Derive on-treatment flag (ONTRTFL
) in an ADaM dataset with a single
assessment date (e.g ADT
) or event start and end dates (e.g.
ASTDT
/AENDT
).
Usage
derive_var_ontrtfl(
dataset,
new_var = ONTRTFL,
start_date,
end_date = NULL,
ref_start_date,
ref_end_date = NULL,
ref_end_window = 0,
ignore_time_for_ref_end_date = TRUE,
filter_pre_timepoint = NULL,
span_period = NULL
)
Arguments
- dataset
Input dataset.
Required columns are
start_date
,end_date
,ref_start_date
andref_end_date
.- new_var
On-treatment flag variable name to be created.
Default is
ONTRTFL
.- start_date
The start date (e.g.
AESDT
) or assessment date (e.g.ADT
) Required; A date or date-time object column is expected.Refer to
derive_vars_dt()
to impute and derive a date from a date character vector to a date object.- end_date
The end date of assessment/event (e.g.
AENDT
) A date or date-time object column is expected.Refer to
derive_vars_dt()
to impute and derive a date from a date character vector to a date object.Optional; Default is null. If the used and date value is missing on an observation, it is assumed the medication is ongoing and
ONTRTFL
is set to"Y"
.- ref_start_date
The lower bound of the on-treatment period Required; A date or date-time object column is expected.
Refer to
derive_vars_dt()
to impute and derive a date from a date character vector to a date object.- ref_end_date
The upper bound of the on-treatment period A date or date-time object column is expected.
Refer to
derive_vars_dt()
to impute and derive a date from a date character vector to a date object.Optional; This can be null and everything after
ref_start_date
will be considered on-treatment. Default isNULL
.- ref_end_window
A window to add to the upper bound
ref_end_date
measured in days (e.g. 7 if 7 days should be added to the upper bound) Optional; default is 0.- ignore_time_for_ref_end_date
If the argument is set to
TRUE
, the time part is ignored for checking if the event occurred more thanref_end_window
days after reference end date.Permitted Values:
TRUE
,FALSE
- filter_pre_timepoint
An expression to filter observations as not on-treatment when
date
=ref_start_date
. For example, if observations whereVSTPT = PRE
should not be considered on-treatment whendate = ref_start_date
,filter_pre_timepoint
should be used to denote when the on-treatment flag should be set to null. Optional; default isNULL
.- span_period
A
"Y"
scalar character. If"Y"
, events that started prior to theref_start_date
and are ongoing or end after theref_start_date
are flagged as"Y"
. Optional; default isNULL
.
Details
On-Treatment is calculated by determining whether the assessment
date or start/stop dates fall between 2 dates. The following logic is used
to assign on-treatment = "Y"
:
start_date
is missing andref_start_date
is non-missingNo timepoint filter is provided (
filter_pre_timepoint
) and bothstart_date
andref_start_date
are non-missing andstart_date
=ref_start_date
A timepoint is provided (
filter_pre_timepoint
) and bothstart_date
andref_start_date
are non-missing andstart_date = ref_start_date
and the filter provided infilter_pre_timepoint
is not true.ref_end_date
is not provided andref_start_date < start_date
ref_end_date
is provided andref_start_date < start_date
<=ref_end_date + ref_end_window
.
If the end_date
is provided and the end_date
< ref_start_date then the
ONTRTFL
is set to NULL
.This would be applicable to cases where the
start_date
is missing and ONTRTFL
has been assigned as "Y"
above.
If the span_period
is specified as "Y"
, this allows the user to assign
ONTRTFL
as "Y"
to cases where the record started prior to the
ref_start_date
and was ongoing or ended after the ref_start_date
.
Any date imputations needed should be done prior to calling this function.
See also
BDS-Findings Functions that returns variable appended to dataset:
derive_var_analysis_ratio()
,
derive_var_anrind()
,
derive_var_atoxgr_dir()
,
derive_var_atoxgr()
,
derive_var_basetype()
,
derive_var_base()
,
derive_var_chg()
,
derive_var_pchg()
,
derive_var_shift()
Examples
library(tibble)
library(dplyr, warn.conflicts = FALSE)
library(lubridate, warn.conflicts = FALSE)
advs <- tribble(
~USUBJID, ~ADT, ~TRTSDT, ~TRTEDT,
"P01", ymd("2020-02-24"), ymd("2020-01-01"), ymd("2020-03-01"),
"P02", ymd("2020-01-01"), ymd("2020-01-01"), ymd("2020-03-01"),
"P03", ymd("2019-12-31"), ymd("2020-01-01"), ymd("2020-03-01")
)
derive_var_ontrtfl(
advs,
start_date = ADT,
ref_start_date = TRTSDT,
ref_end_date = TRTEDT
)
#> # A tibble: 3 x 5
#> USUBJID ADT TRTSDT TRTEDT ONTRTFL
#> <chr> <date> <date> <date> <chr>
#> 1 P01 2020-02-24 2020-01-01 2020-03-01 Y
#> 2 P02 2020-01-01 2020-01-01 2020-03-01 Y
#> 3 P03 2019-12-31 2020-01-01 2020-03-01 NA
advs <- tribble(
~USUBJID, ~ADT, ~TRTSDT, ~TRTEDT,
"P01", ymd("2020-07-01"), ymd("2020-01-01"), ymd("2020-03-01"),
"P02", ymd("2020-04-30"), ymd("2020-01-01"), ymd("2020-03-01"),
"P03", ymd("2020-03-15"), ymd("2020-01-01"), ymd("2020-03-01")
)
derive_var_ontrtfl(
advs,
start_date = ADT,
ref_start_date = TRTSDT,
ref_end_date = TRTEDT,
ref_end_window = 60
)
#> # A tibble: 3 x 5
#> USUBJID ADT TRTSDT TRTEDT ONTRTFL
#> <chr> <date> <date> <date> <chr>
#> 1 P01 2020-07-01 2020-01-01 2020-03-01 NA
#> 2 P02 2020-04-30 2020-01-01 2020-03-01 Y
#> 3 P03 2020-03-15 2020-01-01 2020-03-01 Y
advs <- tribble(
~USUBJID, ~ADTM, ~TRTSDTM, ~TRTEDTM,
"P01", ymd_hm("2020-01-02T12:00"), ymd_hm("2020-01-01T12:00"), ymd_hm("2020-03-01T12:00"),
"P02", ymd("2020-01-01"), ymd_hm("2020-01-01T12:00"), ymd_hm("2020-03-01T12:00"),
"P03", ymd("2019-12-31"), ymd_hm("2020-01-01T12:00"), ymd_hm("2020-03-01T12:00"),
) %>%
mutate(TPT = c(NA, "PRE", NA))
derive_var_ontrtfl(
advs,
start_date = ADTM,
ref_start_date = TRTSDTM,
ref_end_date = TRTEDTM,
filter_pre_timepoint = TPT == "PRE"
)
#> # A tibble: 3 x 6
#> USUBJID ADTM TRTSDTM TRTEDTM TPT
#> <chr> <dttm> <dttm> <dttm> <chr>
#> 1 P01 2020-01-02 12:00:00 2020-01-01 12:00:00 2020-03-01 12:00:00 NA
#> 2 P02 2020-01-01 00:00:00 2020-01-01 12:00:00 2020-03-01 12:00:00 PRE
#> 3 P03 2019-12-31 00:00:00 2020-01-01 12:00:00 2020-03-01 12:00:00 NA
#> # … with 1 more variable: ONTRTFL <chr>
advs <- tribble(
~USUBJID, ~ASTDT, ~TRTSDT, ~TRTEDT, ~AENDT,
"P01", ymd("2020-03-15"), ymd("2020-01-01"), ymd("2020-03-01"), ymd("2020-12-01"),
"P02", ymd("2019-04-30"), ymd("2020-01-01"), ymd("2020-03-01"), ymd("2020-03-15"),
"P03", ymd("2019-04-30"), ymd("2020-01-01"), ymd("2020-03-01"), NA,
)
derive_var_ontrtfl(
advs,
start_date = ASTDT,
end_date = AENDT,
ref_start_date = TRTSDT,
ref_end_date = TRTEDT,
ref_end_window = 60,
span_period = "Y"
)
#> # A tibble: 3 x 6
#> USUBJID ASTDT TRTSDT TRTEDT AENDT ONTRTFL
#> <chr> <date> <date> <date> <date> <chr>
#> 1 P01 2020-03-15 2020-01-01 2020-03-01 2020-12-01 Y
#> 2 P02 2019-04-30 2020-01-01 2020-03-01 2020-03-15 Y
#> 3 P03 2019-04-30 2020-01-01 2020-03-01 NA Y
advs <- tribble(
~USUBJID, ~ASTDT, ~AP01SDT, ~AP01EDT, ~AENDT,
"P01", ymd("2020-03-15"), ymd("2020-01-01"), ymd("2020-03-01"), ymd("2020-12-01"),
"P02", ymd("2019-04-30"), ymd("2020-01-01"), ymd("2020-03-01"), ymd("2020-03-15"),
"P03", ymd("2019-04-30"), ymd("2020-01-01"), ymd("2020-03-01"), NA,
)
derive_var_ontrtfl(
advs,
new_var = ONTR01FL,
start_date = ASTDT,
end_date = AENDT,
ref_start_date = AP01SDT,
ref_end_date = AP01EDT,
span_period = "Y"
)
#> # A tibble: 3 x 6
#> USUBJID ASTDT AP01SDT AP01EDT AENDT ONTR01FL
#> <chr> <date> <date> <date> <date> <chr>
#> 1 P01 2020-03-15 2020-01-01 2020-03-01 2020-12-01 NA
#> 2 P02 2019-04-30 2020-01-01 2020-03-01 2020-03-15 Y
#> 3 P03 2019-04-30 2020-01-01 2020-03-01 NA Y