test_that("conceptIdColumn", { skip_on_cran() expect_no_error( standardConceptIdColumn("condition_occurrence") ) expect_identical( standardConceptIdColumn("condition_occurrence"), "condition_concept_id" ) expect_identical( standardConceptIdColumn("drug_exposure"), "drug_concept_id" ) expect_identical( standardConceptIdColumn("cohort_k"), "cohort_definition_id" ) expect_no_error( sourceConceptIdColumn("condition_occurrence") ) expect_identical( sourceConceptIdColumn("condition_occurrence"), "condition_source_concept_id" ) expect_identical( sourceConceptIdColumn("drug_exposure"), "drug_source_concept_id" ) expect_true( is.na(sourceConceptIdColumn("cohort_k")) ) }) test_that("working examples", { skip_on_cran() # functionality cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2), cohort_start_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )), cohort_end_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )) ) cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2, 2, 1), cohort_start_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )), cohort_end_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )) ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 2 ) result <- cdm$cohort1 %>% .addIntersect(tableName = "cohort2", value = "date", nameStyle = "xx") expect_true(length(attributes(cdm$cohort1)) == length(attributes(result))) for (i in names(attributes(cdm$cohort1))) { if (i != "names" && i != "tbl_name") { x <- attr(cdm$cohort1, i) y <- attr(result, i) if (i == "class") { x <- x[x != "GeneratedCohortSet"] y <- y[y != "GeneratedCohortSet"] } expect_true(identical(x, y)) } } result <- result %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(colnames(result)[1] == "cohort_definition_id") expect_true(colnames(result)[2] == "subject_id") expect_true(colnames(result)[3] == "cohort_start_date") expect_true(colnames(result)[4] == "cohort_end_date") expect_true(all(result %>% dplyr::pull("xx") == as.Date(c("2020-01-15", "2020-01-15", "2020-01-25", "2020-01-24", "2020-03-15")))) result1 <- cdm$cohort1 %>% .addIntersect(tableName = "cohort2", value = "count") %>% .addIntersect(tableName = "cohort2", value = "days") %>% .addIntersect(tableName = "cohort2", value = "flag") %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(result1$count_all_0_to_inf == c(4, 4, 3, 3, 1))) expect_true(all(result1$days_all_0_to_inf == c(14, 0, 5, 23, 43))) expect_true(all(result1$flag_all_0_to_inf == c(1, 1, 1, 1, 1))) result2 <- cdm$cohort1 %>% .addIntersect(tableName = "cohort2", value = "count", order = "last") %>% .addIntersect(tableName = "cohort2", value = "flag", order = "last") %>% .addIntersect(tableName = "cohort2", value = "date", order = "last") %>% .addIntersect(tableName = "cohort2", value = "days", order = "last") %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) result6 <- cdm$cohort1 %>% .addIntersect(tableName = "cohort2", value = c("date", "count", "days", "flag"), order = "last") %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) for (col in colnames(result2)) { expect_true(all(result2[[col]][!is.na(result2[[col]])] == result6[[col]][!is.na(result6[[col]])])) } expect_true(all(result2$date_all_0_to_inf == as.Date(c( "2020-02-16", "2020-02-16", "2020-02-16", "2020-03-15", "2020-03-15" )))) expect_true(all(result2$days_all_0_to_inf == c(46, 32, 27, 74, 43))) expect_true(all(result2$count_all_0_to_inf == c(4, 4, 3, 3, 1))) expect_true(all(result2$flag_all_0_to_inf == c(1, 1, 1, 1, 1))) result3 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", window = list(c(-Inf, 0)), value = "date" ) %>% .addIntersect( tableName = "cohort2", window = list(c(-Inf, 0)), value = "days" ) %>% .addIntersect( tableName = "cohort2", window = list(c(-Inf, 0)), value = "count" ) %>% .addIntersect( tableName = "cohort2", window = list(c(-Inf, 0)), value = "flag" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(result3$date_all_minf_to_0 %in% as.Date( c(NA, "2020-01-15", "2020-01-15", NA, "2020-01-24") ))) expect_true(all(result3$days_all_minf_to_0 %in% c(NA, 0, -5, NA, -8))) expect_true(all(result3$count_all_minf_to_0 == c(0, 1, 1, 0, 2))) expect_true(all(result3$flag_all_minf_to_0 == c(0, 1, 1, 0, 1))) result4 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", window = list(c(-30, 30)), value = "date" ) %>% .addIntersect( tableName = "cohort2", window = list(c(-30, 30)), value = "days" ) %>% .addIntersect( tableName = "cohort2", window = list(c(-30, 30)), value = "count" ) %>% .addIntersect( tableName = "cohort2", window = list(c(-30, 30)), value = "flag" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(result4$date_all_m30_to_30 == as.Date(c( "2020-01-15", "2020-01-15", "2020-01-15", "2020-01-24", "2020-01-24" )))) expect_true(all(result4$days_all_m30_to_30 == c(14, 0, -5, 23, -8))) expect_true(all(result4$count_all_m30_to_30 == c(3, 3, 4, 2, 2))) expect_true(all(result4$flag_all_m30_to_30 == c(1, 1, 1, 1, 1))) result5 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", window = list(c(-30, 30)), value = "date", order = "last" ) %>% .addIntersect( tableName = "cohort2", window = list(c(-30, 30)), value = "days", order = "last" ) %>% .addIntersect( tableName = "cohort2", window = list(c(-30, 30)), value = "count", order = "last" ) %>% .addIntersect( tableName = "cohort2", window = list(c(-30, 30)), value = "flag", order = "last" ) %>% dplyr::arrange(subject_id, cohort_start_date) %>% dplyr::collect() expect_true(all(result5$count_all_m30_to_30 == c(3, 3, 4, 2, 2))) expect_true(all(result5$flag_all_m30_to_30 == c(1, 1, 1, 1, 1))) expect_true(all(result5$days_all_m30_to_30 == c(25, 11, 27, 28, -3))) expect_true(all(result5$date_all_m30_to_30 == as.Date(c( "2020-01-26", "2020-01-26", "2020-02-16", "2020-01-29", "2020-01-29" )))) mockDisconnect(cdm = cdm) }) test_that("working examples with cohort_end_date", { skip_on_cran() # functionality cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2), cohort_start_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )), cohort_end_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )) ) cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2, 2, 1), cohort_start_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )), cohort_end_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )) ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 2 ) result <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", value = "date", indexDate = "cohort_end_date" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all( result$date_all_0_to_inf == as.Date(c( "2020-01-15", "2020-01-15", "2020-01-25", "2020-01-24", "2020-03-15" )) )) mockDisconnect(cdm = cdm) }) test_that("working examples with extra column", { skip_on_cran() # functionality cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2), cohort_start_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )), cohort_end_date = as.Date(c( "2020-01-14", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )) ) cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2, 2, 1), cohort_start_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )), cohort_end_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )) ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 2 ) cdm$cohort2 <- cdm$cohort2 %>% dbplyr::window_order( .data$cohort_definition_id, .data$subject_id, .data$cohort_start_date ) %>% dplyr::mutate(measurment_result = dplyr::row_number()) %>% dbplyr::window_order() %>% dplyr::compute() result <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", value = c("flag", "measurment_result"), filterVariable = "cohort_definition_id", filterId = 1, idName = "covid", window = list(c(0, Inf)) ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) result1 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", value = "measurment_result", filterVariable = "cohort_definition_id", filterId = 2, idName = "covid", window = list(c(0, Inf)) ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2, 2, 1), cohort_start_date = as.Date(c( "2020-01-15", "2020-01-16", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )), cohort_end_date = as.Date(c( "2020-01-15", "2020-01-16", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )) ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 2 ) cdm$cohort2 <- cdm$cohort2 %>% dbplyr::window_order( .data$cohort_definition_id, .data$subject_id, .data$cohort_start_date ) %>% dplyr::mutate(measurment_result = dplyr::row_number()) %>% dbplyr::window_order() %>% dplyr::compute() result2 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", value = "measurment_result", nameStyle = "{value}_{window_name}" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) result3 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", value = c("flag", "measurment_result"), nameStyle = "{value}_{window_name}", window = list(c(-400, -200)) ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(result$measurment_result_covid_0_to_inf == c(1, 1, 2, 5, 7))) expect_true(all(is.na(result1$measurment_result_covid_0_to_inf))) expect_true(all(result2$measurment_result_0_to_inf == c("1", "1", 3, 5, 7))) expect_true(all(is.na(result3$measurment_result_m400_to_m200))) mockDisconnect(cdm = cdm) }) test_that("working examples with multiple cohort Ids", { skip_on_cran() # functionality cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2), cohort_start_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )), cohort_end_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )) ) cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 2, 2, 3, 3, 3), subject_id = c(1, 1, 1, 2, 2, 2, 1), cohort_start_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )), cohort_end_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )) ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 2 ) compareNA <- function(v1, v2) { same <- (v1 == v2) | (is.na(v1) & is.na(v2)) same[is.na(same)] <- FALSE return(same) } result <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", filterVariable = "cohort_definition_id", filterId = 1, value = "date" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(compareNA(result$date_id1_0_to_inf, as.Date(c( "2020-01-15", "2020-01-15", "2020-01-25", NA, NA ))))) result1 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", filterVariable = "cohort_definition_id", filterId = 2, value = "count" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(result1$count_id2_0_to_inf == c(1, 1, 1, 1, 0))) result2 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", filterVariable = "cohort_definition_id", filterId = c(1, 3), value = "flag" ) %>% .addIntersect( tableName = "cohort2", filterVariable = "cohort_definition_id", filterId = c(1, 3), value = "count" ) %>% .addIntersect( tableName = "cohort2", filterVariable = "cohort_definition_id", filterId = c(1, 3), value = "days" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) result3 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", filterVariable = "cohort_definition_id", filterId = c(1, 3), value = c("count", "days", "flag") ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) for (col in colnames(result2)) { expect_true(all( result2[[col]][!is.na(result2[[col]])] == result3[[col]][!is.na(result3[[col]])] )) } expect_true(all(result2$count_id1_0_to_inf == c(2, 2, 1, 0, 0))) expect_true(all(compareNA(result2$days_id1_0_to_inf, c(14, 0, 5, NA, NA)))) expect_true(all(result2$flag_id1_0_to_inf == c(1, 1, 1, 0, 0))) expect_true(all(result2$count_id3_0_to_inf == c(1, 1, 1, 2, 1))) expect_true(all(result2$days_id3_0_to_inf == c(46, 32, 27, 23, 43))) expect_true(all(result2$flag_id3_0_to_inf == c(1, 1, 1, 1, 1))) mockDisconnect(cdm = cdm) }) test_that("working examples calculating as incidence target cohort", { skip_on_cran() # functionality cohort1 <- dplyr::tibble( cohort_definition_id = c(1), subject_id = c(1), cohort_start_date = as.Date("2020-01-15"), cohort_end_date = as.Date("2021-01-01") ) cohort2 <- dplyr::tibble( cohort_definition_id = c(1), subject_id = c(1), cohort_start_date = as.Date("2020-01-01"), cohort_end_date = as.Date("2020-02-15") ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2 ) compareNA <- function(v1, v2) { same <- (v1 == v2) | (is.na(v1) & is.na(v2)) same[is.na(same)] <- FALSE return(same) } result <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", window = c(-Inf, Inf), value = "date", nameStyle = "test_{id_name}_{window_name}" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) result1 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", window = c(-Inf, Inf), value = "date", targetEndDate = NULL ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(result$test_all_minf_to_inf == as.Date("2020-01-01"))) expect_true(("date_all_minf_to_inf" %in% colnames(result1))) mockDisconnect(cdm = cdm) }) test_that("working examples with more than one window", { skip_on_cran() # functionality cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2), cohort_start_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )), cohort_end_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )) ) cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 2, 2, 3, 3, 3), subject_id = c(1, 1, 1, 2, 2, 2, 1), cohort_start_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )), cohort_end_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )) ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 2 ) compareNA <- function(v1, v2) { same <- (v1 == v2) | (is.na(v1) & is.na(v2)) same[is.na(same)] <- FALSE return(same) } result <- cdm$cohort1 %>% .addIntersect(tableName = "cohort2", value = "date") %>% .addIntersect( tableName = "cohort2", value = "date", window = list(c(-Inf, 0)) ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) result1 <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", value = "date", window = list(c(0, Inf), c(-Inf, 0)) ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all( result$date_all_0_to_inf == result1$date_all_0_to_inf )) expect_true(all(compareNA( result$date_all_minf_to_0, result1$date_all_minf_to_0 ))) mockDisconnect(cdm = cdm) }) test_that("working examples with tables, not cohorts", { skip_on_cran() # functionality cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2), cohort_start_date = as.Date( c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" ) ), cohort_end_date = as.Date( c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" ) ) ) drugExposure <- dplyr::tibble( drug_exposure_id = 0, drug_type_concept_id = 0, person_id = c(1, 1), drug_concept_id = c(1, 2), drug_exposure_start_date = as.Date(c("2020-02-10", "2019-09-01")), drug_exposure_end_date = as.Date(NA) ) conditionOccurrence <- dplyr::tibble( condition_concept_id = c(1, 1, 2, 2, 3, 3, 3), condition_occurrence_id = 0, condition_type_concept_id = 0, person_id = c(1, 1, 1, 2, 2, 2, 1), condition_start_date = as.Date( c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" ) ), condition_end_date = as.Date( c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" ) ), ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, condition_occurrence = conditionOccurrence, drug_exposure = drugExposure, numberIndividuals = 2 ) compareNA <- function(v1, v2) { same <- (v1 == v2) | (is.na(v1) & is.na(v2)) same[is.na(same)] <- FALSE return(same) } result <- cdm$cohort1 %>% .addIntersect( tableName = "condition_occurrence", value = "date", targetStartDate = "condition_start_date", targetEndDate = "condition_end_date", window = list(c(0, Inf), c(-Inf, 0)) ) %>% dplyr::collect() expect_true(all(result$date_all_0_to_inf %in% as.Date(c("2020-01-15", "2020-01-15", "2020-01-25", "2020-01-24", "2020-03-15")))) result1 <- cdm$condition_occurrence %>% .addIntersect( tableName = "drug_exposure", value = "count", indexDate = "condition_start_date", targetStartDate = "drug_exposure_start_date", targetEndDate = NULL, window = list(c(0, Inf), c(-Inf, 0)), filterVariable = "drug_concept_id", filterId = c(1, 2) ) %>% dplyr::collect() |> dplyr::arrange(person_id, condition_start_date) expect_true(all(result1$count_id1_0_to_inf == c(1, 1, 1, 0, 0, 0, 0))) # test output all zero column when no result found expect_true(all(result1$count_id2_0_to_inf == c(0, 0, 0, 0, 0, 0, 0))) expect_true(all(result1$count_id1_minf_to_0 == c(0, 0, 0, 1, 0, 0, 0))) expect_true(all(result1$count_id2_minf_to_0 == c(1, 1, 1, 1, 0, 0, 0))) result2 <- cdm$condition_occurrence %>% .addIntersect( tableName = "drug_exposure", value = "count", indexDate = "condition_start_date", targetStartDate = "drug_exposure_start_date", targetEndDate = NULL, window = list(c(0, Inf), c(-Inf, 0)) ) %>% dplyr::collect() |> dplyr::arrange(person_id, condition_start_date) expect_true(all(result1$count_id1_0_to_inf + result1$count_id2_0_to_inf == result2$count_all_0_to_inf)) expect_true(all(result1$count_id1_minf_to_0 + result1$count_id2_minf_to_0 == result2$count_all_minf_to_0)) result3 <- cdm$condition_occurrence %>% .addIntersect( tableName = "drug_exposure", value = "date", indexDate = "condition_start_date", targetStartDate = "drug_exposure_start_date", targetEndDate = NULL, window = list(c(0, Inf)), filterVariable = "drug_concept_id", filterId = c(1, 2) ) %>% dplyr::collect() |> dplyr::arrange(person_id, condition_start_date) # test output all zero column when no result found expect_true(all(is.na(result3$date_id2_0_to_inf))) result4 <- cdm$condition_occurrence %>% .addIntersect( tableName = "drug_exposure", value = "days", indexDate = "condition_start_date", targetStartDate = "drug_exposure_start_date", targetEndDate = NULL, window = list(c(0, Inf)), filterVariable = "drug_concept_id", filterId = c(1, 2) ) %>% dplyr::collect() |> dplyr::arrange(person_id, condition_start_date) # test output all zero column when no result found expect_true(all(is.na(result4$days_id2_0_to_inf))) mockDisconnect(cdm = cdm) }) test_that("check input length and type for each of the arguments", { skip_on_cran() cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2), cohort_start_date = as.Date( c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" ) ), cohort_end_date = as.Date( c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" ) ) ) cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2, 2, 1), cohort_start_date = as.Date( c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" ) ), cohort_end_date = as.Date( c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" ) ), ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 2 ) expect_error(.addIntersect("cdm$cohort1")) expect_error(.addIntersect(cdm$cohort1)) expect_error(.addIntersect(cdm$cohort1, tableName = "drug")) expect_error(.addIntersect(cdm$cohort1, tableName = "cohort2", value = "end_date")) expect_error(.addIntersect(cdm$cohort1, tableName = "cohort2", value = "flag", cohortId = "3")) expect_error(.addIntersect(cdm$cohort1, tableName = "cohort2", value = "flag", indexDate = 3)) expect_error(.addIntersect(cdm$cohort1, tableName = "cohort2", value = "flag", targetStartDate = "no")) expect_error(.addIntersect(cdm$cohort1, tableName = "cohort2", value = "flag", targetEndDate = NA)) expect_error(.addIntersect(cdm$cohort1, tableName = "cohort2", value = "flag", nameStyle = "test_{nowindow}_{cohortName}")) mockDisconnect(cdm = cdm) }) test_that("test checkWindow function", { skip_on_cran() cdm <- mockPatientProfiles(con = connection(), writeSchema = writeSchema()) expect_error(cdm$cohort1 %>% .addIntersect( value = "days", filterId = 1, filterVariable = "cohort_definition_id", tableName = "cohort2", window = c(150, -90) )) }) test_that("test if column exist, overwrite", { skip_on_cran() cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2), cohort_start_date = as.Date(c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" )), cohort_end_date = cohort_start_date, flag_all_0_to_30 = c(2, 2, 2, 2, 2), count_all_0_to_30 = c(1, 1, 1, 1, 1), days_all_0_to_30 = c(1, 1, 1, 1, 1), date_all_0_to_30 = c(1, 1, 1, 1, 1) ) cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2, 2, 1), cohort_start_date = as.Date(c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" )), cohort_end_date = cohort_start_date, ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 2 ) expect_message( result <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", value = c("flag", "date", "days", "count"), window = list(c(0, 30)) ) %>% dplyr::collect() ) expect_true(sum(colnames(result) == "flag_all_0_to_30") == 1) expect_true(all(result %>% dplyr::arrange(cohort_start_date, subject_id) %>% dplyr::select(flag_all_0_to_30) != cohort1 %>% dplyr::arrange(cohort_start_date, subject_id) %>% dplyr::select(flag_all_0_to_30), na.rm = TRUE)) expect_true(all(result %>% dplyr::arrange(cohort_start_date, subject_id) %>% dplyr::select(count_all_0_to_30) != cohort1 %>% dplyr::arrange(cohort_start_date, subject_id) %>% dplyr::select(count_all_0_to_30), na.rm = TRUE)) expect_true(all(result %>% dplyr::arrange(cohort_start_date, subject_id) %>% dplyr::select(days_all_0_to_30) != cohort1 %>% dplyr::arrange(cohort_start_date, subject_id) %>% dplyr::select(days_all_0_to_30), na.rm = TRUE)) expect_true(all(result %>% dplyr::arrange(cohort_start_date, subject_id) %>% dplyr::select(date_all_0_to_30) != cohort1 %>% dplyr::arrange(cohort_start_date, subject_id) %>% dplyr::select(date_all_0_to_30), na.rm = TRUE)) mockDisconnect(cdm = cdm) }) test_that("overlapTable is empty, check return columns", { skip_on_cran() # functionality cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1), subject_id = c(1, 1, 1, 2, 2), cohort_start_date = as.Date( c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" ) ), cohort_end_date = as.Date( c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01" ) ) ) cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 2, 2, 3, 3, 3), subject_id = c(1, 1, 1, 2, 2, 2, 1), cohort_start_date = as.Date( c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" ) ), cohort_end_date = as.Date( c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" ) ), ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 2 ) result <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", value = c("date", "days", "count", "flag"), filterVariable = "cohort_definition_id", filterId = 2 ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(c( "count_id2_0_to_inf", "flag_id2_0_to_inf", "days_id2_0_to_inf", "date_id2_0_to_inf" ) %in% colnames(result))) expect_true(all(result$count_id2_0_to_inf == 0)) expect_true(all(result$flag_id2_0_to_inf == 0)) expect_true(all(is.na(result$days_id2_0_to_inf))) expect_true(all(is.na(result$date_id2_0_to_inf))) mockDisconnect(cdm = cdm) }) test_that("overlap is empty or not, multiple ids, check return columns", { skip_on_cran() # functionality cohort2 <- dplyr::tibble( cohort_definition_id = c(1, 1, 1, 1, 1, 3), subject_id = c(1, 1, 1, 2, 2, 3), cohort_start_date = as.Date( c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01", "2020-03-03" ) ), cohort_end_date = as.Date( c( "2020-01-01", "2020-01-15", "2020-01-20", "2020-01-01", "2020-02-01", "2020-03-03" ) ) ) cohort1 <- dplyr::tibble( cohort_definition_id = c(1, 1, 2, 2, 3, 3, 3), subject_id = c(3, 3, 3, 3, 3, 3, 3), cohort_start_date = as.Date( c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" ) ), cohort_end_date = as.Date( c( "2020-01-15", "2020-01-25", "2020-01-26", "2020-01-29", "2020-03-15", "2020-01-24", "2020-02-16" ) ), ) cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), cohort1 = cohort1, cohort2 = cohort2, numberIndividuals = 3 ) compareNA <- function(v1, v2) { same <- (v1 == v2) | (is.na(v1) & is.na(v2)) same[is.na(same)] <- FALSE return(same) } result <- cdm$cohort1 %>% addCohortIntersectCount( targetCohortTable = "cohort2" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true("cohort_1_0_to_inf" %in% colnames(result)) expect_true(all(result$cohort_1_0_to_inf == 0)) result <- cdm$cohort1 %>% addCohortIntersectFlag( targetCohortTable = "cohort2" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true("cohort_1_0_to_inf" %in% colnames(result)) expect_true(all(result$cohort_1_0_to_inf == 0)) result <- cdm$cohort1 %>% addCohortIntersectDate( targetCohortTable = "cohort2" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true("cohort_1_0_to_inf" %in% colnames(result)) expect_true(all(is.na(result$cohort_1_0_to_inf))) result <- cdm$cohort1 %>% addCohortIntersectDays( targetCohortTable = "cohort2" ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true("cohort_1_0_to_inf" %in% colnames(result)) expect_true(all(is.na(result$cohort_1_0_to_inf))) result <- cdm$cohort1 %>% .addIntersect( tableName = "cohort2", value = c("flag", "date"), filterVariable = "cohort_definition_id", filterId = c(1, 2, 3), window = list(c(0, Inf), c(-30, -1)), idName = c("num1", "num2", "num3") ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(c( "flag_num1_0_to_inf", "flag_num2_0_to_inf", "flag_num3_0_to_inf", "date_num1_0_to_inf", "date_num2_0_to_inf", "date_num3_0_to_inf", "flag_num1_m30_to_m1", "flag_num2_m30_to_m1", "flag_num3_m30_to_m1", "date_num1_m30_to_m1", "date_num2_m30_to_m1", "date_num3_m30_to_m1" ) %in% colnames(result))) expect_true(all(compareNA(result$date_num3_0_to_inf, c("2020-03-03", "2020-03-03", "2020-03-03", "2020-03-03", "2020-03-03", "2020-03-03", NA)))) expect_true(all(compareNA(result$date_num3_m30_to_m1, c(NA, NA, NA, NA, NA, NA, "2020-03-03")))) expect_true(all(result$flag_num3_0_to_inf == c(1, 1, 1, 1, 1, 1, 0))) expect_true(all(result$flag_num3_m30_to_m1 == c(0, 0, 0, 0, 0, 0, 1))) expect_true(all(result$flag_num2_0_to_inf == c(0, 0, 0, 0, 0, 0, 0))) expect_true(all(result$flag_num1_0_to_inf == c(0, 0, 0, 0, 0, 0, 0))) expect_true(all(result$flag_num2_m30_to_m1 == c(0, 0, 0, 0, 0, 0, 0))) expect_true(all(result$flag_num1_m30_to_m1 == c(0, 0, 0, 0, 0, 0, 0))) expect_true(all(is.na(result$date_num2_0_to_inf))) expect_true(all(is.na(result$date_num1_0_to_inf))) expect_true(all(is.na(result$date_num2_m30_to_m1))) expect_true(all(is.na(result$date_num1_m30_to_m1))) expect_error(cdm$cohort1 %>% addCohortIntersectDate( targetCohortTable = "cohort2", targetCohortId = c(1, 2, 3), window = list(c(0, Inf), c(-30, -1)) ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date)) result <- cdm$cohort1 %>% addCohortIntersectDate( targetCohortTable = "cohort2", targetCohortId = c(1, 3), window = list(c(0, Inf), c(-30, -1)) ) %>% dplyr::collect() |> dplyr::arrange(subject_id, cohort_start_date) expect_true(all(c( "cohort_3_m30_to_m1", "cohort_1_m30_to_m1", "cohort_3_0_to_inf", "cohort_1_0_to_inf" ) %in% colnames(result))) expect_true(all(compareNA(result$cohort_3_0_to_inf, c("2020-03-03", "2020-03-03", "2020-03-03", "2020-03-03", "2020-03-03", "2020-03-03", NA)))) expect_true(all(compareNA(result$cohort_3_m30_to_m1, c(NA, NA, NA, NA, NA, NA, "2020-03-03")))) expect_true(all(is.na(result$cohort_1_m30_to_m1))) expect_true(all(is.na(result$cohort_1_0_to_inf))) mockDisconnect(cdm = cdm) }) test_that("non snake columns not repeated in output", { skip_on_cran() cdm <- mockPatientProfiles(con = connection(), writeSchema = writeSchema()) attr(cdm$cohort1, "cohort_set") <- attr(cdm$cohort1, "cohort_set") %>% dplyr::mutate(cohort_name = toupper(cohort_name)) cdm$cohort2 <- cdm$cohort2 %>% addCohortIntersectFlag(targetCohortTable = "cohort1") expect_true("cohort_1_0_to_inf" %in% colnames(cdm$cohort2)) expect_false("COHORT_1_0_to_inf" %in% colnames(cdm$cohort2)) }) test_that("no NA when overwrite column", { skip_on_cran() cdm <- mockPatientProfiles( con = connection(), writeSchema = writeSchema(), numberIndividuals = 1000 ) # Presence in characteristis 'cohort 1' in 180 days before cohort start cdm$cohort1 <- cdm$cohort1 %>% addCohortIntersectFlag( targetCohortTable = "cohort2", window = list(c(-180, -1)), targetCohortId = 1, nameStyle = "{cohort_name}" ) # Trying to overwrite the previous created variable, for example because the characteristics cohort has changed. expect_message( cdm$cohort1 <- cdm$cohort1 %>% addCohortIntersectFlag( targetCohortTable = "cohort2", window = list(c(-180, -1)), targetCohortId = 1, nameStyle = "{cohort_name}" ) ) expect_true(!any(is.na(cdm$cohort1 %>% dplyr::pull("cohort_1")))) # subject 2, who has no record for cohort_definition_id 1 in the characteristics cohort, now gets a "NA" # Moving the "cohort_definition_id == 1" records from subject 1 to subject 2: cdm$cohort2 <- cdm$cohort2 %>% dplyr::mutate(subject_id = dplyr::if_else(cohort_definition_id == 1 & subject_id == 1, 2, subject_id)) expect_message( cdm$cohort1 <- cdm$cohort1 %>% addCohortIntersectFlag( targetCohortTable = "cohort2", window = list(c(-180, -1)), targetCohortId = 1, nameStyle = "{cohort_name}" ) ) expect_true(!any(is.na(cdm$cohort1 %>% dplyr::pull("cohort_1")))) mockDisconnect(cdm = cdm) })