Skip to contents

Add an Aggregated Parameter and Derive the Associated Start and End Dates

Source: R/derive_param_exposure.R
derive_param_exposure.Rd

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.

Usage

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

Arguments

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. Only variables specified in by_vars will be populated in the newly created records.

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. exprs(PARAMCD = "TDOSE",PARCAT1 = "OVERALL")). More general expression are not allowed.

Permitted Values: List of variable-value pairs

Value

The input dataset with a new record added for each group (with respect to the variables specified for the by_vars parameter). That is, a variable will only be populated in this new record if it is specified in by_vars. 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.

Details

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

See also

BDS-Findings Functions for adding Parameters/Records: default_qtc_paramcd(), derive_expected_records(), derive_extreme_event(), derive_extreme_records(), derive_locf_records(), derive_param_bmi(), derive_param_bsa(), derive_param_computed(), derive_param_doseint(), derive_param_exist_flag(), derive_param_extreme_event(), derive_param_framingham(), derive_param_map(), derive_param_qtc(), derive_param_rr(), derive_param_wbc_abs(), derive_summary_records()

Examples

library(tibble)
library(dplyr, warn.conflicts = FALSE)
library(lubridate, warn.conflicts = FALSE)
library(stringr, warn.conflicts = FALSE)
adex <- 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 = exprs(USUBJID),
    set_values_to = exprs(PARAMCD = "TDOSE", PARCAT1 = "OVERALL"),
    input_code = "DOSE",
    analysis_var = AVAL,
    summary_fun = function(x) sum(x, na.rm = TRUE)
  ) %>%
  select(-ASTDTM, -AENDTM)
#> # A tibble: 14 x 8
#>    USUBJID PARAMCD  AVAL AVALC         VISIT    ASTDT      AENDT      PARCAT1
#>    <chr>   <chr>   <dbl> <chr>         <chr>    <date>     <date>     <chr>  
#>  1 1015    DOSE       80 NA            BASELINE 2014-01-02 2014-01-16 NA     
#>  2 1015    DOSE       85 NA            WEEK 2   2014-01-17 2014-06-18 NA     
#>  3 1015    DOSE       82 NA            WEEK 24  2014-06-19 2014-07-02 NA     
#>  4 1015    ADJ        NA NA            BASELINE 2014-01-02 2014-01-16 NA     
#>  5 1015    ADJ        NA NA            WEEK 2   2014-01-17 2014-06-18 NA     
#>  6 1015    ADJ        NA NA            WEEK 24  2014-06-19 2014-07-02 NA     
#>  7 1017    DOSE       80 NA            BASELINE 2014-01-05 2014-01-19 NA     
#>  8 1017    DOSE       50 NA            WEEK 2   2014-01-20 2014-05-10 NA     
#>  9 1017    DOSE       65 NA            WEEK 24  2014-05-10 2014-07-02 NA     
#> 10 1017    ADJ        NA NA            BASELINE 2014-01-05 2014-01-19 NA     
#> 11 1017    ADJ        NA ADVERSE EVENT WEEK 2   2014-01-20 2014-05-10 NA     
#> 12 1017    ADJ        NA NA            WEEK 24  2014-05-10 2014-07-02 NA     
#> 13 1015    TDOSE     247 NA            NA       2014-01-02 2014-07-02 OVERALL
#> 14 1017    TDOSE     195 NA            NA       2014-01-05 2014-07-02 OVERALL

# average dose in w2-24
adex %>%
  derive_param_exposure(
    by_vars = exprs(USUBJID),
    filter = VISIT %in% c("WEEK 2", "WEEK 24"),
    set_values_to = exprs(PARAMCD = "AVDW224", PARCAT1 = "WEEK2-24"),
    input_code = "DOSE",
    analysis_var = AVAL,
    summary_fun = function(x) mean(x, na.rm = TRUE)
  ) %>%
  select(-ASTDTM, -AENDTM)
#> # A tibble: 14 x 8
#>    USUBJID PARAMCD  AVAL AVALC         VISIT    ASTDT      AENDT      PARCAT1 
#>    <chr>   <chr>   <dbl> <chr>         <chr>    <date>     <date>     <chr>   
#>  1 1015    DOSE     80   NA            BASELINE 2014-01-02 2014-01-16 NA      
#>  2 1015    DOSE     85   NA            WEEK 2   2014-01-17 2014-06-18 NA      
#>  3 1015    DOSE     82   NA            WEEK 24  2014-06-19 2014-07-02 NA      
#>  4 1015    ADJ      NA   NA            BASELINE 2014-01-02 2014-01-16 NA      
#>  5 1015    ADJ      NA   NA            WEEK 2   2014-01-17 2014-06-18 NA      
#>  6 1015    ADJ      NA   NA            WEEK 24  2014-06-19 2014-07-02 NA      
#>  7 1017    DOSE     80   NA            BASELINE 2014-01-05 2014-01-19 NA      
#>  8 1017    DOSE     50   NA            WEEK 2   2014-01-20 2014-05-10 NA      
#>  9 1017    DOSE     65   NA            WEEK 24  2014-05-10 2014-07-02 NA      
#> 10 1017    ADJ      NA   NA            BASELINE 2014-01-05 2014-01-19 NA      
#> 11 1017    ADJ      NA   ADVERSE EVENT WEEK 2   2014-01-20 2014-05-10 NA      
#> 12 1017    ADJ      NA   NA            WEEK 24  2014-05-10 2014-07-02 NA      
#> 13 1015    AVDW224  83.5 NA            NA       2014-01-17 2014-07-02 WEEK2-24
#> 14 1017    AVDW224  57.5 NA            NA       2014-01-20 2014-07-02 WEEK2-24

# Any dose adjustment?
adex %>%
  derive_param_exposure(
    by_vars = exprs(USUBJID),
    set_values_to = exprs(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)
#> # A tibble: 14 x 8
#>    USUBJID PARAMCD  AVAL AVALC         VISIT    ASTDT      AENDT      PARCAT1
#>    <chr>   <chr>   <dbl> <chr>         <chr>    <date>     <date>     <chr>  
#>  1 1015    DOSE       80 NA            BASELINE 2014-01-02 2014-01-16 NA     
#>  2 1015    DOSE       85 NA            WEEK 2   2014-01-17 2014-06-18 NA     
#>  3 1015    DOSE       82 NA            WEEK 24  2014-06-19 2014-07-02 NA     
#>  4 1015    ADJ        NA NA            BASELINE 2014-01-02 2014-01-16 NA     
#>  5 1015    ADJ        NA NA            WEEK 2   2014-01-17 2014-06-18 NA     
#>  6 1015    ADJ        NA NA            WEEK 24  2014-06-19 2014-07-02 NA     
#>  7 1017    DOSE       80 NA            BASELINE 2014-01-05 2014-01-19 NA     
#>  8 1017    DOSE       50 NA            WEEK 2   2014-01-20 2014-05-10 NA     
#>  9 1017    DOSE       65 NA            WEEK 24  2014-05-10 2014-07-02 NA     
#> 10 1017    ADJ        NA NA            BASELINE 2014-01-05 2014-01-19 NA     
#> 11 1017    ADJ        NA ADVERSE EVENT WEEK 2   2014-01-20 2014-05-10 NA     
#> 12 1017    ADJ        NA NA            WEEK 24  2014-05-10 2014-07-02 NA     
#> 13 1015    TADJ       NA NA            NA       2014-01-02 2014-07-02 OVERALL
#> 14 1017    TADJ       NA Y             NA       2014-01-05 2014-07-02 OVERALL