derive_param_exposure: Add an Aggregated Parameter and Derive the Associated Start...
In epijim/admiral: ADaM in R Asset Library

Description Usage Arguments Details Value Author(s) Examples

Add a record computed from the aggregated analysis value of another parameter and compute the start (ASTDT(M))and end date (AENDT(M)) as the minimum and maximum date by by_vars.

derive_param_exposure(
  dataset,
  by_vars,
  input_code,
  analysis_var,
  summary_fun,
  filter = NULL,
  set_values_to = NULL
)

`dataset`	Input dataset The variables specified by the `by_vars`,`analysis_var` parameters and `PARAMCD` are expected, Either `ASTDTM` and `AENDTM` or `ASTDT` and `AENDT` are also expected.
`by_vars`	Grouping variables For each group defined by `by_vars` an observation is added to the output dataset. Permitted Values: list of variables
`input_code`	Required parameter code The observations where `PARAMCD` equals the specified value are considered to compute the summary record. Permitted Values: A character of `PARAMCD` value
`analysis_var`	Analysis variable.
`summary_fun`	Function that takes as an input the `analysis_var` and performs the calculation. This can include built-in functions as well as user defined functions, for example `mean` or `function(x) mean(x, na.rm = TRUE)`.
`filter`	Filter condition The specified condition is applied to the input dataset before deriving the new parameter, i.e., only observations fulfilling the condition are taken into account. Permitted Values: a condition
`set_values_to`	Variable-value pairs Set a list of variables to some specified value for the new observation(s) LHS refer to a variable. It is expected that at least `PARAMCD` is defined. RHS refers to the values to set to the variable. This can be a string, a symbol, a numeric value or NA. (e.g. `vars(PARAMCD = "TDOSE",PARCAT1 = "OVERALL")`). More general expression are not allowed. Permitted Values: List of variable-value pairs

For each group (with respect to the variables specified for the by_vars parameter), an observation is added to the output dataset and the defined values are set to the defined variables

The input dataset with a new record added for each group (with respect to the variables specified for the by_vars parameter). For each new record,

the variable specified analysis_var is computed as defined by summary_fun,
the variable(s) specified on the LHS of set_values_to are set to their paired value (RHS). In addition, the start and end date are computed as the minimum/maximum dates by by_vars.

If the input datasets contains

both AxxDTM and AxxDT then all ASTDTM,AENDTM, ASTDT, AENDT are computed
only AxxDTM then ASTDTM,AENDTM are computed
only AxxDT then ASTDT,AENDT are computed.

Samia Kabi

library(dplyr, warn.conflicts = FALSE)
library(lubridate, warn.conflicts = FALSE)
library(stringr, warn.conflicts = FALSE)
adex <- tibble::tribble(
  ~USUBJID, ~PARAMCD, ~AVAL, ~AVALC, ~VISIT, ~ASTDT, ~AENDT,
  "1015", "DOSE", 80, NA_character_, "BASELINE", ymd("2014-01-02"), ymd("2014-01-16"),
  "1015", "DOSE", 85, NA_character_, "WEEK 2", ymd("2014-01-17"), ymd("2014-06-18"),
  "1015", "DOSE", 82, NA_character_, "WEEK 24", ymd("2014-06-19"), ymd("2014-07-02"),
  "1015", "ADJ", NA, NA_character_, "BASELINE", ymd("2014-01-02"), ymd("2014-01-16"),
  "1015", "ADJ", NA, NA_character_, "WEEK 2", ymd("2014-01-17"), ymd("2014-06-18"),
  "1015", "ADJ", NA, NA_character_, "WEEK 24", ymd("2014-06-19"), ymd("2014-07-02"),
  "1017", "DOSE", 80, NA_character_, "BASELINE", ymd("2014-01-05"), ymd("2014-01-19"),
  "1017", "DOSE", 50, NA_character_, "WEEK 2", ymd("2014-01-20"), ymd("2014-05-10"),
  "1017", "DOSE", 65, NA_character_, "WEEK 24", ymd("2014-05-10"), ymd("2014-07-02"),
  "1017", "ADJ", NA, NA_character_, "BASELINE", ymd("2014-01-05"), ymd("2014-01-19"),
  "1017", "ADJ", NA, "ADVERSE EVENT", "WEEK 2", ymd("2014-01-20"), ymd("2014-05-10"),
  "1017", "ADJ", NA, NA_character_, "WEEK 24", ymd("2014-05-10"), ymd("2014-07-02")
) %>%
  mutate(ASTDTM = ymd_hms(paste(ASTDT, "00:00:00")), AENDTM = ymd_hms(paste(AENDT, "00:00:00")))

# Cumulative dose
adex %>%
  derive_param_exposure(
    by_vars = vars(USUBJID),
    set_values_to = vars(PARAMCD = "TDOSE", PARCAT1 = "OVERALL"),
    input_code = "DOSE",
    analysis_var = AVAL,
    summary_fun = function(x) sum(x, na.rm = TRUE)
   ) %>%
  select(-ASTDTM, -AENDTM)

# average dose in w2-24
adex %>%
  derive_param_exposure(
    by_vars = vars(USUBJID),
    filter = VISIT %in% c("WEEK 2", "WEEK 24"),
    set_values_to = vars(PARAMCD = "AVDW224", PARCAT1 = "WEEK2-24"),
    input_code = "DOSE",
    analysis_var = AVAL,
    summary_fun = function(x) mean(x, na.rm = TRUE)
  ) %>%
  select(-ASTDTM, -AENDTM)

# Any dose adjustment?
adex %>%
  derive_param_exposure(
    by_vars = vars(USUBJID),
    set_values_to = vars(PARAMCD = "TADJ", PARCAT1 = "OVERALL"),
    input_code = "ADJ",
    analysis_var = AVALC,
    summary_fun = function(x) if_else(sum(!is.na(x)) > 0, "Y", NA_character_)
  ) %>%
  select(-ASTDTM, -AENDTM)