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Adds a Parameter Indicating If a Subject Had a Response before Progressive Disease

Source: R/derive_param_response.R
derive_param_response.Rd

Adds a parameter indicating if a response has been observed. If a response has been observed, AVALC is set to "Y", AVAL to 1 and ADT is set to the first date when a response has been observed. If a response has not been observed, AVALC is set to "N", AVAL to 0 and ADT is set NA.

Usage

derive_param_response(
  dataset,
  dataset_adsl,
  filter_source,
  source_pd = NULL,
  source_datasets = NULL,
  set_values_to,
  aval_fun = yn_to_numeric,
  subject_keys = get_admiral_option("subject_keys")
)

Arguments

dataset

Input dataset

The variables specified by the subject_keysand ADT are expected.

After applying filter_source and/or source_pd the variable ADT and the variables specified by subject_keys must be a unique key of the dataset.

dataset_adsl

Input dataset

  • The variables specified for subject_keys are expected.

  • For each observation of the specified dataset a new observation is added to the input dataset. This is to capture those patients that may never have had a tumor assessment.

filter_source

Source filter

All observations in the dataset data fulfilling the specified condition are selected.

source_pd

Sources and conditions defining the end of the assessment period for the responses.

An object of type date_source is expected

All observations in dataset defining the response data fulfilling the filter_source condition are considered as response if they fall before the end of the assessment period as defined by source_pd.

  • For subjects with at least one response before the end of the assessment period, AVALC is set to "Y", AVAL to 1, and ADT to the first date when the response occurred.

  • For all other subjects AVALC is set to "N", AVAL to 0, and ADT to NA.

source_datasets

Source dataset

A named list of datasets with one element is expected (e.g. list(adrs= adrs)).

The name must match the dataset_name field of the admiral::date_source() object specified for source_pd.

The variables specified by the subject_keys argument and the date field of the admiral::date_source() object are expected in the dataset.

set_values_to

Variables to set

A named list returned by vars() defining the variables to be set for the new parameter, e.g. vars(PARAMCD = "RSP", PARAM = "Response by investigator") is expected.

The values must be symbols, character strings, numeric values or NA.

aval_fun

Function to map character analysis value (AVALC) to numeric analysis value (AVAL)

The (first) argument of the function must expect a character vector and the function must return a numeric vector.

subject_keys

Variables to uniquely identify a subject

A list of symbols created using vars() is expected.

Value

The input dataset with a new parameter indicating if and when a response occurred

Details

  1. The Date of the end of the assessment period (e.g. Progressive disease, as defined by pd_source) is added to the response dataset.

  2. The response dataset is restricted to observations occurring before ** or on ** the date of progressive disease.

  3. For each subject (with respect to the variables specified for the subject_keys parameter), the first observation (with respect to ADT) where the response condition (filter_source parameter) is fulfilled is selected.

  4. For each observation in dataset_adsl a new observation is created.

  • For subjects with a response AVALC is set to "Y", AVAL to 1, and ADT to the first date (ADT) where the response condition is fulfilled.

  • For all other subjects AVALC is set to "N", AVAL to 0 and ADT to NA.

  1. The variables specified by the set_values_to parameter are added to the new observations.

  2. The new observations are added to input dataset.

See also

ADRS Functions for adding Parameters: derive_param_bor(), derive_param_clinbenefit(), derive_param_confirmed_bor(), derive_param_confirmed_resp()

Author

Samia Kabi

Examples

library(dplyr)
library(admiral)
library(lubridate)
library(rlang)
#> 
#> Attaching package: ‘rlang’
#> The following object is masked from ‘package:magrittr’:
#> 
#>     set_names

adsl <- tibble::tribble(
  ~USUBJID,
  "1",
  "2",
  "3",
  "4"
) %>%
  mutate(STUDYID = "XX1234")

adrs <- tibble::tribble(
  ~USUBJID, ~PARAMCD, ~ADTC,         ~AVALC, ~ANL01FL,
  "1",      "OVR",    "2020-01-02",  "PR",   "Y",
  "1",      "OVR",    "2020-02-01",  "CR",   "Y",
  "1",      "OVR",    "2020-03-01",  "CR",   "Y",
  "1",      "OVR",    "2020-04-01",  "SD",   "Y",
  "1",      "PD",     NA_character_, "N",    "Y",
  "2",      "OVR",    "2021-06-15",  "SD",   "Y",
  "2",      "OVR",    "2021-07-16",  "PD",   "Y",
  "2",      "OVR",    "2021-09-14",  "PD",   "Y",
  "2",      "PD",     "2021-09-14",  "Y",    "Y",
  "3",      "OVR",    "2021-09-14",  "SD",   "Y",
  "3",      "OVR",    "2021-10-30",  "PD",   "Y",
  "3",      "OVR",    "2021-12-25",  "CR",   "Y",
  "3",      "PD",     "2021-10-30",  "Y",    "Y"
) %>%
  mutate(
    STUDYID = "XX1234",
    ADT = ymd(ADTC),
    ANL01FL = "Y"
  ) %>%
  select(-ADTC)

# Define the end of the assessment period for responses:
# all responses before or on the first PD will be used.
pd <- date_source(
  dataset_name = "adrs",
  date = ADT,
  filter = PARAMCD == "PD" & AVALC == "Y"
)
# Derive the response parameter
derive_param_response(
  dataset = adrs,
  dataset_adsl = adsl,
  filter_source = PARAMCD == "OVR" & AVALC %in% c("CR", "PR") & ANL01FL == "Y",
  source_pd = pd,
  source_datasets = list(adrs = adrs),
  set_values_to = vars(
    PARAMCD = "RSP",
    PARAM = "Response by investigator"
  ),
  subject_keys = get_admiral_option("subject_keys")
) %>%
  arrange(USUBJID, PARAMCD, ADT)
#> # A tibble: 17 x 8
#>    USUBJID PARAMCD AVALC ANL01FL STUDYID ADT        PARAM                   AVAL
#>    <chr>   <chr>   <chr> <chr>   <chr>   <date>     <chr>                  <dbl>
#>  1 1       OVR     PR    Y       XX1234  2020-01-02 NA                        NA
#>  2 1       OVR     CR    Y       XX1234  2020-02-01 NA                        NA
#>  3 1       OVR     CR    Y       XX1234  2020-03-01 NA                        NA
#>  4 1       OVR     SD    Y       XX1234  2020-04-01 NA                        NA
#>  5 1       PD      N     Y       XX1234  NA         NA                        NA
#>  6 1       RSP     Y     Y       XX1234  2020-01-02 Response by investiga…     1
#>  7 2       OVR     SD    Y       XX1234  2021-06-15 NA                        NA
#>  8 2       OVR     PD    Y       XX1234  2021-07-16 NA                        NA
#>  9 2       OVR     PD    Y       XX1234  2021-09-14 NA                        NA
#> 10 2       PD      Y     Y       XX1234  2021-09-14 NA                        NA
#> 11 2       RSP     N     NA      XX1234  NA         Response by investiga…     0
#> 12 3       OVR     SD    Y       XX1234  2021-09-14 NA                        NA
#> 13 3       OVR     PD    Y       XX1234  2021-10-30 NA                        NA
#> 14 3       OVR     CR    Y       XX1234  2021-12-25 NA                        NA
#> 15 3       PD      Y     Y       XX1234  2021-10-30 NA                        NA
#> 16 3       RSP     N     NA      XX1234  NA         Response by investiga…     0
#> 17 4       RSP     N     NA      XX1234  NA         Response by investiga…     0