Demographic table
Arguments
- adsl
ADSL data set, dataframe
- arm
Arm variable, character, "`TRT01P" by default.
- vars
Characters of variables
- stats
see `.stats` from [tern::analyze_vars()]
- split_by_study
Split by study, building structured header for tables
- side_by_side
"GlobalAsia" or "GlobalAsiaChina" to define the side by side requirement
Note
* Default arm variables are set to `"TRT01A"` for safety output, and `"TRT01P"` for efficacy output
Examples
library(dplyr)
adsl <- eg_adsl
out1 <- t_dm_slide(adsl, "TRT01P", c("SEX", "AGE", "RACE", "ETHNIC", "COUNTRY"))
print(out1)
#> Demographic slide
#>
#> ———————————————————————————————————————————————————————————————————————————————————————————————————————
#> A: Drug X B: Placebo C: Combination All Patients
#> ———————————————————————————————————————————————————————————————————————————————————————————————————————
#> Sex
#> F 79 (59%) 82 (61.2%) 70 (53%) 231 (57.8%)
#> M 55 (41%) 52 (38.8%) 62 (47%) 169 (42.2%)
#> Age
#> Median 33.00 35.00 35.00 34.00
#> Min - Max 21.0 - 50.0 21.0 - 62.0 20.0 - 69.0 20.0 - 69.0
#> Race
#> ASIAN 68 (50.7%) 67 (50%) 73 (55.3%) 208 (52%)
#> BLACK OR AFRICAN AMERICAN 31 (23.1%) 28 (20.9%) 32 (24.2%) 91 (22.8%)
#> WHITE 27 (20.1%) 26 (19.4%) 21 (15.9%) 74 (18.5%)
#> AMERICAN INDIAN OR ALASKA NATIVE 8 (6%) 11 (8.2%) 6 (4.5%) 25 (6.2%)
#> MULTIPLE 0 1 (0.7%) 0 1 (0.2%)
#> NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER 0 1 (0.7%) 0 1 (0.2%)
#> OTHER 0 0 0 0
#> UNKNOWN 0 0 0 0
#> Ethnicity
#> NOT REPORTED 6 (4.5%) 10 (7.5%) 11 (8.3%) 27 (6.8%)
#> HISPANIC OR LATINO 15 (11.2%) 18 (13.4%) 15 (11.4%) 48 (12%)
#> NOT HISPANIC OR LATINO 104 (77.6%) 103 (76.9%) 101 (76.5%) 308 (77%)
#> UNKNOWN 9 (6.7%) 3 (2.2%) 5 (3.8%) 17 (4.2%)
#> Country
#> CHN 74 (55.2%) 81 (60.4%) 64 (48.5%) 219 (54.8%)
#> USA 10 (7.5%) 13 (9.7%) 17 (12.9%) 40 (10%)
#> BRA 13 (9.7%) 7 (5.2%) 10 (7.6%) 30 (7.5%)
#> PAK 12 (9%) 9 (6.7%) 10 (7.6%) 31 (7.8%)
#> NGA 8 (6%) 7 (5.2%) 11 (8.3%) 26 (6.5%)
#> RUS 5 (3.7%) 8 (6%) 6 (4.5%) 19 (4.8%)
#> JPN 5 (3.7%) 4 (3%) 9 (6.8%) 18 (4.5%)
#> GBR 4 (3%) 3 (2.2%) 2 (1.5%) 9 (2.2%)
#> CAN 3 (2.2%) 2 (1.5%) 3 (2.3%) 8 (2%)
#> CHE 0 0 0 0
generate_slides(out1, paste0(tempdir(), "/dm.pptx"))
#> [1] "Demographic slide"
#> [1] "Demographic slide (cont.)"
#> [1] "Demographic slide (cont.)"
#> [1] "Demographic slide (cont.)"
out2 <- t_dm_slide(adsl, "TRT01P", c("SEX", "AGE", "RACE", "ETHNIC", "COUNTRY"),
split_by_study = TRUE
)
print(out2)
#> Demographic slide
#>
#> —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
#> AB12345-1 AB12345-2
#> A: Drug X B: Placebo C: Combination A: Drug X B: Placebo C: Combination
#> —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
#> Sex
#> F 36 (58.1%) 48 (64.9%) 33 (51.6%) 43 (59.7%) 34 (56.7%) 37 (54.4%)
#> M 26 (41.9%) 26 (35.1%) 31 (48.4%) 29 (40.3%) 26 (43.3%) 31 (45.6%)
#> Age
#> Median 33.50 34.00 35.00 32.50 35.00 35.00
#> Min - Max 23.0 - 48.0 21.0 - 62.0 21.0 - 64.0 21.0 - 50.0 24.0 - 58.0 20.0 - 69.0
#> Race
#> ASIAN 34 (54.8%) 37 (50%) 31 (48.4%) 34 (47.2%) 30 (50%) 42 (61.8%)
#> BLACK OR AFRICAN AMERICAN 13 (21%) 14 (18.9%) 18 (28.1%) 18 (25%) 14 (23.3%) 14 (20.6%)
#> WHITE 11 (17.7%) 16 (21.6%) 11 (17.2%) 16 (22.2%) 10 (16.7%) 10 (14.7%)
#> AMERICAN INDIAN OR ALASKA NATIVE 4 (6.5%) 5 (6.8%) 4 (6.2%) 4 (5.6%) 6 (10%) 2 (2.9%)
#> MULTIPLE 0 1 (1.4%) 0 0 0 0
#> NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER 0 1 (1.4%) 0 0 0 0
#> OTHER 0 0 0 0 0 0
#> UNKNOWN 0 0 0 0 0 0
#> Ethnicity
#> NOT REPORTED 3 (4.8%) 5 (6.8%) 7 (10.9%) 3 (4.2%) 5 (8.3%) 4 (5.9%)
#> HISPANIC OR LATINO 8 (12.9%) 12 (16.2%) 7 (10.9%) 7 (9.7%) 6 (10%) 8 (11.8%)
#> NOT HISPANIC OR LATINO 45 (72.6%) 55 (74.3%) 50 (78.1%) 59 (81.9%) 48 (80%) 51 (75%)
#> UNKNOWN 6 (9.7%) 2 (2.7%) 0 3 (4.2%) 1 (1.7%) 5 (7.4%)
#> Country
#> CHN 29 (46.8%) 50 (67.6%) 29 (45.3%) 45 (62.5%) 31 (51.7%) 35 (51.5%)
#> USA 4 (6.5%) 4 (5.4%) 6 (9.4%) 6 (8.3%) 9 (15%) 11 (16.2%)
#> BRA 9 (14.5%) 3 (4.1%) 5 (7.8%) 4 (5.6%) 4 (6.7%) 5 (7.4%)
#> PAK 5 (8.1%) 5 (6.8%) 5 (7.8%) 7 (9.7%) 4 (6.7%) 5 (7.4%)
#> NGA 3 (4.8%) 4 (5.4%) 6 (9.4%) 5 (6.9%) 3 (5%) 5 (7.4%)
#> RUS 5 (8.1%) 4 (5.4%) 5 (7.8%) 0 4 (6.7%) 1 (1.5%)
#> JPN 3 (4.8%) 0 5 (7.8%) 2 (2.8%) 4 (6.7%) 4 (5.9%)
#> GBR 2 (3.2%) 2 (2.7%) 0 2 (2.8%) 1 (1.7%) 2 (2.9%)
#> CAN 2 (3.2%) 2 (2.7%) 3 (4.7%) 1 (1.4%) 0 0
#> CHE 0 0 0 0 0 0