseUnit(acetaminophen, cdm, keepOriginal = TRUE)

acetaminophen_doses

Stratify by Route Category

acetaminophen_routes <- stratifyByRouteCategory(acetaminophen, cdm)

acetaminophen_routes

Stratify by Dose Form

acetaminophen_dose_forms <- stratifyByDoseForm(acetaminophen, cdm)

acetaminophen_dose_forms

Add or remove concepts from a codelist

We can also add specific concepts to our codelist. For example, we will add the ingredient “acetaminophen” to all our codelists:

acetaminophen_routes1 <- addConcepts(acetaminophen_routes, 
                                     cdm,
                                     concepts = c(1125315L))
acetaminophen_routes1

Or we can add acetaminophen + descendants, and only to some of the codelists

x <- getDescendants(cdm = cdm, conceptId = c(1125315L))
acetaminophen_routes2 <- addConcepts(acetaminophen_routes, 
                                     cdm,
                                     concepts = x$concept_id, 
                                     codelistName = "acetaminophen_unclassified_route_category")
acetaminophen_routes2

And similarly, we can exclude specific concepts and their descendants from our codelist:

acetaminophen_routes3 <- excludeConcepts(acetaminophen_routes, 
                                         cdm,
                                         concepts = x$concept_id, 
                                         codelistName = "acetaminophen_inhalable")
acetaminophen_routes3

Notice that in this case, the codelist “acetaminophen_inhalable” is removed as there are no elements left after the exclusion of the code 35873016 and its descendants.

Codelist construction

Notice that all the functions introduced previously are “pipeble”, allowing for a tidy and clear codelist construction:

acetaminophen <- getDrugIngredientCodes(cdm,
                                        name = "acetaminophen",
                                        nameStyle = "{concept_name}",
                                        type = "codelist")

new_codelist <- acetaminophen |>
  addConcepts(cdm, 
              concepts = c(1L, 2L, 3L)) |>
  subsetOnDomain(cdm,
                 domain = "Drug") |>
  stratifyByDoseUnit(cdm = cdm) |>
  excludeConcepts(cdm,
                  concepts = c(1127898)) 

new_codelist

Compare codelists

Now we will compare two codelists to identify overlapping and unique codes.

acetaminophen <- getDrugIngredientCodes(cdm, 
                                        name = "acetaminophen", 
                                        nameStyle = "{concept_name}",
                                        type = "codelist_with_details")
hydrocodone <- getDrugIngredientCodes(cdm, 
                                      name = "hydrocodone", 
                                      doseUnit = "milligram", 
                                      nameStyle = "{concept_name}",
                                      type = "codelist_with_details")

Compare the two sets:

comparison <- compareCodelists(acetaminophen,
                               hydrocodone)

comparison |> glimpse()

comparison |> filter(codelist == "Both")