DT1C

Alternative BEP Indicator in Demographics Table

The tables below compare the overall population (“All”) with the biomarker evaluable population (“BEP”) with regards to selected demographic variables.

We will use the cadsl data set from the random.cdisc.data package to illustrate the tables. We add a second artificial BEP flag variable BEP02FL.

In order to compare All with BEP, we need to define a list bep_groups defining these two groups. The reason is that these two groups are overlapping (BEP is a subset of All). Here, we refer in the list elements to the levels Y and N of the biomarker population flag variable BEP01FL from adsl which we will use below:

Code

library(tern)
library(dplyr)

set.seed(123)
adsl <- random.cdisc.data::cadsl %>%
  df_explicit_na() %>%
  mutate(BEP02FL = factor(sample(c("Y", "N"), size = n(), replace = TRUE)))

bep_groups <- list(
  "All" = c("Y", "N"),
  "BEP" = "Y"
)

This can then be used by the tern layout function split_cols_by_groups() below.

We can of course use a different BEP factor variable BEP02FL with corresponding groups definition bep2_groups in the demographics table DT1.

Code

bep2_groups <- list(
  "All" = c("Y", "N"),
  "BEP2" = "Y"
)

lyt <- basic_table() %>%
  split_cols_by("ARM") %>%
  split_cols_by_groups("BEP02FL", bep2_groups) %>%
  analyze_vars(c("AGE", "SEX")) %>%
  add_colcounts()

build_table(lyt, adsl)

                      A: Drug X                  B: Placebo                C: Combination      
                  All          BEP2           All          BEP2           All          BEP2    
                (N=134)       (N=68)        (N=134)       (N=75)        (N=132)       (N=68)   
———————————————————————————————————————————————————————————————————————————————————————————————
AGE                                                                                            
  n               134           68            134           75            132           68     
  Mean (SD)   33.8 (6.6)    32.3 (6.2)    35.4 (7.9)    35.5 (7.4)    35.4 (7.7)    35.3 (6.7) 
  Median         33.0          31.0          35.0          36.0          35.0          35.0    
  Min - Max   21.0 - 50.0   21.0 - 47.0   21.0 - 62.0   23.0 - 58.0   20.0 - 69.0   21.0 - 49.0
SEX                                                                                            
  n               134           68            134           75            132           68     
  F            79 (59%)     42 (61.8%)    82 (61.2%)     48 (64%)      70 (53%)      34 (50%)  
  M            55 (41%)     26 (38.2%)    52 (38.8%)     27 (36%)      62 (47%)      34 (50%)

Code

sessionInfo()

R version 4.4.2 (2024-10-31)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 24.04.1 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

time zone: Etc/UTC
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] dplyr_1.1.4       tern_0.9.7        rtables_0.6.11    magrittr_2.0.3   
[5] formatters_0.5.10

loaded via a namespace (and not attached):
 [1] Matrix_1.7-2             gtable_0.3.6             jsonlite_1.9.0          
 [4] compiler_4.4.2           tidyselect_1.2.1         stringr_1.5.1           
 [7] tidyr_1.3.1              splines_4.4.2            scales_1.3.0            
[10] yaml_2.3.10              fastmap_1.2.0            lattice_0.22-6          
[13] ggplot2_3.5.1            R6_2.6.1                 generics_0.1.3          
[16] knitr_1.49               forcats_1.0.0            rbibutils_2.3           
[19] htmlwidgets_1.6.4        backports_1.5.0          checkmate_2.3.2         
[22] tibble_3.2.1             munsell_0.5.1            pillar_1.10.1           
[25] rlang_1.1.5              broom_1.0.7              stringi_1.8.4           
[28] xfun_0.51                cli_3.6.4                Rdpack_2.6.2            
[31] digest_0.6.37            grid_4.4.2               lifecycle_1.0.4         
[34] vctrs_0.6.5              evaluate_1.0.3           glue_1.8.0              
[37] nestcolor_0.1.3          codetools_0.2-20         survival_3.8-3          
[40] random.cdisc.data_0.3.16 colorspace_2.1-1         rmarkdown_2.29          
[43] purrr_1.0.4              tools_4.4.2              pkgconfig_2.0.3         
[46] htmltools_0.5.8.1

Reuse