Adds a Parameter for Confirmed Best Overall Response
Source:R/derive_param_confirmed_bor.R
derive_param_confirmed_bor.Rd
The derive_param_confirmed_bor()
function has been superseded in favor of derive_extreme_event()
.
Adds a parameter for confirmed best overall response (BOR)
Usage
derive_param_confirmed_bor(
dataset,
dataset_adsl,
filter_source,
source_pd = NULL,
source_datasets = NULL,
reference_date,
ref_start_window,
ref_confirm,
max_nr_ne = 1,
accept_sd = FALSE,
missing_as_ne = FALSE,
aval_fun,
set_values_to,
subject_keys = get_admiral_option("subject_keys")
)
Arguments
- dataset
Input dataset
The
PARAMCD
,ADT
, andAVALC
variables and the variables specified bysubject_keys
andreference_date
are expected.After applying
filter_source
and/orsource_pd
the variableADT
and the variables specified bysubject_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 best overall 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 (seeadmiral::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
fromsource_pd
with an existing dataset.For example if
source_pd = pd_date
withpd_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.- reference_date
Reference date
The reference date is used for the derivation of
"SD"
and"NON-CR/NON-PD"
response (see "Details" section). Usually it is treatment start date (TRTSDT
) or randomization date (RANDDT
).Permitted Values: a numeric date variable
- ref_start_window
Stable disease time window
Assessments at least the specified number of days after the reference date (i.e. where
ADT
>=reference_date
+ref_start_window
) with response"CR"
,"PR"
,"SD"
, or"NON-CR/NON-PD"
are considered for"SD"
or"NON-CR/NON-PD"
response.Permitted Values: a non-negative numeric scalar
- 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
- missing_as_ne
Consider no assessments as
"NE"
?If the argument is set to
TRUE
, the response is set to"NE"
for subjects without an assessment in the input dataset. Otherwise, the response is set to"MISSING"
for these subjects.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 = "CBOR", PARAM = "Confirmed Best Overall Response")
is expected. The values must be symbols, character strings, numeric values, orNA
.- subject_keys
Variables to uniquely identify a subject
A list of symbols created using
exprs()
is expected.
Details
The input dataset (
dataset
) is restricted to the observations matchingfilter_source
and to observations before or at the date specified bysource_pd
.The following potential confirmed responses are selected from the restricted input dataset:
"CR"
: An assessment is considered as complete response (CR) ifAVALC == "CR"
,there is a confirmatory assessment with
AVALC == "CR"
at leastref_confirm
days after the assessment,all assessments between the assessment and the confirmatory assessment are
"CR"
or"NE"
, andthere are at most
max_nr_ne
"NE"
assessments between the assessment and the confirmatory assessment.
"PR"
: An assessment is considered as partial response (PR) ifAVALC == "PR"
,there is a confirmatory assessment with
AVALC %in% c("CR", "PR")
at leastref_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, andif the
accept_sd
argument is set toTRUE
, one"SD"
assessment in the confirmation period is accepted. Otherwise, no"SD"
assessment must occur within the confirmation period.
"SD"
: An assessment is considered as stable disease (SD) ifAVALC %in% c("CR", "PR", "SD")
andthe assessment is at least
ref_start_window
days afterreference_date
.
"NON-CR/NON-PD"
: An assessment is considered as NON-CR/NON-PD ifAVALC = "NON-CR/NON-PD"
andthe assessment is at least
ref_start_window
days afterreference_date
.
"PD"
: An assessment is considered as progressive disease (PD) ifAVALC == "PD"
."NE"
: An assessment is considered as not estimable (NE) ifAVALC == "NE"
orAVALC %in% c("CR", "PR", "SD", "NON-CR/NON-PD")
and the assessment is less thanref_start_window
days afterreference_date
.
"ND"
: An assessment is considered as not done (ND) ifAVALC == "ND"
."MISSING"
: An assessment is considered as missing (MISSING) if a subject has no observation in the input dataset.If the
missing_as_ne
argument is set toTRUE
,AVALC
is set to"NE"
for these subjects.
For each subject the best response as derived in the previous step is selected, where
"CR"
is best and"MISSING"
is worst in the order above. If the best response is not unique, the first one (with respect toADT
) is selected. If the selected record is from the input dataset, all variables are kept. If the selected record is fromdataset_adsl
, all variables which are in bothdataset
anddataset_adsl
are kept.The
AVAL
variable is added and set toaval_fun(AVALC)
.The variables specified by the
set_values_to
parameter are added to the new observations.The new observations are added to input dataset.
See also
Other superseded:
derive_param_bor()
,
derive_param_clinbenefit()
,
derive_param_confirmed_resp()
,
derive_param_response()
,
filter_pd()
Examples
library(dplyr)
library(lubridate)
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(
TRTSDT = ymd(TRTSDTC),
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 = ymd(ADTC),
STUDYID = "XX1234"
) %>%
select(-ADTC) %>%
derive_vars_merged(
dataset_add = adsl,
by_vars = exprs(STUDYID, USUBJID),
new_vars = exprs(TRTSDT)
)
pd_date <- date_source(
dataset_name = "adrs",
date = ADT,
filter = PARAMCD == "PD" & ANL01FL == "Y"
)
# Derive confirmed best overall response parameter
derive_param_confirmed_bor(
adrs,
dataset_adsl = adsl,
filter_source = PARAMCD == "OVR" & ANL01FL == "Y",
source_pd = pd_date,
source_datasets = list(adrs = adrs),
reference_date = TRTSDT,
ref_start_window = 28,
ref_confirm = 28,
set_values_to = exprs(
PARAMCD = "CBOR",
PARAM = "Best Confirmed Overall Response by Investigator"
)
) %>%
filter(PARAMCD == "CBOR")
#> Warning: Dataset contains CR records followed by PR.
#> Run `get_crpr_dataset()` to access the CR records records followed by PR
#> # A tibble: 9 × 8
#> USUBJID AVALC PARAMCD ANL01FL ADT STUDYID TRTSDT PARAM
#> <chr> <chr> <chr> <chr> <date> <chr> <date> <chr>
#> 1 1 CR CBOR Y 2020-02-01 XX1234 2020-01-01 Best Conf…
#> 2 2 SD CBOR Y 2020-02-01 XX1234 2019-12-12 Best Conf…
#> 3 3 SD CBOR Y 2020-01-01 XX1234 2019-11-11 Best Conf…
#> 4 4 SD CBOR Y 2020-03-01 XX1234 2019-12-30 Best Conf…
#> 5 5 NON-CR/NON-PD CBOR Y 2020-05-15 XX1234 2020-01-01 Best Conf…
#> 6 6 SD CBOR Y 2020-03-30 XX1234 2020-02-02 Best Conf…
#> 7 7 NE CBOR Y 2020-02-06 XX1234 2020-02-02 Best Conf…
#> 8 8 MISSING CBOR NA NA XX1234 2020-04-01 Best Conf…
#> 9 9 SD CBOR Y 2020-05-01 XX1234 2020-03-01 Best Conf…
# Derive confirmed best overall response parameter (accepting SD for PR,
# accept two NEs, and considering missings as NE)
derive_param_confirmed_bor(
adrs,
dataset_adsl = adsl,
filter_source = PARAMCD == "OVR" & ANL01FL == "Y",
source_pd = pd_date,
source_datasets = list(adrs = adrs),
reference_date = TRTSDT,
ref_start_window = 28,
ref_confirm = 28,
max_nr_ne = 2,
accept_sd = TRUE,
missing_as_ne = TRUE,
set_values_to = exprs(
PARAMCD = "CBOR",
PARAM = "Best Confirmed Overall Response by Investigator"
)
) %>%
filter(PARAMCD == "CBOR")
#> Warning: Dataset contains CR records followed by PR.
#> Run `get_crpr_dataset()` to access the CR records records followed by PR
#> # A tibble: 9 × 8
#> USUBJID AVALC PARAMCD ANL01FL ADT STUDYID TRTSDT PARAM
#> <chr> <chr> <chr> <chr> <date> <chr> <date> <chr>
#> 1 1 CR CBOR Y 2020-02-01 XX1234 2020-01-01 Best Conf…
#> 2 2 PR CBOR Y 2020-02-01 XX1234 2019-12-12 Best Conf…
#> 3 3 SD CBOR Y 2020-01-01 XX1234 2019-11-11 Best Conf…
#> 4 4 SD CBOR Y 2020-03-01 XX1234 2019-12-30 Best Conf…
#> 5 5 NON-CR/NON-PD CBOR Y 2020-05-15 XX1234 2020-01-01 Best Conf…
#> 6 6 SD CBOR Y 2020-03-30 XX1234 2020-02-02 Best Conf…
#> 7 7 NE CBOR Y 2020-02-06 XX1234 2020-02-02 Best Conf…
#> 8 8 NE CBOR NA NA XX1234 2020-04-01 Best Conf…
#> 9 9 CR CBOR Y 2020-03-16 XX1234 2020-03-01 Best Conf…