In this vignette we will explore the functionality and arguments of
summariseTemporalSymmetry() function. This function uses
cdm$intersect introduced in the previous vignette
Step 1. Generate a sequence cohort to produce
aggregated statistics containing the frequency for different time gaps
between the initiation of the marker and the initiation of the index
(marker_date \(-\)
index_date). The work of this function is best illustrated
via an example.
Recall that in the previous vignette, we’ve used
cdm$aspirin and cdm$acetaminophen to generate
cdm$intersect like so:
summariseTemporalSymmetry(cohort = cdm$intersect) %>%
dplyr::glimpse()
#> Rows: 558
#> Columns: 13
#> $ result_id <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ cdm_name <chr> "Synthea synthetic health database", "Synthea synthet…
#> $ group_name <chr> "index_name &&& marker_name", "index_name &&& marker_…
#> $ group_level <chr> "aspirin &&& acetaminophen", "aspirin &&& acetaminoph…
#> $ strata_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ strata_level <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ variable_name <chr> "temporal_symmetry", "temporal_symmetry", "temporal_s…
#> $ variable_level <chr> "-29", "40", "10", "20", "69", "-35", "89", "36", "10…
#> $ estimate_name <chr> "count", "count", "count", "count", "count", "count",…
#> $ estimate_type <chr> "integer", "integer", "integer", "integer", "integer"…
#> $ estimate_value <chr> "6", "7", "6", "10", "5", "5", "5", "5", NA, "9", "9"…
#> $ additional_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ additional_level <chr> "overall", "overall", "overall", "overall", "overall"…The default unit of the difference of two initiations is measured in months. In this example, the first row is showing there are \(6\) cases of index happening after marker with the gap being \(29\) months whereas the second row is showing there are \(7\) cases of index happening before marker with the gap being \(40\) months.
cohort_definition_idThis parameter is used to subset the cohort table inputted to the
summariseTemporalSymmetry(). Imagine the user only wants to
include cohort_definition_id \(=
1\) from cdm$intersect in the
summariseTemporalSymmetry(), then one could do the
following:
summariseTemporalSymmetry(cohort = cdm$intersect,
cohortId = 1) %>%
dplyr::glimpse()
#> Rows: 558
#> Columns: 13
#> $ result_id <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ cdm_name <chr> "Synthea synthetic health database", "Synthea synthet…
#> $ group_name <chr> "index_name &&& marker_name", "index_name &&& marker_…
#> $ group_level <chr> "aspirin &&& acetaminophen", "aspirin &&& acetaminoph…
#> $ strata_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ strata_level <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ variable_name <chr> "temporal_symmetry", "temporal_symmetry", "temporal_s…
#> $ variable_level <chr> "26", "277", "261", "375", "162", "178", "268", "17",…
#> $ estimate_name <chr> "count", "count", "count", "count", "count", "count",…
#> $ estimate_type <chr> "integer", "integer", "integer", "integer", "integer"…
#> $ estimate_value <chr> "9", NA, NA, NA, NA, NA, NA, "17", "5", "13", NA, "6"…
#> $ additional_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ additional_level <chr> "overall", "overall", "overall", "overall", "overall"…Of course and once again this does nothing because every entry in
cdm$intersect has cohort_definition_id \(= 1\).
timescaleRecall the default for the timescale is month, one could
also change this to either day or year.
summariseTemporalSymmetry(cohort = cdm$intersect,
timescale = "day") %>%
dplyr::glimpse()
#> Rows: 1,350
#> Columns: 13
#> $ result_id <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ cdm_name <chr> "Synthea synthetic health database", "Synthea synthet…
#> $ group_name <chr> "index_name &&& marker_name", "index_name &&& marker_…
#> $ group_level <chr> "aspirin &&& acetaminophen", "aspirin &&& acetaminoph…
#> $ strata_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ strata_level <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ variable_name <chr> "temporal_symmetry", "temporal_symmetry", "temporal_s…
#> $ variable_level <chr> "1641", "792", "7951", "-1157", "-3808", "9991", "138…
#> $ estimate_name <chr> "count", "count", "count", "count", "count", "count",…
#> $ estimate_type <chr> "integer", "integer", "integer", "integer", "integer"…
#> $ estimate_value <chr> NA, NA, NA, NA, NA, NA, NA, NA, "8", NA, NA, NA, NA, …
#> $ additional_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ additional_level <chr> "overall", "overall", "overall", "overall", "overall"…summariseTemporalSymmetry(cohort = cdm$intersect,
timescale = "year") %>%
dplyr::glimpse()
#> Rows: 94
#> Columns: 13
#> $ result_id <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ cdm_name <chr> "Synthea synthetic health database", "Synthea synthet…
#> $ group_name <chr> "index_name &&& marker_name", "index_name &&& marker_…
#> $ group_level <chr> "aspirin &&& acetaminophen", "aspirin &&& acetaminoph…
#> $ strata_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ strata_level <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ variable_name <chr> "temporal_symmetry", "temporal_symmetry", "temporal_s…
#> $ variable_level <chr> "4", "-11", "31", "37", "-15", "-21", "34", "48", "39…
#> $ estimate_name <chr> "count", "count", "count", "count", "count", "count",…
#> $ estimate_type <chr> "integer", "integer", "integer", "integer", "integer"…
#> $ estimate_value <chr> "71", "18", "5", "5", "8", "7", "5", NA, NA, NA, "39"…
#> $ additional_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ additional_level <chr> "overall", "overall", "overall", "overall", "overall"…minCellCountBy default, the minimum number of events to reported is 5, below which results will be obscured. If 0, all results will be reported and the user could do this via:
summariseTemporalSymmetry(cohort = cdm$intersect,
minCellCount = 0) %>%
dplyr::glimpse()
#> Rows: 558
#> Columns: 13
#> $ result_id <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ cdm_name <chr> "Synthea synthetic health database", "Synthea synthet…
#> $ group_name <chr> "index_name &&& marker_name", "index_name &&& marker_…
#> $ group_level <chr> "aspirin &&& acetaminophen", "aspirin &&& acetaminoph…
#> $ strata_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ strata_level <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ variable_name <chr> "temporal_symmetry", "temporal_symmetry", "temporal_s…
#> $ variable_level <chr> "26", "277", "261", "375", "162", "178", "268", "17",…
#> $ estimate_name <chr> "count", "count", "count", "count", "count", "count",…
#> $ estimate_type <chr> "integer", "integer", "integer", "integer", "integer"…
#> $ estimate_value <chr> "9", "2", "1", "1", "2", "3", "3", "17", "5", "13", "…
#> $ additional_name <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ additional_level <chr> "overall", "overall", "overall", "overall", "overall"…