Check for inconsistency between AE outcome (AEOUT) and death date (AEDTHDTC)

This check looks for AEs with Death date(AEDTHDTC) but outcome (AEOUT) is not FATAL and conversely AEs with no death date (AEDTHDTC) but outcome (AEOUT) is fatal

check_ae_aeout(AE, preproc = identity, ...)

Arguments

AE

Adverse Events SDTM dataset with variables USUBJID, AEDTHDTC, AEOUT

preproc

An optional company specific preprocessing script

...

Other arguments passed to methods

Value

boolean value if check failed or passed with 'msg' attribute if the test failed

Author

Shumei Chi

Examples

AE <- data.frame(
    USUBJID = 1:7,
    AEDTHDTC = c(NA, "NA", "2015-03-12", "2017-01-22", "1999-11-07","",NA),
    AEOUT = c("", "", "","FATAL","RECOVERED/RESOLVED","FATAL","FATAL"),
    AESPID = "FORMNAME-R:13/L:13XXXX",
    stringsAsFactors = FALSE
)

check_ae_aeout(AE)
#> [1] FALSE
#> attr(,"msg")
#> [1] "AEs with inconsistent AEDTHDTC and AEOUT found."
#> attr(,"data")
#>   USUBJID   AEDTHDTC              AEOUT
#> 1       3 2015-03-12                   
#> 2       5 1999-11-07 RECOVERED/RESOLVED
#> 3       6                         FATAL
#> 4       7       <NA>              FATAL
check_ae_aeout(AE,preproc=roche_derive_rave_row)
#> [1] FALSE
#> attr(,"msg")
#> [1] "AEs with inconsistent AEDTHDTC and AEOUT found."
#> attr(,"data")
#>   USUBJID   AEDTHDTC              AEOUT          RAVE
#> 1       3 2015-03-12                    FORMNAME-R:13
#> 2       5 1999-11-07 RECOVERED/RESOLVED FORMNAME-R:13
#> 3       6                         FATAL FORMNAME-R:13
#> 4       7       <NA>              FATAL FORMNAME-R:13

AE$AEDTHDTC <- NULL
check_ae_aeout(AE)
#> [1] FALSE
#> attr(,"msg")
#> [1] "AE is missing the variable: AEDTHDTC"

AE$AEOUT <- NULL
check_ae_aeout(AE)
#> [1] FALSE
#> attr(,"msg")
#> [1] "AE is missing the variables: AEDTHDTC, AEOUT"