SFG3

Survival Forest Graphs for One Treatment Arm

SFG

We prepare the data similarly as in SFG1, focusing on a single arm in the biomarker evaluable population.

Code

library(tern)
library(dplyr)

adtte <- random.cdisc.data::cadtte %>%
  df_explicit_na() %>%
  filter(
    PARAMCD == "OS",
    ARM == "A: Drug X",
    BEP01FL == "Y"
  ) %>%
  mutate(
    AVAL = day2month(AVAL),
    AVALU = "Months",
    is_event = CNSR == 0
  ) %>%
  var_relabel(
    BEP01FL = "BEP",
    BMRKR1 = "Biomarker (Countinuous)"
  )

We define a vector of all cutpoints to use for a numeric biomarker (here BMRKR1). We lapply() over this vector, each time generating a binary factor variable BMRKR1_cut and then tabulating the resulting statistics as e.g. in SFG1. Then we rbind() all tables in the list together.

Code

all_cutpoints <- c(2.5, 5, 7.5, 10)

tables_all_cutpoints <- lapply(all_cutpoints, function(cutpoint) {
  adtte_cut <- adtte %>%
    mutate(
      BMRKR1_cut = explicit_na(factor(
        ifelse(BMRKR1 > cutpoint, "Greater", "Less")
      ))
    )
  tbl <- extract_survival_subgroups(
    variables = list(
      tte = "AVAL",
      is_event = "is_event",
      arm = "BMRKR1_cut"
    ),
    label_all = paste0("BMRKR1 (", cutpoint, ")"),
    data = adtte_cut
  )
  basic_table() %>%
    tabulate_survival_subgroups(
      df = tbl,
      vars = c("n_tot_events", "n", "n_events", "median", "hr", "ci"),
      time_unit = adtte_cut$AVALU[1]
    )
})
result <- do.call(rbind, tables_all_cutpoints)

We can now produce the forest plot using the g_forest() function. Notice that the result object in these derivation steps has lost its attributes. In order to specify the column indices for the estimator, confidence interval, and header, we need to derive the attributes from one of the original tables and specify them using the col_x, col_y and forest_header arguments of g_forest().

Code

one_table <- tables_all_cutpoints[[1]]
g_forest(result,
  col_x = attr(one_table, "col_x"),
  col_ci = attr(one_table, "col_ci"),
  forest_header = attr(one_table, "forest_header")
)

Code

sessionInfo()

R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.4 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-r0.3.20.so;  LAPACK version 3.10.0

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_0.9.5.9022       rtables_0.6.9.9014   
[4] magrittr_2.0.3        formatters_0.5.9.9001

loaded via a namespace (and not attached):
 [1] Matrix_1.7-0                  gtable_0.3.5                 
 [3] jsonlite_1.8.8                compiler_4.4.1               
 [5] tidyselect_1.2.1              stringr_1.5.1                
 [7] tidyr_1.3.1                   splines_4.4.1                
 [9] scales_1.3.0                  yaml_2.3.10                  
[11] fastmap_1.2.0                 lattice_0.22-6               
[13] ggplot2_3.5.1                 R6_2.5.1                     
[15] labeling_0.4.3                generics_0.1.3               
[17] knitr_1.48                    forcats_1.0.0                
[19] rbibutils_2.2.16              htmlwidgets_1.6.4            
[21] backports_1.5.0               checkmate_2.3.2              
[23] tibble_3.2.1                  munsell_0.5.1                
[25] pillar_1.9.0                  rlang_1.1.4                  
[27] utf8_1.2.4                    broom_1.0.6                  
[29] stringi_1.8.4                 xfun_0.47                    
[31] cli_3.6.3                     withr_3.0.1                  
[33] Rdpack_2.6.1                  digest_0.6.37                
[35] grid_4.4.1                    cowplot_1.1.3                
[37] lifecycle_1.0.4               vctrs_0.6.5                  
[39] evaluate_0.24.0               glue_1.7.0                   
[41] farver_2.1.2                  codetools_0.2-20             
[43] survival_3.7-0                random.cdisc.data_0.3.15.9009
[45] fansi_1.0.6                   colorspace_2.1-1             
[47] purrr_1.0.2                   rmarkdown_2.28               
[49] tools_4.4.1                   pkgconfig_2.0.3              
[51] htmltools_0.5.8.1

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