Adverse event table
t_ae_pt_soc_slide(
adsl,
adae,
arm,
cutoff = NA,
prune_by_total = FALSE,
split_by_study = FALSE,
side_by_side = NULL
)ADSL data set, dataframe
ADAE data set, dataframe
Arm variable, character
Cutoff threshold
Prune according total column
Split by study, building structured header for tables
"GlobalAsia" or "GlobalAsiaChina" to define the side by side requirement
rtables object
library(dplyr)
# Example 1
adsl <- eg_adsl %>%
dplyr::mutate(TRT01A = factor(TRT01A, levels = c("A: Drug X", "B: Placebo")))
adae <- eg_adae %>%
dplyr::mutate(
TRT01A = factor(TRT01A, levels = c("A: Drug X", "B: Placebo")),
ATOXGR = AETOXGR
)
out <- t_ae_pt_soc_slide(adsl, adae, "TRT01A", 2)
print(out)
#> Adverse Events table
#>
#> ———————————————————————————————————————————————————————————————————————
#> MedDRA System Organ Class
#> MedDRA Preferred Term N (%) A: Drug X B: Placebo All Patients
#> ———————————————————————————————————————————————————————————————————————
#> cl A.1
#> dcd A.1.1.1.1 45 (33.6%) 31 (23.1%) 128 (32.0%)
#> dcd A.1.1.1.2 41 (30.6%) 39 (29.1%) 122 (30.5%)
#> cl B.1
#> dcd B.1.1.1.1 38 (28.4%) 37 (27.6%) 111 (27.8%)
#> cl B.2
#> dcd B.2.2.3.1 38 (28.4%) 40 (29.9%) 123 (30.8%)
#> dcd B.2.1.2.1 39 (29.1%) 34 (25.4%) 119 (29.8%)
#> cl C.1
#> dcd C.1.1.1.3 36 (26.9%) 34 (25.4%) 106 (26.5%)
#> cl C.2
#> dcd C.2.1.2.1 28 (20.9%) 36 (26.9%) 112 (28.0%)
#> cl D.1
#> dcd D.1.1.1.1 42 (31.3%) 32 (23.9%) 120 (30.0%)
#> dcd D.1.1.4.2 38 (28.4%) 34 (25.4%) 112 (28.0%)
#> cl D.2
#> dcd D.2.1.5.3 37 (27.6%) 46 (34.3%) 133 (33.2%)
generate_slides(out, paste0(tempdir(), "/ae.pptx"))
#> [1] "Adverse Events table"
#> [1] "Adverse Events table (cont.)"
# Example 2, prune by total column
out2 <- t_ae_pt_soc_slide(adsl, adae, "TRT01A", 25, prune_by_total = TRUE)
print(out2)
#> Adverse Events table
#>
#> ———————————————————————————————————————————————————————————————————————
#> MedDRA System Organ Class
#> MedDRA Preferred Term N (%) A: Drug X B: Placebo All Patients
#> ———————————————————————————————————————————————————————————————————————
#> cl A.1
#> dcd A.1.1.1.1 45 (33.6%) 31 (23.1%) 128 (32.0%)
#> dcd A.1.1.1.2 41 (30.6%) 39 (29.1%) 122 (30.5%)
#> cl B.1
#> dcd B.1.1.1.1 38 (28.4%) 37 (27.6%) 111 (27.8%)
#> cl B.2
#> dcd B.2.2.3.1 38 (28.4%) 40 (29.9%) 123 (30.8%)
#> dcd B.2.1.2.1 39 (29.1%) 34 (25.4%) 119 (29.8%)
#> cl C.1
#> dcd C.1.1.1.3 36 (26.9%) 34 (25.4%) 106 (26.5%)
#> cl C.2
#> dcd C.2.1.2.1 28 (20.9%) 36 (26.9%) 112 (28.0%)
#> cl D.1
#> dcd D.1.1.1.1 42 (31.3%) 32 (23.9%) 120 (30.0%)
#> dcd D.1.1.4.2 38 (28.4%) 34 (25.4%) 112 (28.0%)
#> cl D.2
#> dcd D.2.1.5.3 37 (27.6%) 46 (34.3%) 133 (33.2%)
generate_slides(out2, paste0(tempdir(), "/ae2.pptx"))
#> [1] "Adverse Events table"
#> [1] "Adverse Events table (cont.)"