TTET01 template may be used to summarize any binary outcome or response variable at
a single time point. Typical application for oncology
Usage
ttet01_main(
adam_db,
dataset = "adtte",
arm_var = "ARM",
ref_group = NULL,
summarize_event = TRUE,
perform_analysis = "unstrat",
strata = NULL,
...
)
ttet01_pre(adam_db, dataset = "adtte", ...)
ttet01_post(tlg, prune_0 = TRUE, ...)
ttet01Arguments
- adam_db
(
listofdata.frames) object containing theADaMdatasets- dataset
(
string) the name of a table in theadam_dbobject.- arm_var
(
string) variable used for column splitting- ref_group
(
string) The name of the reference group, the value should be identical to the values inarm_var, if not specified, it will by default use the first level or value ofarm_var.- summarize_event
(
flag) should the event description be displayed, default is TRUE- perform_analysis
(
string) option to display statistical comparisons using stratified analyses, or unstratified analyses, or both, e.g.c("unstrat", "strat"). Only unstratified will be displayed by default- strata
(
string) stratification factors, e.g.strata = c("STRATA1", "STRATA2"), by default as NULL- ...
Further arguments passed to
control_surv_time(),control_coxph(),control_survtp(), andsurv_timepoint(). For details, see the documentation intern. Commonly used arguments includepval_method,conf_level,conf_type,quantiles,ties,time_point,method, etc.- tlg
(
TableTree,Listingorggplot) object typically produced by amainfunction.- prune_0
(
flag) remove 0 count rows
Value
the main function returns an rtables object.
the preprocessing function returns a list of data.frame.
the postprocessing function returns an rtables object or an ElementaryTable (null report).
Functions
ttet01_main(): Main TLG functionttet01_pre(): Preprocessingttet01_post(): Postprocessing
Examples
library(dplyr)
library(dunlin)
proc_data <- log_filter(syn_data, PARAMCD == "PFS", "adtte")
run(ttet01, proc_data)
#> A: Drug X B: Placebo C: Combination
#> (N=15) (N=15) (N=15)
#> —————————————————————————————————————————————————————————————————————————————————————
#> Patients with event (%) 10 (66.7%) 11 (73.3%) 11 (73.3%)
#> Earliest contributing event
#> Death 5 6 4
#> Disease Progression 5 5 7
#> Patients without event (%) 5 (33.3%) 4 (26.7%) 4 (26.7%)
#> Time to Event (MONTHS)
#> Median 17.2 18.1 12.6
#> 95% CI (11.9, 24.4) (6.5, 34.1) (7.1, 15.6)
#> 25% and 75%-ile 11.9, 24.4 6.5, 34.1 7.1, 15.5
#> Range 1.2 to 46.9 {1} 1.0 to 50.5 {2} 1.9 to 28.9
#> Unstratified Analysis
#> p-value (log-rank) 0.8668 0.1419
#> Hazard Ratio 0.93 1.95
#> 95% CI (0.39, 2.22) (0.79, 4.80)
#> 6 MONTHS
#> Patients remaining at risk 10 11 10
#> Event Free Rate (%) 78.32 78.57 80.00
#> 95% CI (56.47, 100.00) (57.08, 100.00) (59.76, 100.00)
#> Difference in Event Free Rate 0.25 1.68
#> 95% CI (-30.40, 30.90) (-28.11, 31.47)
#> p-value (Z-test) 0.9873 0.9121
#> 12 MONTHS
#> Patients remaining at risk 8 6 7
#> Event Free Rate (%) 69.62 55.10 62.22
#> 95% CI (44.40, 94.84) (27.89, 82.31) (35.39, 89.06)
#> Difference in Event Free Rate -14.52 -7.40
#> 95% CI (-51.62, 22.58) (-44.22, 29.43)
#> p-value (Z-test) 0.4431 0.6938
#> —————————————————————————————————————————————————————————————————————————————————————
#>
#> {1} - Censored observation: range maximum
#> {2} - Censored observations: range minimum & maximum
#> —————————————————————————————————————————————————————————————————————————————————————
#>
run(ttet01, proc_data,
summarize_event = FALSE, perform_analysis = c("unstrat", "strat"),
strata = c("STRATA1", "STRATA2"),
conf_type = "log-log",
time_point = c(6, 12),
method = "both"
)
#> A: Drug X B: Placebo C: Combination
#> (N=15) (N=15) (N=15)
#> —————————————————————————————————————————————————————————————————————————————————————
#> Patients with event (%) 10 (66.7%) 11 (73.3%) 11 (73.3%)
#> Patients without event (%) 5 (33.3%) 4 (26.7%) 4 (26.7%)
#> Time to Event (MONTHS)
#> Median 17.2 18.1 12.6
#> 95% CI (4.3, 24.4) (4.7, 34.1) (2.0, 15.6)
#> 25% and 75%-ile 11.9, 24.4 6.5, 34.1 7.1, 15.5
#> Range 1.2 to 46.9 {1} 1.0 to 50.5 {2} 1.9 to 28.9
#> Unstratified Analysis
#> p-value (log-rank) 0.8668 0.1419
#> Hazard Ratio 0.93 1.95
#> 95% CI (0.39, 2.22) (0.79, 4.80)
#> Stratified Analysis
#> p-value (log-rank) 0.7771 0.1499
#> Hazard Ratio 0.87 2.42
#> 95% CI (0.33, 2.29) (0.71, 8.30)
#> 6 MONTHS
#> Patients remaining at risk 10 11 10
#> Event Free Rate (%) 78.32 78.57 80.00
#> 95% CI (46.51, 92.50) (47.25, 92.54) (49.98, 93.07)
#> Difference in Event Free Rate 0.25 1.68
#> 95% CI (-30.40, 30.90) (-28.11, 31.47)
#> p-value (Z-test) 0.9873 0.9121
#> 12 MONTHS
#> Patients remaining at risk 8 6 7
#> Event Free Rate (%) 69.62 55.10 62.22
#> 95% CI (37.36, 87.53) (25.54, 77.09) (30.81, 82.60)
#> Difference in Event Free Rate -14.52 -7.40
#> 95% CI (-51.62, 22.58) (-44.22, 29.43)
#> p-value (Z-test) 0.4431 0.6938
#> —————————————————————————————————————————————————————————————————————————————————————
#>
#> {1} - Censored observation: range maximum
#> {2} - Censored observations: range minimum & maximum
#> —————————————————————————————————————————————————————————————————————————————————————
#>