Calculate details of a study's primary endpoint statistical testing

Trial concept calculated: Calculates several results-related elements of the primary statistical analysis of the primary endpoint. Requires loading results-related information. For CTIS and ISRCTN, such information is not available in structured format. Recommended to be combined with f.controlType, f.sampleSize, f.assignmentType and other ctrdata-trial-concepts for analyses.

Usage

f.primaryEndpointResults(df = NULL)

Arguments

df

data frame such as from dbGetFieldsIntoDf. If NULL, prints fields needed in df for calculating this trial concept, which can be used with dbGetFieldsIntoDf.

Value

data frame with columns _id and new columns: .primaryEndpointFirstPvalue (discarding any inequality indicator, e.g. <=), .primaryEndpointFirstPmethod (normalised string, e.g. chisquared), .primaryEndpointFirstPsize (number included in test, across assignment groups).

Examples

# fields needed
f.primaryEndpointResults()
#> $euctr
#> [1] "endPoints.endPoint.type.value" "endPoints.endPoint"           
#> 
#> $ctgov
#> [1] "clinical_results.outcome_list.outcome.type"
#> [2] "clinical_results.outcome_list.outcome"     
#> 
#> $ctgov2
#> [1] "resultsSection.outcomeMeasuresModule.outcomeMeasures.type"
#> [2] "resultsSection.outcomeMeasuresModule.outcomeMeasures"     
#> 
#> $isrctn
#> NULL
#> 
#> $ctis
#> NULL
#> 

# apply trial concept when creating data frame
dbc <- nodbi::src_sqlite(
  dbname = system.file("extdata", "demo.sqlite", package = "ctrdata"),
  collection = "my_trials", flags = RSQLite::SQLITE_RO)
trialsDf <- dbGetFieldsIntoDf(
  calculate = "f.primaryEndpointResults",
  con = dbc)
#> To review trial concepts details, call 'help("ctrdata-trial-concepts")'
#> Querying database (6 fields)...
#> Typing fields...
#> Calculating f.primaryEndpointResults...                            

trialsDf
#> # A tibble: 11 × 4
#>    `_id`             .primaryEndpointFirstPvalue .primaryEndpointFirstPmethod  
#>    <chr>                                   <dbl> <chr>                         
#>  1 2016-004489-24-DE                      0.001  cochranmantelhaenszel         
#>  2 2019-002663-10-ES                      0.0001 ancova                        
#>  3 2022-000099-20-DE                      0.0001 exactusingbinomialdistribution
#>  4 NCT00567567                            0.0082 logrank                       
#>  5 NCT00716976                           NA      NA                            
#>  6 NCT01305200                           NA      NA                            
#>  7 NCT01987596                           NA      NA                            
#>  8 NCT03275402                           NA      NA                            
#>  9 NCT03325556                            0.0023 regressioncox                 
#> 10 NCT03443973                           NA      NA                            
#> 11 NCT03548584                           NA      NA                            
#> # ℹ 1 more variable: .primaryEndpointFirstPsize <dbl>