derive_vars_last_dose: Derive Last Dose
In epijim/admiral: ADaM in R Asset Library

Description Usage Arguments Details Value Author(s) Examples

Add EX source variables from last dose to the input dataset.

derive_vars_last_dose(
  dataset,
  dataset_ex,
  filter_ex = NULL,
  by_vars = vars(STUDYID, USUBJID),
  dose_id = vars(),
  dose_date,
  analysis_date,
  single_dose_condition = (EXDOSFRQ == "ONCE"),
  new_vars = NULL,
  traceability_vars = NULL
)

`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 `dplyr::vars`).
`dose_id`	Variables to identify unique dose (created by `dplyr::vars`). Defaults to empty `vars()`.
`dose_date`	The EX dose date variable.
`analysis_date`	The analysis date variable.
`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_vars`	Variables to keep from `dataset_ex`, with the option to rename. Can either be variables created by `dplyr::vars` (e.g. `vars(VISIT)`), or named list returned by `vars()` (e.g. `vars(LSTEXVIS = VISIT)`). If set to `NULL`, then all variables from `dataset_ex` are kept without renaming. Defaults to `NULL`.
`traceability_vars`	A named list returned by `vars()` listing the traceability variables, e.g. `vars(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.

All date (date-time) variables can be characters in standard ISO format or of date / date-time class. For ISO format, see impute_dtc - parameter dtc for further details. When doing date comparison to identify last dose, date-time imputations are done as follows:

dose_date: no date imputation, time imputation to 00:00:00 if time is missing.
analysis_date: no date imputation, time imputation to 23:59:59 if time is missing.

The last dose records are identified as follows:

The dataset_ex is filtered using filter_ex, if provided. This is useful for, for example, filtering for valid dose only.
The datasets dataset and dataset_ex are joined using by_vars.
The last dose is identified: the last dose is the EX record with maximum date where dose_date is lower to or equal to analysis_date, subject to both date values are non-NA. The last dose is identified per by_vars. If multiple EX records exist for the same dose_date, then either dose_id needs to be supplied (e.g. dose_id = vars(EXSEQ)) to identify unique records, or an error is issued. When dose_id is supplied, the last EX record from the same dose_date sorted by dose_id will be used to identify last dose.
The EX source variables (as specified in new_vars) from last dose are appended to the dataset and returned to the user.

This function only works correctly for EX dataset with a structure of single dose per row. If your study EX dataset has multiple doses per row, use expansion_function_name?? to transform the EX dataset into single dose per row structure before calling derive_vars_last_dose.

If variables (other than those specified in by_vars) exist in both dataset and dataset_ex, then join cannot be performed properly and an error is issued. To resolve the error, use new_vars to either keep variables unique to dataset_ex, or use this option to rename variables from dataset_ex (e.g. new_vars = vars(LSTEXVIS = VISIT)).

Input dataset with EX source variables from last dose added.

Ondrej Slama, Annie Yang

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

ae %>%
  head(100) %>%
  derive_vars_last_dose(
    head(ex_single, 100),
    filter_ex = (EXDOSE > 0 | (EXDOSE == 0 & grepl("PLACEBO", EXTRT))) &
      nchar(EXENDTC) >= 10,
    new_vars = vars(EXDOSE, EXTRT, EXSEQ, EXENDTC, VISIT),
    dose_date = EXENDTC,
    analysis_date = AESTDTC,
    single_dose_condition = (EXSTDTC == EXENDTC)
  ) %>%
  select(STUDYID, USUBJID, AESEQ, AESTDTC, EXDOSE, EXTRT, EXENDTC, EXSEQ, VISIT)

# or with traceability variables
ae %>%
  head(100) %>%
  derive_vars_last_dose(
    head(ex_single, 100),
    filter_ex = (EXDOSE > 0 | (EXDOSE == 0 & grepl("PLACEBO", EXTRT))) &
      nchar(EXENDTC) >= 10,
    new_vars = vars(EXDOSE, EXTRT, EXSEQ, EXENDTC, VISIT),
    dose_date = EXENDTC,
    analysis_date = AESTDTC,
    single_dose_condition = (EXSTDTC == EXENDTC),
    traceability_vars = dplyr::vars(LDOSEDOM = "EX", LDOSESEQ = EXSEQ, LDOSEVAR = "EXENDTC")
  ) %>%
  select(STUDYID, USUBJID, AESEQ, AESTDTC, EXDOSE, EXTRT, EXENDTC, LDOSEDOM, LDOSESEQ, LDOSEVAR)