This article describes creating a BDS time-to-event ADaM.
The main part in programming a time-to-event dataset is the definition of the events and censoring times. {admiral} supports single events like death or composite events like disease progression or death. More than one source dataset can be used for the definition of the event and censoring times.
Note: All examples assume CDISC SDTM and/or ADaM format as input unless otherwise specified.
The examples of this vignette require the following packages.
library(admiral)
library(dplyr)
library(admiral.test)CNSR, ADT, STARTDT)AVAL)ASEQ)To start, all datasets needed for the creation of the time-to-event dataset should be read into the environment. This will be a company specific process.
For example purpose, the ADSL dataset—which is included in {admiral}—and the SDTM datasets from {admiral.test} are used.
data("admiral_ae")
data("admiral_adsl")
ae <- admiral_ae
adsl <- admiral_adslThe following code creates a minimally viable ADAE dataset to be used throughout the following examples.
adae <- ae %>%
left_join(adsl, by = c("STUDYID", "USUBJID")) %>%
derive_vars_dt(
new_vars_prefix = "AST",
dtc = AESTDTC,
highest_imputation = "M"
) %>%
derive_vars_dt(
new_vars_prefix = "AEN",
dtc = AEENDTC,
highest_imputation = "M",
date_imputation = "last"
) %>%
mutate(TRTEMFL = if_else(ASTDT >= TRTSDT &
AENDT <= TRTEDT + days(30), "Y", NA_character_))CNSR, ADT, STARTDT)To derive the parameter dependent variables like CNSR, ADT, STARTDT, EVNTDESC, SRCDOM, PARAMCD, … the derive_param_tte() function can be used. It adds one parameter to the input dataset with one observation per subject. Usually it is called several times.
For each subject it is determined if an event occurred. In the affirmative the analysis date ADT is set to the earliest event date. If no event occurred, the analysis date is set to the latest censoring date.
The events and censorings are defined by the event_source() and the censor_source() class respectively. It defines
filter parameter) of a source dataset (dataset_name parameter) are potential events or censorings,CNSR variable (censor parameter), anddate parameter).The date can be provided as date (--DT variable), datetime (--DTM variable), or character ISO-8601 date (--DTC variable).
CDISC strongly recommends CNSR = 0 for events and positive integers for censorings. {admiral} enforces this recommendation. Therefore the censor parameter is available for censor_source() only. It is defaulted to 1.
The dataset_name parameter expects a character value which is used as an identifier. The actual data which is used for the derivation of the parameter is provided via the source_datasets parameter of derive_param_tte(). It expects a named list of datasets. The names correspond to the identifiers specified for the dataset_name parameter. This allows to define events and censoring independent of the data.
The table below shows all pre-defined tte_source objects which should cover the most common use cases.
| object | dataset_name | filter | date | censor | set_values_to |
|---|---|---|---|---|---|
| ae_ser_event | adae | TRTEMFL == “Y” & AESER == “Y” | ASTDT | 0 | EVNTDESC: “SERIOUS ADVERSE EVENT” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
| ae_gr2_event | adae | TRTEMFL == “Y” & ATOXGR == “2” | ASTDT | 0 | EVNTDESC: “GRADE 2 ADVERSE EVENT” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
| ae_sev_event | adae | TRTEMFL == “Y” & AESEV == “SEVERE” | ASTDT | 0 | EVNTDESC: “SEVERE ADVERSE EVENT” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
| ae_gr4_event | adae | TRTEMFL == “Y” & ATOXGR == “4” | ASTDT | 0 | EVNTDESC: “GRADE 4 ADVERSE EVENT” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
| ae_gr3_event | adae | TRTEMFL == “Y” & ATOXGR == “3” | ASTDT | 0 | EVNTDESC: “GRADE 3 ADVERSE EVENT” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
| lastalive_censor | adsl | NULL | LSTALVDT | 1 | EVNTDESC: “ALIVE” SRCDOM: “ADSL” SRCVAR: “LSTALVDT” |
| ae_event | adae | TRTEMFL == “Y” | ASTDT | 0 | EVNTDESC: “ADVERSE EVENT” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
| death_event | adsl | DTHFL == “Y” | DTHDT | 0 | EVNTDESC: “DEATH” SRCDOM: “ADSL” SRCVAR: “DTHDT” |
| ae_gr35_event | adae | TRTEMFL == “Y” & ATOXGR %in% c(“3”, “4”, “5”) | ASTDT | 0 | EVNTDESC: “GRADE 3-5 ADVERSE EVENT” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
| ae_wd_event | adae | TRTEMFL == “Y” & AEACN == “DRUG WITHDRAWN” | ASTDT | 0 | EVNTDESC: “ADVERSE EVENT LEADING TO DRUG WITHDRAWAL” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
| ae_gr1_event | adae | TRTEMFL == “Y” & ATOXGR == “1” | ASTDT | 0 | EVNTDESC: “GRADE 1 ADVERSE EVENT” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
| ae_gr5_event | adae | TRTEMFL == “Y” & ATOXGR == “5” | ASTDT | 0 | EVNTDESC: “GRADE 5 ADVERSE EVENT” SRCDOM: “ADAE” SRCVAR: “ASTDT” SRCSEQ: AESEQ |
These pre-defined objects can be passed directly to derive_param_tte() to create a new time-to-event parameter.
adtte <- derive_param_tte(
dataset_adsl = adsl,
start_date = TRTSDT,
event_conditions = list(ae_ser_event),
censor_conditions = list(lastalive_censor),
source_datasets = list(adsl = adsl, adae = adae),
set_values_to = vars(PARAMCD = "TTAESER", PARAM = "Time to First Serious AE")
)| USUBJID | PARAMCD | PARAM | STARTDT | ADT | CNSR |
|---|---|---|---|---|---|
| 01-701-1015 | TTAESER | Time to First Serious AE | 2014-01-02 | 2014-07-02 | 1 |
| 01-701-1023 | TTAESER | Time to First Serious AE | 2012-08-05 | 2012-09-02 | 1 |
| 01-701-1028 | TTAESER | Time to First Serious AE | 2013-07-19 | 2014-01-14 | 1 |
| 01-701-1033 | TTAESER | Time to First Serious AE | 2014-03-18 | 2014-04-14 | 1 |
| 01-701-1034 | TTAESER | Time to First Serious AE | 2014-07-01 | 2014-12-30 | 1 |
| 01-701-1047 | TTAESER | Time to First Serious AE | 2013-02-12 | 2013-04-07 | 1 |
| 01-701-1097 | TTAESER | Time to First Serious AE | 2014-01-01 | 2014-07-09 | 1 |
| 01-701-1111 | TTAESER | Time to First Serious AE | 2012-09-07 | 2012-09-17 | 1 |
| 01-701-1115 | TTAESER | Time to First Serious AE | 2012-11-30 | 2013-01-23 | 1 |
| 01-701-1118 | TTAESER | Time to First Serious AE | 2014-03-12 | 2014-09-09 | 1 |
For example, the overall survival time could be defined from treatment start to death. Patients alive or lost to follow-up would be censored to the last alive date. The following call defines a death event based on ADSL variables.
death <- event_source(
dataset_name = "adsl",
filter = DTHFL == "Y",
date = DTHDT
)A corresponding censoring based on the last known alive date can be defined by the following call.
lstalv <- censor_source(
dataset_name = "adsl",
date = LSTALVDT
)The definitions can be passed to derive_param_tte() to create a new time-to-event parameter.
adtte <- derive_param_tte(
dataset_adsl = adsl,
source_datasets = list(adsl = adsl),
start_date = TRTSDT,
event_conditions = list(death),
censor_conditions = list(lstalv),
set_values_to = vars(PARAMCD = "OS", PARAM = "Overall Survival")
)| USUBJID | PARAMCD | PARAM | STARTDT | ADT | CNSR |
|---|---|---|---|---|---|
| 01-701-1015 | OS | Overall Survival | 2014-01-02 | 2014-07-02 | 1 |
| 01-701-1023 | OS | Overall Survival | 2012-08-05 | 2012-09-02 | 1 |
| 01-701-1028 | OS | Overall Survival | 2013-07-19 | 2014-01-14 | 1 |
| 01-701-1033 | OS | Overall Survival | 2014-03-18 | 2014-04-14 | 1 |
| 01-701-1034 | OS | Overall Survival | 2014-07-01 | 2014-12-30 | 1 |
| 01-701-1047 | OS | Overall Survival | 2013-02-12 | 2013-04-07 | 1 |
| 01-701-1097 | OS | Overall Survival | 2014-01-01 | 2014-07-09 | 1 |
| 01-701-1111 | OS | Overall Survival | 2012-09-07 | 2012-09-17 | 1 |
| 01-701-1115 | OS | Overall Survival | 2012-11-30 | 2013-01-23 | 1 |
| 01-701-1118 | OS | Overall Survival | 2014-03-12 | 2014-09-09 | 1 |
Note that in practice for efficacy parameters you might use randomization date as the time to event origin date.
EVNTDESC, SRCVAR, …)To add additional information like event or censoring description (EVNTDESC) or source variable (SRCVAR) the set_values_to parameter can be specified in the event/censoring definition.
# define death event #
death <- event_source(
dataset_name = "adsl",
filter = DTHFL == "Y",
date = DTHDT,
set_values_to = vars(
EVNTDESC = "DEATH",
SRCDOM = "ADSL",
SRCVAR = "DTHDT"
)
)
# define censoring at last known alive date #
lstalv <- censor_source(
dataset_name = "adsl",
date = LSTALVDT,
set_values_to = vars(
EVNTDESC = "LAST KNOWN ALIVE DATE",
SRCDOM = "ADSL",
SRCVAR = "LSTALVDT"
)
)
# derive time-to-event parameter #
adtte <- derive_param_tte(
dataset_adsl = adsl,
source_datasets = list(adsl = adsl),
event_conditions = list(death),
censor_conditions = list(lstalv),
set_values_to = vars(PARAMCD = "OS", PARAM = "Overall Survival")
)| USUBJID | EVNTDESC | SRCDOM | SRCVAR | CNSR | ADT |
|---|---|---|---|---|---|
| 01-701-1015 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-07-02 |
| 01-701-1023 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2012-09-02 |
| 01-701-1028 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-01-14 |
| 01-701-1033 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-04-14 |
| 01-701-1034 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-12-30 |
| 01-701-1047 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2013-04-07 |
| 01-701-1097 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-07-09 |
| 01-701-1111 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2012-09-17 |
| 01-701-1115 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2013-01-23 |
| 01-701-1118 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-09-09 |
If a subject has no event and has no record meeting the censoring rule, it will not be included in the output dataset. In order to have a record for this subject in the output dataset, another censoring_source() object should be created to specify how those patients will be censored. Therefore the start censoring is defined below to achieve that subjects without data in adrs are censored at the start date.
The ADaM IG requires that a computed date must be accompanied by imputation flags. Thus, if the function detects a --DTF and/or --TMF variable corresponding to start_date then STARTDTF and STARTTMF are set automatically to the values of these variables. If a date variable from one of the event or censoring source datasets is imputed, the imputation flag can be specified for the set_values_to parameter in event_source() or censor_source() (see definition of the start censoring below).
As the CDISC pilot does not contain a RS dataset, the following example for progression free survival uses manually created datasets.
View(adsl)| USUBJID | DTHFL | DTHDT | TRTSDT | TRTSDTF |
|---|---|---|---|---|
| 01 | Y | 2021-06-12 | 2021-01-01 | M |
| 02 | N | NA | 2021-02-03 | NA |
| 03 | Y | 2021-08-21 | 2021-08-10 | NA |
| 04 | N | NA | 2021-02-03 | NA |
| 05 | N | NA | 2021-04-01 | D |
View(adrs)| USUBJID | AVALC | ADT | ASEQ | PARAMCD | PARAM |
|---|---|---|---|---|---|
| 01 | SD | 2021-01-03 | 1 | OVR | Overall Response |
| 01 | PR | 2021-03-04 | 2 | OVR | Overall Response |
| 01 | PD | 2021-05-05 | 3 | OVR | Overall Response |
| 02 | PD | 2021-02-03 | 1 | OVR | Overall Response |
| 04 | SD | 2021-02-13 | 1 | OVR | Overall Response |
| 04 | PR | 2021-04-14 | 2 | OVR | Overall Response |
| 04 | CR | 2021-05-15 | 3 | OVR | Overall Response |
An event for progression free survival occurs if
Therefore two event_source() objects are defined:
pd for progression of disease anddeath for death.Some subjects may experience both events. In this case the first one is selected by derive_param_tte().
# progressive disease event #
pd <- event_source(
dataset_name = "adrs",
filter = AVALC == "PD",
date = ADT,
set_values_to = vars(
EVNTDESC = "PD",
SRCDOM = "ADRS",
SRCVAR = "ADT",
SRCSEQ = ASEQ
)
)
# death event #
death <- event_source(
dataset_name = "adsl",
filter = DTHFL == "Y",
date = DTHDT,
set_values_to = vars(
EVNTDESC = "DEATH",
SRCDOM = "ADSL",
SRCVAR = "DTHDT"
)
)Subjects without event must be censored at the last tumor assessment. For the censoring the lastvisit object is defined as all tumor assessments. Please note that it is not necessary to select the last one or exclude assessments which resulted in progression of disease. This is handled within derive_param_tte().
# last tumor assessment censoring (CNSR = 1 by default) #
lastvisit <- censor_source(
dataset_name = "adrs",
date = ADT,
set_values_to = vars(
EVNTDESC = "LAST TUMOR ASSESSMENT",
SRCDOM = "ADRS",
SRCVAR = "ADT"
)
)Patients without tumor assessment should be censored at the start date. Therefore the start object is defined with the treatment start date as censoring date. It is not necessary to exclude patient with tumor assessment in the definition of start because derive_param_tte() selects the last date across all censor_source() objects as censoring date.
# start date censoring (for patients without tumor assessment) (CNSR = 2) #
start <- censor_source(
dataset_name = "adsl",
date = TRTSDT,
censor = 2,
set_values_to = vars(
EVNTDESC = "TREATMENT START",
SRCDOM = "ADSL",
SRCVAR = "TRTSDT",
ADTF = TRTSDTF
)
)
# derive time-to-event parameter #
adtte <- derive_param_tte(
dataset_adsl = adsl,
source_datasets = list(adsl = adsl, adrs = adrs),
start_date = TRTSDT,
event_conditions = list(pd, death),
censor_conditions = list(lastvisit, start),
set_values_to = vars(PARAMCD = "PFS", PARAM = "Progression Free Survival")
)| USUBJID | PARAMCD | STARTDT | ADT | ADTF | CNSR |
|---|---|---|---|---|---|
| 01 | PFS | 2021-01-01 | 2021-05-05 | NA | 0 |
| 02 | PFS | 2021-02-03 | 2021-02-03 | NA | 0 |
| 03 | PFS | 2021-08-10 | 2021-08-21 | NA | 0 |
| 04 | PFS | 2021-02-03 | 2021-05-15 | NA | 1 |
| 05 | PFS | 2021-04-01 | 2021-04-01 | D | 2 |
If several similar time-to-event parameters need to be derived the call_derivation() function is useful.
In the following example parameters for time to first AE, time to first serious AE, and time to first related AE are derived. The censoring is the same for all three. Only the definition of the event differs.
# define censoring #
observation_end <- censor_source(
dataset_name = "adsl",
date = EOSDT,
censor = 1,
set_values_to = vars(
EVNTDESC = "END OF STUDY",
SRCDOM = "ADSL",
SRCVAR = "EOSDT"
)
)
# define time to first AE #
tt_ae <- event_source(
dataset_name = "ae",
date = ASTDT,
set_values_to = vars(
EVNTDESC = "ADVERSE EVENT",
SRCDOM = "AE",
SRCVAR = "AESTDTC"
)
)
# define time to first serious AE #
tt_ser_ae <- event_source(
dataset_name = "ae",
filter = AESER == "Y",
date = ASTDT,
set_values_to = vars(
EVNTDESC = "SERIOUS ADVERSE EVENT",
SRCDOM = "AE",
SRCVAR = "AESTDTC"
)
)
# define time to first related AE #
tt_rel_ae <- event_source(
dataset_name = "ae",
filter = AEREL %in% c("PROBABLE", "POSSIBLE", "REMOTE"),
date = ASTDT,
set_values_to = vars(
EVNTDESC = "RELATED ADVERSE EVENT",
SRCDOM = "AE",
SRCVAR = "AESTDTC"
)
)
# derive all three time to event parameters #
adaette <- call_derivation(
derivation = derive_param_tte,
variable_params = list(
params(
event_conditions = list(tt_ae),
set_values_to = vars(PARAMCD = "TTAE")
),
params(
event_conditions = list(tt_ser_ae),
set_values_to = vars(PARAMCD = "TTSERAE")
),
params(
event_conditions = list(tt_rel_ae),
set_values_to = vars(PARAMCD = "TTRELAE")
)
),
dataset_adsl = adsl,
source_datasets = list(adsl = adsl, ae = adae),
censor_conditions = list(observation_end)
)| USUBJID | PARAMCD | STARTDT | ADT | CNSR | EVNTDESC | SRCDOM | SRCVAR |
|---|---|---|---|---|---|---|---|
| 01-701-1015 | TTAE | 2014-01-02 | 2014-01-03 | 0 | ADVERSE EVENT | AE | AESTDTC |
| 01-701-1015 | TTRELAE | 2014-01-02 | 2014-01-03 | 0 | RELATED ADVERSE EVENT | AE | AESTDTC |
| 01-701-1015 | TTSERAE | 2014-01-02 | 2014-07-02 | 1 | END OF STUDY | ADSL | EOSDT |
| 01-701-1023 | TTAE | 2012-08-05 | 2012-08-07 | 0 | ADVERSE EVENT | AE | AESTDTC |
| 01-701-1023 | TTRELAE | 2012-08-05 | 2012-08-07 | 0 | RELATED ADVERSE EVENT | AE | AESTDTC |
| 01-701-1023 | TTSERAE | 2012-08-05 | 2012-09-02 | 1 | END OF STUDY | ADSL | EOSDT |
| 01-701-1028 | TTAE | 2013-07-19 | 2014-01-14 | 1 | END OF STUDY | ADSL | EOSDT |
| 01-701-1028 | TTRELAE | 2013-07-19 | 2014-01-14 | 1 | END OF STUDY | ADSL | EOSDT |
| 01-701-1028 | TTSERAE | 2013-07-19 | 2014-01-14 | 1 | END OF STUDY | ADSL | EOSDT |
| 01-701-1033 | TTAE | 2014-03-18 | 2014-04-14 | 1 | END OF STUDY | ADSL | EOSDT |
If time-to-event parameters need to be derived for each by group of a source dataset, the by_vars parameter can be specified. Then a time-to-event parameter is derived for each by group.
Please note that CDISC requires separate parameters (PARAMCD, PARAM) for the by groups. Therefore the variables specified for the by_vars parameter are not included in the output dataset. The PARAMCD variable should be specified for the set_value_to parameter using an expression on the right hand side which results in a unique value for each by group. If the values of the by variables should be included in the output dataset, they can be stored in PARCATn variables.
In the following example a time-to-event parameter for each preferred term in the AE dataset is derived.
View(adsl)| USUBJID | TRTSDT | EOSDT | STUDYID |
|---|---|---|---|
| 01 | 2020-12-06 | 2021-03-06 | AB42 |
| 02 | 2021-01-16 | 2021-02-03 | AB42 |
View(ae)| USUBJID | AESTDTC | AESEQ | AEDECOD | STUDYID | AESTDT |
|---|---|---|---|---|---|
| 01 | 2021-01-03T10:56 | 1 | Flu | AB42 | 2021-01-03 |
| 01 | 2021-03-04 | 2 | Cough | AB42 | 2021-03-04 |
| 01 | 2021 | 3 | Flu | AB42 | 2021-01-01 |
# define time to first adverse event event #
ttae <- event_source(
dataset_name = "ae",
date = AESTDT,
set_values_to = vars(
EVNTDESC = "AE",
SRCDOM = "AE",
SRCVAR = "AESTDTC",
SRCSEQ = AESEQ
)
)
# define censoring at end of study #
eos <- censor_source(
dataset_name = "adsl",
date = EOSDT,
set_values_to = vars(
EVNTDESC = "END OF STUDY",
SRCDOM = "ADSL",
SRCVAR = "EOSDT"
)
)
# derive time-to-event parameter #
adtte <- derive_param_tte(
dataset_adsl = adsl,
by_vars = vars(AEDECOD),
start_date = TRTSDT,
event_conditions = list(ttae),
censor_conditions = list(eos),
source_datasets = list(adsl = adsl, ae = ae),
set_values_to = vars(
PARAMCD = paste0("TTAE", as.numeric(as.factor(AEDECOD))),
PARAM = paste("Time to First", AEDECOD, "Adverse Event"),
PARCAT1 = "TTAE",
PARCAT2 = AEDECOD
)
)| USUBJID | STARTDT | PARAMCD | PARAM | ADT | CNSR | SRCSEQ |
|---|---|---|---|---|---|---|
| 01 | 2020-12-06 | TTAE1 | Time to First Cough Adverse Event | 2021-03-04 | 0 | 2 |
| 01 | 2020-12-06 | TTAE2 | Time to First Flu Adverse Event | 2021-01-01 | 0 | 3 |
| 02 | 2021-01-16 | TTAE1 | Time to First Cough Adverse Event | 2021-02-03 | 1 | NA |
| 02 | 2021-01-16 | TTAE2 | Time to First Flu Adverse Event | 2021-02-03 | 1 | NA |
AVAL)The analysis value (AVAL) can be derived by calling derive_vars_duration().
This example derives the time to event in days. Other units can be requested by the specifying the out_unit parameter.
adtte <- derive_vars_duration(
adtte,
new_var = AVAL,
start_date = STARTDT,
end_date = ADT
)| STUDYID | USUBJID | EVNTDESC | SRCDOM | SRCVAR | CNSR | ADT | STARTDT | PARAMCD | PARAM | AVAL |
|---|---|---|---|---|---|---|---|---|---|---|
| CDISCPILOT01 | 01-701-1015 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-07-02 | 2014-01-02 | OS | Overall Survival | 182 |
| CDISCPILOT01 | 01-701-1023 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2012-09-02 | 2012-08-05 | OS | Overall Survival | 29 |
| CDISCPILOT01 | 01-701-1028 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-01-14 | 2013-07-19 | OS | Overall Survival | 180 |
| CDISCPILOT01 | 01-701-1033 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-04-14 | 2014-03-18 | OS | Overall Survival | 28 |
| CDISCPILOT01 | 01-701-1034 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-12-30 | 2014-07-01 | OS | Overall Survival | 183 |
| CDISCPILOT01 | 01-701-1047 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2013-04-07 | 2013-02-12 | OS | Overall Survival | 55 |
| CDISCPILOT01 | 01-701-1097 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-07-09 | 2014-01-01 | OS | Overall Survival | 190 |
| CDISCPILOT01 | 01-701-1111 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2012-09-17 | 2012-09-07 | OS | Overall Survival | 11 |
| CDISCPILOT01 | 01-701-1115 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2013-01-23 | 2012-11-30 | OS | Overall Survival | 55 |
| CDISCPILOT01 | 01-701-1118 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-09-09 | 2014-03-12 | OS | Overall Survival | 182 |
ASEQ)The {admiral} function derive_var_obs_number() can be used to derive ASEQ:
adtte <- derive_var_obs_number(
adtte,
by_vars = vars(STUDYID, USUBJID),
order = vars(PARAMCD),
check_type = "error"
)| STUDYID | USUBJID | EVNTDESC | SRCDOM | SRCVAR | CNSR | ADT | STARTDT | PARAMCD | PARAM | AVAL | ASEQ |
|---|---|---|---|---|---|---|---|---|---|---|---|
| CDISCPILOT01 | 01-701-1015 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-07-02 | 2014-01-02 | OS | Overall Survival | 182 | 1 |
| CDISCPILOT01 | 01-701-1023 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2012-09-02 | 2012-08-05 | OS | Overall Survival | 29 | 1 |
| CDISCPILOT01 | 01-701-1028 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-01-14 | 2013-07-19 | OS | Overall Survival | 180 | 1 |
| CDISCPILOT01 | 01-701-1033 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-04-14 | 2014-03-18 | OS | Overall Survival | 28 | 1 |
| CDISCPILOT01 | 01-701-1034 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-12-30 | 2014-07-01 | OS | Overall Survival | 183 | 1 |
| CDISCPILOT01 | 01-701-1047 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2013-04-07 | 2013-02-12 | OS | Overall Survival | 55 | 1 |
| CDISCPILOT01 | 01-701-1097 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-07-09 | 2014-01-01 | OS | Overall Survival | 190 | 1 |
| CDISCPILOT01 | 01-701-1111 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2012-09-17 | 2012-09-07 | OS | Overall Survival | 11 | 1 |
| CDISCPILOT01 | 01-701-1115 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2013-01-23 | 2012-11-30 | OS | Overall Survival | 55 | 1 |
| CDISCPILOT01 | 01-701-1118 | LAST KNOWN ALIVE DATE | ADSL | LSTALVDT | 1 | 2014-09-09 | 2014-03-12 | OS | Overall Survival | 182 | 1 |
Variables from ADSL which are required for time-to-event analyses, e.g., treatment variables or covariates can be added using derive_vars_merged().
adtte <- derive_vars_merged(
adtte,
dataset_add = adsl,
new_vars = vars(ARMCD, ARM, ACTARMCD, ACTARM, AGE, SEX),
by_vars = vars(STUDYID, USUBJID)
)| USUBJID | PARAMCD | CNSR | AVAL | ARMCD | AGE | SEX |
|---|---|---|---|---|---|---|
| 01-701-1015 | OS | 1 | 182 | Pbo | 63 | F |
| 01-701-1023 | OS | 1 | 29 | Pbo | 64 | M |
| 01-701-1028 | OS | 1 | 180 | Xan_Hi | 71 | M |
| 01-701-1033 | OS | 1 | 28 | Xan_Lo | 74 | M |
| 01-701-1034 | OS | 1 | 183 | Xan_Hi | 77 | F |
| 01-701-1047 | OS | 1 | 55 | Pbo | 85 | F |
| 01-701-1097 | OS | 1 | 190 | Xan_Lo | 68 | M |
| 01-701-1111 | OS | 1 | 11 | Xan_Lo | 81 | F |
| 01-701-1115 | OS | 1 | 55 | Xan_Lo | 84 | M |
| 01-701-1118 | OS | 1 | 182 | Pbo | 52 | M |