Table 1 - does not report correct subject count

[gowthamrao]

FeatureExtraction/R/Table1.R

Line 570 in 8a7cb70

formatCount(attr(covariateData1, "metaData")$populationSize),

To reproduce

• do feature extraction with aggregate = TRUE for more than cohorts
• make sure more than cohort has data in it
• create table 1 for any cohortId other than the first
• the subjectCount of the first cohort is shown in table header

[anthonysena]

Note: I'll create a reprex for this issue so we have details on how to reproduce this bug.

[ginberg]

@anthonysena could you create a reprex for this?

[anthonysena]

Here it is - in this example, I've created aggregated features for the 4 cohorts in Eunomia but the Table1 output appears to include the wrong cohorts.

connectionDetails <- Eunomia::getEunomiaConnectionDetails()
cohortCounts <- Eunomia::createCohorts(
  connectionDetails = connectionDetails
)
#> Connecting using SQLite driver
#> Creating cohort: Celecoxib
#>   |                                                                              |                                                                      |   0%  |                                                                              |======================================================================| 100%
#> Executing SQL took 0.0157 secs
#> Creating cohort: Diclofenac
#>   |                                                                              |                                                                      |   0%  |                                                                              |======================================================================| 100%
#> Executing SQL took 0.0157 secs
#> Creating cohort: GiBleed
#>   |                                                                              |                                                                      |   0%  |                                                                              |======================================================================| 100%
#> Executing SQL took 0.0308 secs
#> Creating cohort: NSAIDs
#>   |                                                                              |                                                                      |   0%  |                                                                              |======================================================================| 100%
#> Executing SQL took 0.0659 secs
#> Cohorts created in table main.cohort
print(cohortCounts)
#>   cohortId       name
#> 1        1  Celecoxib
#> 2        2 Diclofenac
#> 3        3    GiBleed
#> 4        4     NSAIDs
#>                                                                                        description
#> 1    A simplified cohort definition for new users of celecoxib, designed specifically for Eunomia.
#> 2    A simplified cohort definition for new users ofdiclofenac, designed specifically for Eunomia.
#> 3 A simplified cohort definition for gastrointestinal bleeding, designed specifically for Eunomia.
#> 4       A simplified cohort definition for new users of NSAIDs, designed specifically for Eunomia.
#>   count
#> 1  1844
#> 2   850
#> 3   479
#> 4  2694

covariateData <- FeatureExtraction::getDbCovariateData(
  connectionDetails = connectionDetails,
  cdmDatabaseSchema = "main",
  cohortDatabaseSchema = "main",
  covariateSettings = FeatureExtraction::createDefaultCovariateSettings(),
  aggregated = TRUE
)
#> Connecting using SQLite driver
#> Constructing features on server
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#> Executing SQL took 1.58 secs
#> Fetching data from server
#> Fetching data took 0.226 secs

table1 <- FeatureExtraction::createTable1(
  covariateData1 = covariateData,
  covariateData2 = covariateData,
  cohortId1 = 2, #Diclofenac - Cohort Count == 850
  cohortId2 = 4,  #NSAIDs - Cohort Count = 2694
  output = 'one column'
)
print(table1, n = 30)
#> # A tibble: 30 × 4
#>    Characteristic                `% (n = 1,844)` `% (n =   479)` `% (n = 2,694)`
#>    <chr>                         <chr>           <chr>           <chr>          
#>  1 "Age group"                   ""              ""              ""             
#>  2 "   30 -  34"                 " 11.8"         " 11.5"         "-0.01"        
#>  3 "   35 -  39"                 " 49.4"         " 48.4"         "-0.02"        
#>  4 "   40 -  44"                 " 35.8"         " 36.4"         " 0.01"        
#>  5 "   45 -  49"                 "  3.1"         "  3.7"         " 0.04"        
#>  6 "Gender: female"              " 52.1"         " 51.0"         "-0.02"        
#>  7 "Medical history: General"    ""              ""              ""             
#>  8 "  Osteoarthritis"            "100.0"         "100.0"         "  NaN"        
#>  9 "  Rheumatoid arthritis"      " 0"            "  0.0"         " 0.03"        
#> 10 "  Ulcerative colitis"        "  1.1"         "  2.4"         " 0.11"        
#> 11 "Medical history: Cardiovasc… ""              ""              ""             
#> 12 "  Coronary arteriosclerosis" "  0.1"         "  0.1"         " 0.01"        
#> 13 ""                            ""              ""              ""             
#> 14 "Characteristic"              "Value"         "Value"         "Std.Diff"     
#> 15 "Charlson comorbidity index"  ""              ""              ""             
#> 16 "    Mean"                    "0.4"           "0.5"           " 0.40"        
#> 17 "    Std. deviation"          "0.3"           "0.4"           "  "           
#> 18 "    Minimum"                 "0.0"           "0.0"           "  "           
#> 19 "    25th percentile"         "0.0"           "0.0"           "  "           
#> 20 "    Median"                  "0.0"           "0.0"           "  "           
#> 21 "    75th percentile"         "1.0"           "1.0"           "  "           
#> 22 "    Maximum"                 "3.0"           "3.0"           "  "           
#> 23 "CHADS2Vasc"                  ""              ""              ""             
#> 24 "    Mean"                    "0.5"           "0.5"           "-0.02"        
#> 25 "    Std. deviation"          "0.5"           "0.5"           "  "           
#> 26 "    Minimum"                 "0.0"           "0.0"           "  "           
#> 27 "    25th percentile"         "0.0"           "0.0"           "  "           
#> 28 "    Median"                  "0.0"           "1.0"           "  "           
#> 29 "    75th percentile"         "0.0"           "1.0"           "  "           
#> 30 "    Maximum"                 "1.0"           "1.0"           "  "

^{Created on 2024-03-29 with reprex v2.1.0}