derive_param_confirmed_resp {admiralonco}R Documentation

Adds a Parameter for Confirmed Response

Description

[Superseded] The derive_param_confirmed_resp() function has been superseded in favor of derive_extreme_event().

Adds a parameter for confirmed response

Usage

derive_param_confirmed_resp(
  dataset,
  dataset_adsl,
  filter_source,
  source_pd = NULL,
  source_datasets = NULL,
  ref_confirm,
  max_nr_ne = 1,
  accept_sd = FALSE,
  aval_fun,
  set_values_to,
  subject_keys = get_admiral_option("subject_keys")
)

Arguments

dataset

Input dataset

The PARAMCD, ADT, and AVALC variables and the variables specified by subject_keys and reference_date 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

ADSL input dataset

The variables specified for subject_keys are expected. For each subject of the specified dataset a new observation is added to the input dataset.

filter_source

Source filter

All observations in dataset_source fulfilling the specified condition are considered for deriving the confirmed response.

source_pd

Date of first progressive disease (PD)

If the parameter is specified, the observations of the input dataset for deriving the new parameter are restricted to observations up to the specified date. Observations at the specified date are included. For subjects without first PD date all observations are take into account.

Permitted Values: a date_source object (see admiral::date_source() for details)

source_datasets

Source dataset for the first PD date

A named list of datasets is expected. It links the dataset_name from source_pd with an existing dataset.

For example if source_pd = pd_date with 

pd_date <- date_source(
  dataset_name = "adrs",
  date = ADT,
  filter = PARAMCD == PD
)

and the actual response dataset in the script is myadrs, source_datasets = list(adrs = myadrs) should be specified.

ref_confirm

Minimum time period for confirmation

The assessment and the confirmatory assessment for "CR" and "PR" have to be at least the specified number of days apart.

max_nr_ne

The specified number of "NE" assessments between the assessment and the confirmatory assessment for "CR" and "PR" response is accepted.

Permitted Values: a non-negative numeric scalar

accept_sd

Accept "SD" for "PR"?

If the argument is set to TRUE, one "SD" assessment between the assessment and the confirmatory assessment for "PR" response is accepted. Otherwise, no "SD" assessment must occur between the two assessments.

Permitted Values: a logical scalar

aval_fun

Deprecated, please use set_values_to instead.

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.

set_values_to

Variables to set

A named list returned by exprs() defining the variables to be set for the new parameter, e.g. exprs(PARAMCD = "CRSP", PARAM = "Confirmed Response") is expected. The values must be symbols, character strings, numeric values, or NA.

subject_keys

Variables to uniquely identify a subject

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

Details

  1. The input dataset (dataset) is restricted to the observations matching filter_source and to observations before or at the date specified by source_pd.

  2. A subject is considered as responder if there is at least one observation in the restricted dataset with

    • AVALC == "CR",

    • there is a confirmatory assessment with AVALC == "CR" at least ref_confirm days after the assessment,

    • all assessments between the assessment and the confirmatory assessment are "CR" or "NE", and

    • there are at most max_nr_ne "NE" assessments between the assessment and the confirmatory assessment.

    or at least one observation with

    • AVALC == "PR",

    • there is a confirmatory assessment with AVALC %in% c("CR", "PR") at least ref_confirm days after the assessment,

    • all assessments between the assessment and the confirmatory assessment are "CR", "PR", "SD", or "NE",

    • there is no "PR" assessment after a "CR" assessment in the confirmation period,

    • there are at most max_nr_ne "NE" assessments between the assessment and the confirmatory assessment,

    • if the accept_sd argument is set to TRUE, one "SD" assessment in the confirmation period is accepted. Otherwise, no "SD" assessment must occur within the confirmation period.

  3. For responders AVALC is set to "Y" and ADT to the first date where the response criteria are fulfilled. For all other subjects in dataset_adsl AVALC is set to "N" and ADT to NA.

  4. The AVAL variable is added and set to aval_fun(AVALC).

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

  6. The new observations are added to input dataset.

Value

The input dataset with a new parameter for confirmed response

Author(s)

Stefan Bundfuss

See Also

Other superseded: derive_param_bor(), derive_param_clinbenefit(), derive_param_confirmed_bor(), derive_param_response(), filter_pd()

Examples


library(dplyr)
library(admiral)

# Create ADSL dataset
adsl <- tibble::tribble(
  ~USUBJID, ~TRTSDTC,
  "1",      "2020-01-01",
  "2",      "2019-12-12",
  "3",      "2019-11-11",
  "4",      "2019-12-30",
  "5",      "2020-01-01",
  "6",      "2020-02-02",
  "7",      "2020-02-02",
  "8",      "2020-04-01",
  "9",      "2020-03-01"
) %>%
  mutate(
    STUDYID = "XX1234"
  )

# Create ADRS dataset
ovr_obs <- tibble::tribble(
  ~USUBJID, ~ADTC,        ~AVALC,
  "1",      "2020-01-01", "PR",
  "1",      "2020-02-01", "CR",
  "1",      "2020-02-16", "NE",
  "1",      "2020-03-01", "CR",
  "1",      "2020-04-01", "SD",
  "2",      "2020-01-01", "SD",
  "2",      "2020-02-01", "PR",
  "2",      "2020-03-01", "SD",
  "2",      "2020-03-13", "CR",
  "3",      "2019-11-12", "CR",
  "3",      "2019-12-02", "CR",
  "3",      "2020-01-01", "SD",
  "4",      "2020-01-01", "PR",
  "4",      "2020-03-01", "SD",
  "4",      "2020-04-01", "SD",
  "4",      "2020-05-01", "PR",
  "4",      "2020-05-15", "NON-CR/NON-PD",
  "5",      "2020-01-01", "PR",
  "5",      "2020-01-10", "SD",
  "5",      "2020-01-20", "PR",
  "5",      "2020-05-15", "NON-CR/NON-PD",
  "6",      "2020-02-06", "PR",
  "6",      "2020-02-16", "CR",
  "6",      "2020-03-30", "PR",
  "6",      "2020-04-12", "PD",
  "6",      "2020-05-01", "CR",
  "6",      "2020-06-01", "CR",
  "7",      "2020-02-06", "PR",
  "7",      "2020-02-16", "CR",
  "7",      "2020-04-01", "NE",
  "9",      "2020-03-16", "CR",
  "9",      "2020-04-01", "NE",
  "9",      "2020-04-16", "NE",
  "9",      "2020-05-01", "CR"
) %>%
  mutate(PARAMCD = "OVR", ANL01FL = "Y")

pd_obs <-
  bind_rows(tibble::tribble(
    ~USUBJID, ~ADTC,        ~AVALC,
    "6",      "2020-04-12", "Y"
  ) %>%
    mutate(PARAMCD = "PD", ANL01FL = "Y"))

adrs <- bind_rows(ovr_obs, pd_obs) %>%
  mutate(
    ADT = lubridate::ymd(ADTC),
    STUDYID = "XX1234"
  ) %>%
  select(-ADTC)

pd_date <- date_source(
  dataset_name = "adrs",
  date = ADT,
  filter = PARAMCD == "PD" & ANL01FL == "Y"
)

# Derive confirmed response parameter
derive_param_confirmed_resp(
  adrs,
  dataset_adsl = adsl,
  filter_source = PARAMCD == "OVR" & ANL01FL == "Y",
  source_pd = pd_date,
  source_datasets = list(adrs = adrs),
  ref_confirm = 28,
  set_values_to = exprs(
    PARAMCD = "CRSP",
    PARAM = "Confirmed Response by Investigator"
  )
) %>%
  filter(PARAMCD == "CRSP")

# Derive confirmed response parameter (accepting SD for PR and two NEs)
derive_param_confirmed_resp(
  adrs,
  dataset_adsl = adsl,
  filter_source = PARAMCD == "OVR" & ANL01FL == "Y",
  source_pd = pd_date,
  source_datasets = list(adrs = adrs),
  ref_confirm = 28,
  max_nr_ne = 2,
  accept_sd = TRUE,
  set_values_to = exprs(
    PARAMCD = "CRSP",
    PARAM = "Confirmed Response by Investigator"
  )
) %>%
  filter(PARAMCD == "CRSP")
[Package admiralonco version 1.1.0 Index]