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Derive Treatment-emergent Flag

Source: R/derive_var_trtemfl.R
derive_var_trtemfl.Rd

Derive treatment emergent analysis flag (e.g., TRTEMFL).

Usage 

derive_var_trtemfl(
  dataset,
  new_var = TRTEMFL,
  start_date = ASTDTM,
  end_date = AENDTM,
  trt_start_date = TRTSDTM,
  trt_end_date = NULL,
  end_window = NULL,
  ignore_time_for_trt_end = TRUE,
  initial_intensity = NULL,
  intensity = NULL,
  group_var = NULL,
  subject_keys = get_admiral_option("subject_keys")
)

Arguments

dataset

Input dataset

The variables specified by start_date, end_date, trt_start_date, trt_end_date, initial_intensity, and intensity are expected.

Permitted values

a dataset, i.e., a data.frame or tibble

Default value

none

new_var

New variable

Permitted values

an unquoted symbol, e.g., AVAL

Default value

TRTEMFL

start_date

Event start date

Permitted values

a date or datetime variable

Default value

ASTDTM

end_date

Event end date

Permitted values

a date or datetime variable

Default value

AENDTM

trt_start_date

Treatment start date

Permitted values

a date or datetime variable

Default value

TRTSDTM

trt_end_date

Treatment end date

Permitted values

a date or datetime variable

Default value

NULL

end_window

If the argument is specified (in 'days'), events starting more than the specified number of days after end of treatment, are not flagged.

Permitted values

a positive integer, e.g. 2 or 5

Default value

NULL

ignore_time_for_trt_end

If the argument is set to TRUE, the time part is ignored for checking if the event occurred more than end_window days after end of treatment.

Permitted values

TRUE, FALSE

Default value

TRUE

initial_intensity

Initial severity/intensity or toxicity

initial_intensity is ignored when group_var is specified.

If this argument is specified and group_var is NULL, events which start before treatment start and end after treatment start (or are ongoing) and worsened (i.e., the intensity is greater than the initial intensity), are flagged.

The values of the specified variable must be comparable with the usual comparison operators. I.e., if the intensity is greater than the initial intensity initial_intensity < intensity must evaluate to TRUE.

Permitted values

an unquoted symbol, e.g., AVAL

Default value

NULL

intensity

Severity/intensity or toxicity

If the argument is specified, events which start before treatment start and end after treatment start (or are ongoing) and worsened (i.e., the intensity is greater than the initial intensity), are flagged.

The values of the specified variable must be comparable with the usual comparison operators. I.e., if the intensity is greater than the initial intensity initial_intensity < intensity must evaluate to TRUE.

Permitted values

an unquoted symbol, e.g., AVAL

Default value

NULL

group_var

Grouping variable

If the argument is specified, it assumes that AEs are recorded as one episode of AE with multiple lines using a grouping variable.

Events starting during treatment or before treatment and worsening afterward are flagged. Once an AE record in a group is flagged, all subsequent records in the treatment window are flagged regardless of severity.

Permitted values

an unquoted symbol, e.g., AVAL

Default value

NULL

subject_keys

Variables to uniquely identify a subject.

This argument is only used when group_var is specified.

Permitted values

list of variables created by exprs(), e.g., exprs(USUBJID, VISIT)

Default value

get_admiral_option("subject_keys")

Value

The input dataset with the variable specified by new_var added

Details

For the derivation of the new variable the following cases are considered in this order. The first case which applies, defines the value of the variable.

  • not treated: If trt_start_date is NA, it is set to NA_character_.

  • event before treatment: If end_date is before trt_start_date (and end_date is not NA), it is set to NA_character_.

  • no event date: If start_date is NA, it is set to "Y" as in such cases it is usually considered more conservative to assume the event was treatment-emergent.

  • event started during treatment:

    • if end_window is not specified: if start_date is on or after trt_start_date, it is set to "Y",

    • if end_window is specified: if start_date is on or after trt_start_date and start_date is on or before trt_end_date + end_window days, it is set to "Y",

  • event started before treatment and (possibly) worsened on treatment:

    • if initial_intensity, intensity is specified and group_var is not specified: if initial_intensity < intensity and start_date is before trt_start_date and end_date is on or after trt_start_date or end_date is NA, it is set to "Y";

    • if group_var is specified: if intensity at treatment start < intensity and start_date is after trt_start_date and end_date is on or after trt_start_date or end_date is NA, it is set to "Y";

  • Otherwise it is set to NA_character_.

The behavior of derive_var_trtemfl() is aligned with the proposed treatment-emergent AE assignment in the following PHUSE White Paper. See the final example in the examples section below.

See also

OCCDS Functions: derive_vars_atc(), derive_vars_query()

Examples

Basic treatment-emergent flag

Derive TRTEMFL without considering treatment end and worsening

  • For this basic example, all we are using are AE start/end dates and comparing those against treatment start date.

  • If the AE started on or after treatment then we flag as treatment-emergent (e.g. records 5-7).

  • If missing AE start date then we flag as treatment-emergent as worst case (e.g. records 8, 11 and 13), unless we know that the AE end date was before treatment so we can rule out this being treatment-emergent (e.g. record 12).

  • Any not treated subject would not get their AEs flagged as treatment-emergent (e.g. records 14-16).

library(tibble)
library(dplyr, warn.conflicts = FALSE)
library(lubridate)

adae <- tribble(
  ~USUBJID, ~ASTDT,            ~AENDT,            ~AEITOXGR, ~AETOXGR,
  # before treatment
  "1",      ymd("2021-12-13"), ymd("2021-12-15"), "1",       "1",
  "1",      ymd("2021-12-14"), ymd("2021-12-14"), "1",       "3",
  # starting before treatment and ending during treatment
  "1",      ymd("2021-12-30"), ymd("2022-01-14"), "1",       "3",
  "1",      ymd("2021-12-31"), ymd("2022-01-01"), "1",       "1",
  # starting during treatment
  "1",      ymd("2022-01-01"), ymd("2022-01-02"), "3",       "4",
  # after treatment
  "1",      ymd("2022-05-10"), ymd("2022-05-10"), "2",       "2",
  "1",      ymd("2022-05-11"), ymd("2022-05-11"), "2",       "2",
  # missing dates
  "1",      NA,                NA,                "3",       "4",
  "1",      ymd("2021-12-30"), NA,                "3",       "4",
  "1",      ymd("2021-12-31"), NA,                "3",       "3",
  "1",      NA,                ymd("2022-01-04"), "3",       "4",
  "1",      NA,                ymd("2021-12-24"), "3",       "4",
  "1",      NA,                ymd("2022-06-04"), "3",       "4",
  # without treatment
  "2",      NA,                ymd("2021-12-03"), "1",       "2",
  "2",      ymd("2021-12-01"), ymd("2021-12-03"), "1",       "2",
  "2",      ymd("2021-12-06"), NA,                "1",       "2"
) %>%
  mutate(
    STUDYID = "AB42",
    TRTSDT = if_else(USUBJID == "1", ymd("2022-01-01"), NA),
    TRTEDT = if_else(USUBJID == "1", ymd("2022-04-30"), NA)
  )

derive_var_trtemfl(
  adae,
  start_date = ASTDT,
  end_date = AENDT,
  trt_start_date = TRTSDT
) %>% select(USUBJID, TRTSDT, ASTDT, AENDT, TRTEMFL)
#> # A tibble: 16 × 5
#>    USUBJID TRTSDT     ASTDT      AENDT      TRTEMFL
#>    <chr>   <date>     <date>     <date>     <chr>
#>  1 1       2022-01-01 2021-12-13 2021-12-15 <NA>
#>  2 1       2022-01-01 2021-12-14 2021-12-14 <NA>
#>  3 1       2022-01-01 2021-12-30 2022-01-14 <NA>
#>  4 1       2022-01-01 2021-12-31 2022-01-01 <NA>
#>  5 1       2022-01-01 2022-01-01 2022-01-02 Y
#>  6 1       2022-01-01 2022-05-10 2022-05-10 Y
#>  7 1       2022-01-01 2022-05-11 2022-05-11 Y
#>  8 1       2022-01-01 NA         NA         Y
#>  9 1       2022-01-01 2021-12-30 NA         <NA>
#> 10 1       2022-01-01 2021-12-31 NA         <NA>
#> 11 1       2022-01-01 NA         2022-01-04 Y
#> 12 1       2022-01-01 NA         2021-12-24 <NA>
#> 13 1       2022-01-01 NA         2022-06-04 Y
#> 14 2       NA         NA         2021-12-03 <NA>
#> 15 2       NA         2021-12-01 2021-12-03 <NA>
#> 16 2       NA         2021-12-06 NA         <NA>

Considering treatment end date (trt_end_date and end_window)

Derive TRTEMFL taking a treatment end window into account

  • In addition to the treatment-emergent checks explained in the above example, we now supply a treatment end date, trt_end_date = TRTEDT and an end window, end_window = 10. With these, any AE which started on or before treatment end date + 10 days is considered as treatment-emergent. Otherwise, those starting after the treatment end window are no longer flagged as treatment-emergent (e.g. record 7).

derive_var_trtemfl(
  adae,
  start_date = ASTDT,
  end_date = AENDT,
  trt_start_date = TRTSDT,
  trt_end_date = TRTEDT,
  end_window = 10
) %>% select(USUBJID, TRTSDT, TRTEDT, ASTDT, AENDT, TRTEMFL)
#> # A tibble: 16 × 6
#>    USUBJID TRTSDT     TRTEDT     ASTDT      AENDT      TRTEMFL
#>    <chr>   <date>     <date>     <date>     <date>     <chr>
#>  1 1       2022-01-01 2022-04-30 2021-12-13 2021-12-15 <NA>
#>  2 1       2022-01-01 2022-04-30 2021-12-14 2021-12-14 <NA>
#>  3 1       2022-01-01 2022-04-30 2021-12-30 2022-01-14 <NA>
#>  4 1       2022-01-01 2022-04-30 2021-12-31 2022-01-01 <NA>
#>  5 1       2022-01-01 2022-04-30 2022-01-01 2022-01-02 Y
#>  6 1       2022-01-01 2022-04-30 2022-05-10 2022-05-10 Y
#>  7 1       2022-01-01 2022-04-30 2022-05-11 2022-05-11 <NA>
#>  8 1       2022-01-01 2022-04-30 NA         NA         Y
#>  9 1       2022-01-01 2022-04-30 2021-12-30 NA         <NA>
#> 10 1       2022-01-01 2022-04-30 2021-12-31 NA         <NA>
#> 11 1       2022-01-01 2022-04-30 NA         2022-01-04 Y
#> 12 1       2022-01-01 2022-04-30 NA         2021-12-24 <NA>
#> 13 1       2022-01-01 2022-04-30 NA         2022-06-04 Y
#> 14 2       NA         NA         NA         2021-12-03 <NA>
#> 15 2       NA         NA         2021-12-01 2021-12-03 <NA>
#> 16 2       NA         NA         2021-12-06 NA         <NA>

Considering treatment worsening (initial_intensity and intensity)

Derive a new variable named TRTEM2FL taking worsening after treatment start into account

  • We also now start look at changes in intensity following treatment start using the initial_intensity and intensity arguments. This only impacts AEs starting before treatment, and ending on or after treatment (or with missing AE end date). We can additionally consider treatment-emergence for an AE that was ongoing at the start of treatment which may have worsened as a result of treatment, i.e. the most extreme intensity is greater than the initial intensity (e.g. records 3 and 9).

derive_var_trtemfl(
  adae,
  new_var = TRTEM2FL,
  start_date = ASTDT,
  end_date = AENDT,
  trt_start_date = TRTSDT,
  trt_end_date = TRTEDT,
  end_window = 10,
  initial_intensity = AEITOXGR,
  intensity = AETOXGR
) %>% select(USUBJID, TRTSDT, ASTDT, AENDT, AEITOXGR, AETOXGR, TRTEM2FL)
#> # A tibble: 16 × 7
#>    USUBJID TRTSDT     ASTDT      AENDT      AEITOXGR AETOXGR TRTEM2FL
#>    <chr>   <date>     <date>     <date>     <chr>    <chr>   <chr>
#>  1 1       2022-01-01 2021-12-13 2021-12-15 1        1       <NA>
#>  2 1       2022-01-01 2021-12-14 2021-12-14 1        3       <NA>
#>  3 1       2022-01-01 2021-12-30 2022-01-14 1        3       Y
#>  4 1       2022-01-01 2021-12-31 2022-01-01 1        1       <NA>
#>  5 1       2022-01-01 2022-01-01 2022-01-02 3        4       Y
#>  6 1       2022-01-01 2022-05-10 2022-05-10 2        2       Y
#>  7 1       2022-01-01 2022-05-11 2022-05-11 2        2       <NA>
#>  8 1       2022-01-01 NA         NA         3        4       Y
#>  9 1       2022-01-01 2021-12-30 NA         3        4       Y
#> 10 1       2022-01-01 2021-12-31 NA         3        3       <NA>
#> 11 1       2022-01-01 NA         2022-01-04 3        4       Y
#> 12 1       2022-01-01 NA         2021-12-24 3        4       <NA>
#> 13 1       2022-01-01 NA         2022-06-04 3        4       Y
#> 14 2       NA         NA         2021-12-03 1        2       <NA>
#> 15 2       NA         2021-12-01 2021-12-03 1        2       <NA>
#> 16 2       NA         2021-12-06 NA         1        2       <NA>

Worsening when the same AE is collected over multiple records (intensity and group_var)

Derive TRTEMFL taking worsening after treatment into account within a grouping variable

  • Firstly, to understand which records correspond to the same AE, we need to supply a grouping variable (group_var). Then this example works in a similar way to the above one, but here we don't have an initial intensity so we have to use the intensity of the AE at the time of treatment start. If an ongoing AE increases intensity after treatment start (i.e. worsens), then from that point on the records are considered treatment-emergent, unless after the treatment end window (e.g. records 4, 6 and 7).

adae2 <- tribble(
  ~USUBJID, ~ASTDT,            ~AENDT,            ~AETOXGR, ~AEGRPID,
  # ongoing AE where intensity drops after treatment start
  "1",      ymd("2021-12-31"), ymd("2022-01-01"), "3",      "1",
  "1",      ymd("2022-01-02"), ymd("2022-01-11"), "2",      "1",
  # ongoing AE where intensity increases after treatment start
  "1",      ymd("2021-12-31"), ymd("2022-01-01"), "1",      "2",
  "1",      ymd("2022-01-02"), ymd("2022-01-11"), "2",      "2",
  # ongoing AE where intensity increases after treatment start and then drops
  "1",      ymd("2021-12-31"), ymd("2022-01-01"), "1",      "3",
  "1",      ymd("2022-01-02"), ymd("2022-01-11"), "2",      "3",
  "1",      ymd("2022-01-12"), ymd("2022-01-15"), "1",      "3"
) %>%
  mutate(
    STUDYID = "AB42",
    TRTSDT = if_else(USUBJID == "1", ymd("2022-01-01"), NA),
    TRTEDT = if_else(USUBJID == "1", ymd("2022-04-30"), NA)
  )

derive_var_trtemfl(
  adae2,
  start_date = ASTDT,
  end_date = AENDT,
  trt_start_date = TRTSDT,
  trt_end_date = TRTEDT,
  end_window = 10,
  intensity = AETOXGR,
  group_var = AEGRPID
) %>% select(USUBJID, TRTSDT, ASTDT, AENDT, AETOXGR, AEGRPID, TRTEMFL)
#> # A tibble: 7 × 7
#>   USUBJID TRTSDT     ASTDT      AENDT      AETOXGR AEGRPID TRTEMFL
#>   <chr>   <date>     <date>     <date>     <chr>   <chr>   <chr>
#> 1 1       2022-01-01 2021-12-31 2022-01-01 3       1       <NA>
#> 2 1       2022-01-01 2022-01-02 2022-01-11 2       1       <NA>
#> 3 1       2022-01-01 2021-12-31 2022-01-01 1       2       <NA>
#> 4 1       2022-01-01 2022-01-02 2022-01-11 2       2       Y
#> 5 1       2022-01-01 2021-12-31 2022-01-01 1       3       <NA>
#> 6 1       2022-01-01 2022-01-02 2022-01-11 2       3       Y
#> 7 1       2022-01-01 2022-01-12 2022-01-15 1       3       Y

Further Examples from PHUSE White Paper

Here we present more cases (some new, some similar to the examples above) which are aligned one-to-one with the scenarios in the PHUSE White Paper

adae3 <- tribble(
  ~USUBJID, ~TRTSDTM, ~TRTEDTM, ~ASTDTM, ~AENDTM, ~AEITOXGR, ~AETOXGR,
  # Patient 1: Pre-treatment AE
  "1", "2021-01-01", "2021-12-31", "2020-12-20", "2020-12-21", "2", "2",
  # Patient 2: On-treatment AE
  "2", "2021-01-01", "2021-12-31", "2021-12-20", "2021-12-21", "2", "2",
  # Patient 3: Pre-treatment AE, then on-treatment AE at same intensity
  "3", "2021-01-01", "2021-12-31", "2020-12-20", "2020-12-21", "2", "2",
  "3", "2021-01-01", "2021-12-31", "2021-12-20", "2021-12-21", "2", "2",
  # Patient 4: Pre-treatment AE, then on-treatment AE at wors. intensity
  "4", "2021-01-01", "2021-12-31", "2020-12-20", "2020-12-21", "2", "2",
  "4", "2021-01-01", "2021-12-31", "2021-12-20", "2021-12-21", "2", "3",
  # Patient 5: Pre-treatment AE, then on-treatment AE at impr. intensity
  "5", "2021-01-01", "2021-12-31", "2020-12-20", "2020-12-21", "2", "2",
  "5", "2021-01-01", "2021-12-31", "2021-12-20", "2021-12-21", "2", "1",
  # Patient 6: AE starting pre-treatment, continuing on-treatment, then 2nd AE at same intensity
  "6", "2021-01-01", "2021-12-31", "2020-12-23", "2021-01-21", "2", "2",
  "6", "2021-01-01", "2021-12-31", "2021-12-20", "2021-12-21", "2", "2",
  # Patient 7: AE starting pre-treatment, continuing on-treatment, then 2nd AE at wors. intensity
  "7", "2021-01-01", "2021-12-31", "2020-12-23", "2021-01-21", "2", "2",
  "7", "2021-01-01", "2021-12-31", "2021-12-20", "2021-12-21", "2", "3",
  # Patient 8: AE starting pre-treatment, continuing on-treatment, then 2nd AE at impr. intensity
  "8", "2021-01-01", "2021-12-31", "2020-12-23", "2021-01-21", "2", "2",
  "8", "2021-01-01", "2021-12-31", "2021-12-20", "2021-12-21", "2", "1",
  # Patient 9: AE starting pre-treatment, continuing on-treatment, and no change in intensity
  "9", "2021-01-01", "2021-12-31", "2020-12-23", "2021-01-21", "2", "2",
  # Patient 10: AE starting pre-treatment, continuing on-treatment, and wors. intensity
  "10", "2021-01-01", "2021-12-31", "2020-12-23", "2021-01-21", "2", "4",
  # Patient 11: AE starting pre-treatment, continuing on-treatment, and impr. intensity
  "11", "2021-01-01", "2021-12-31", "2020-12-23", "2021-01-21", "2", "1",
  # Patient 12: AE starting pre-treatment, worsening, then improving
  "12", "2021-01-01", "2021-12-31", "2020-12-23", "2021-01-21", "3", "2",
  # Patient 13: AE starting pre-treatment, improving, then worsening
  "13", "2021-01-01", "2021-12-31", "2020-12-23", "2021-01-21", "1", "2",
) %>%
  mutate(
    ASTDTM = ymd(ASTDTM),
    AENDTM = ymd(AENDTM),
    TRTSDTM = ymd(TRTSDTM),
    TRTEDTM = ymd(TRTEDTM),
  )

derive_var_trtemfl(
  adae3,
  new_var = TRTEMFL,
  trt_end_date = TRTEDTM,
  end_window = 0,
  initial_intensity = AEITOXGR,
  intensity = AETOXGR,
  subject_keys = exprs(USUBJID)
) %>%
  select(USUBJID, TRTSDTM, TRTEDTM, ASTDTM, AENDTM, AEITOXGR, AETOXGR, TRTEMFL)
#> # A tibble: 19 × 8
#>    USUBJID TRTSDTM    TRTEDTM    ASTDTM     AENDTM     AEITOXGR AETOXGR TRTEMFL
#>    <chr>   <date>     <date>     <date>     <date>     <chr>    <chr>   <chr>
#>  1 1       2021-01-01 2021-12-31 2020-12-20 2020-12-21 2        2       <NA>
#>  2 2       2021-01-01 2021-12-31 2021-12-20 2021-12-21 2        2       Y
#>  3 3       2021-01-01 2021-12-31 2020-12-20 2020-12-21 2        2       <NA>
#>  4 3       2021-01-01 2021-12-31 2021-12-20 2021-12-21 2        2       Y
#>  5 4       2021-01-01 2021-12-31 2020-12-20 2020-12-21 2        2       <NA>
#>  6 4       2021-01-01 2021-12-31 2021-12-20 2021-12-21 2        3       Y
#>  7 5       2021-01-01 2021-12-31 2020-12-20 2020-12-21 2        2       <NA>
#>  8 5       2021-01-01 2021-12-31 2021-12-20 2021-12-21 2        1       Y
#>  9 6       2021-01-01 2021-12-31 2020-12-23 2021-01-21 2        2       <NA>
#> 10 6       2021-01-01 2021-12-31 2021-12-20 2021-12-21 2        2       Y
#> 11 7       2021-01-01 2021-12-31 2020-12-23 2021-01-21 2        2       <NA>
#> 12 7       2021-01-01 2021-12-31 2021-12-20 2021-12-21 2        3       Y
#> 13 8       2021-01-01 2021-12-31 2020-12-23 2021-01-21 2        2       <NA>
#> 14 8       2021-01-01 2021-12-31 2021-12-20 2021-12-21 2        1       Y
#> 15 9       2021-01-01 2021-12-31 2020-12-23 2021-01-21 2        2       <NA>
#> 16 10      2021-01-01 2021-12-31 2020-12-23 2021-01-21 2        4       Y
#> 17 11      2021-01-01 2021-12-31 2020-12-23 2021-01-21 2        1       <NA>
#> 18 12      2021-01-01 2021-12-31 2020-12-23 2021-01-21 3        2       <NA>
#> 19 13      2021-01-01 2021-12-31 2020-12-23 2021-01-21 1        2       Y