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Add PFS events at Tumour Progression to Data

Source: R/SimJointData.R
add_pfs.Rd

Adds new columns pfs_time and pfs_event based on observed changes to SLD.

Usage 

add_pfs(
  object,
  relative_threshold = 1.2,
  absolute_threshold = 5,
  from_time = 0,
  observed_after = FALSE
)

Arguments

object

(SimJointData) where the PFS events should be added.

relative_threshold

(number) a multiplicative threshold for the change in SLD compared to the min(SLD). Default is 1.2 meaning a 20% increase.

absolute_threshold

(number) an absolute threshold for the change in SLD compared to the minimum. Default is 5.

from_time

(number) Ignore observations before this time for determining SLD minimum.

observed_after

(logical) If FALSE set longitudinal observations after the progression time to observed = FALSE

Value

The input SimJointData object with progression-free survival columns pfs_time and pfs_event added.

Details

Both thresholds must be met for a progression to be declared.

Examples 

data <- SimJointData(
  survival = SimSurvivalExponential(lambda = 1/10),
  longitudinal = SimLongitudinalSteinFojo()
  )
data <- add_pfs(data)
data@survival # now has pfs_time and pfs_event columns
#> # A tibble: 100 × 9
#>    subject     study   arm    time cov_cont cov_cat event pfs_time pfs_event
#>    <chr>       <fct>   <fct> <dbl>    <dbl> <fct>   <dbl>    <dbl>     <dbl>
#>  1 subject_001 Study-1 Arm-A     3  -0.470  A           1        3         1
#>  2 subject_002 Study-1 Arm-A    15  -0.806  B           1       15         1
#>  3 subject_003 Study-1 Arm-A     5  -0.941  B           1        5         1
#>  4 subject_004 Study-1 Arm-A    11   0.143  A           1       11         1
#>  5 subject_005 Study-1 Arm-A    13  -1.43   B           1       13         1
#>  6 subject_006 Study-1 Arm-A     1  -0.814  B           1        1         1
#>  7 subject_007 Study-1 Arm-A     7  -0.100  C           1        7         1
#>  8 subject_008 Study-1 Arm-A     5   0.0808 C           1        5         1
#>  9 subject_009 Study-1 Arm-A    27  -0.0793 B           1       27         1
#> 10 subject_010 Study-1 Arm-A    13  -0.690  A           1       13         1
#> # ℹ 90 more rows