Skip to contents

Add a variable for the dose date or datetime of the last dose to the input dataset.

Usage

derive_var_last_dose_date(
  dataset,
  dataset_ex,
  filter_ex = NULL,
  by_vars = exprs(STUDYID, USUBJID),
  dose_id = exprs(),
  dose_date,
  analysis_date,
  single_dose_condition = (EXDOSFRQ == "ONCE"),
  new_var,
  output_datetime = TRUE,
  traceability_vars = NULL
)

Arguments

dataset

Input dataset. The variables specified by the by_vars and analysis_date parameters are expected.

dataset_ex

Input EX dataset. The variables specified by the by_vars, dose_date, new_vars parameters, and source variables from traceability_vars parameter are expected.

filter_ex

Filtering condition applied to EX dataset. For example, it can be used to filter for valid dose. Defaults to NULL.

by_vars

Variables to join by (created by rlang::exprs).

dose_id

Variables to identify unique dose (created by rlang::exprs). Defaults to empty exprs().

dose_date

The EX dose date variable. A date or date-time object is expected.

analysis_date

The analysis date variable. A date or date-time object is expected.

single_dose_condition

The condition for checking if dataset_ex is single dose. An error is issued if the condition is not true. Defaults to (EXDOSFRQ == "ONCE").

new_var

The new date or datetime variable added to dataset.

output_datetime

Display new_var as datetime or as date only. Defaults to TRUE.

traceability_vars

A named list returned by exprs() listing the traceability variables, e.g. exprs(LDOSEDOM = "EX", LDOSESEQ = EXSEQ). The left-hand side (names of the list elements) gives the names of the traceability variables in the returned dataset. The right-hand side (values of the list elements) gives the values of the traceability variables in the returned dataset. These can be either strings or symbols referring to existing variables.

Value

Input dataset with additional column new_var.

Details

The last dose date is derived as the maximum dose date where the dose_date is lower to or equal to the analysis_date per by_vars for each observation in dataset. When output_datetime is TRUE and time is missing, then the last dose date time is imputed to 00:00:00. However, if date is missing, then no imputation is done.

If dose information is aggregated (i.e. is a dosing frequency other than "ONCE" over a period defined by a start and end date) the function create_single_dose_dataset() can be used to generate single doses from aggregate dose information and satisfy single_dose_condition.

Examples

library(dplyr, warn.conflicts = FALSE)
library(admiral.test)
data(admiral_ae)
data(ex_single)

ex_single <- derive_vars_dtm(
  head(ex_single, 100),
  dtc = EXENDTC,
  new_vars_prefix = "EXEN",
  flag_imputation = "none"
)

adae <- admiral_ae %>%
  head(100) %>%
  derive_vars_dtm(
    dtc = AESTDTC,
    new_vars_prefix = "AST",
    highest_imputation = "M"
  )

adae %>%
  derive_var_last_dose_date(
    dataset_ex = ex_single,
    filter_ex = (EXDOSE > 0 | (EXDOSE == 0 & grepl("PLACEBO", EXTRT))) &
      !is.na(EXENDTM),
    dose_date = EXENDTM,
    analysis_date = ASTDTM,
    new_var = LDOSEDTM,
    traceability_vars = exprs(LDOSEDOM = "EX", LDOSESEQ = EXSEQ, LDOSEVAR = "EXDOSE")
  ) %>%
  select(STUDYID, USUBJID, AESEQ, AESTDTC, LDOSEDOM, LDOSESEQ, LDOSEVAR, LDOSEDTM)
#> # A tibble: 100 x 8
#>    STUDYID  USUBJID AESEQ AESTDTC LDOSEDOM LDOSESEQ LDOSEVAR LDOSEDTM           
#>    <chr>    <chr>   <dbl> <chr>   <chr>       <int> <chr>    <dttm>             
#>  1 CDISCPI… 01-701…     1 2014-0… NA             NA NA       NA                 
#>  2 CDISCPI… 01-701…     2 2014-0… NA             NA NA       NA                 
#>  3 CDISCPI… 01-701…     3 2014-0… NA             NA NA       NA                 
#>  4 CDISCPI… 01-701…     3 2012-0… EX              7 EXDOSE   2012-08-11 00:00:00
#>  5 CDISCPI… 01-701…     1 2012-0… EX              3 EXDOSE   2012-08-07 00:00:00
#>  6 CDISCPI… 01-701…     2 2012-0… EX              3 EXDOSE   2012-08-07 00:00:00
#>  7 CDISCPI… 01-701…     4 2012-0… EX              3 EXDOSE   2012-08-07 00:00:00
#>  8 CDISCPI… 01-701…     1 2013-0… NA             NA NA       NA                 
#>  9 CDISCPI… 01-701…     2 2013-0… NA             NA NA       NA                 
#> 10 CDISCPI… 01-701…     1 2014-0… NA             NA NA       NA                 
#> # … with 90 more rows