KG5

Kaplan-Meier Graphs by Treatment Arm and Continuous Biomarker Cut

A setup similar to KG4 is used. The difference here is that we create the initial binary biomarker variable BMRKR1_BIN from comparing the continuous biomarker variable BMRKR1 with a cutoff of interest.

Code

library(tern)
library(dplyr)

adtte <- random.cdisc.data::cadtte %>%
  df_explicit_na() %>%
  filter(PARAMCD == "OS" & BEP01FL == "Y") %>%
  mutate(
    is_event = CNSR == 0,
    BMRKR1_BIN = ifelse(
      BMRKR1 > 5, "High", "Low"
    ),
    ARM_BIN = fct_collapse_only(
      ARM,
      CTRL = c("B: Placebo"),
      TRT = c("A: Drug X", "C: Combination")
    ),
    ARM_BMRKR1 = interaction(ARM_BIN, BMRKR1_BIN)
  )

variables <- list(tte = "AVAL", is_event = "is_event", arm = "ARM_BMRKR1")

We can produce the basic graph using the g_km() function from tern.

Code

g_km(
  df = adtte,
  variables = variables,
  annot_surv_med = FALSE,
  col = c("red", "blue", "red", "blue"),
  lty = c(1, 1, 2, 2)
)

We can also choose to annotate the plot with the median survival time for each of the treatment arms using the annot_surv_med = TRUE option.

Code

g_km(
  df = adtte,
  variables = variables,
  annot_surv_med = TRUE,
  col = c("red", "blue", "red", "blue"),
  lty = c(1, 1, 2, 2)
)

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                 labeling_0.4.3          
[16] generics_0.1.3           knitr_1.49               forcats_1.0.0           
[19] rbibutils_2.3            htmlwidgets_1.6.4        backports_1.5.0         
[22] checkmate_2.3.2          tibble_3.2.1             munsell_0.5.1           
[25] pillar_1.10.1            rlang_1.1.5              broom_1.0.7             
[28] stringi_1.8.4            xfun_0.51                cli_3.6.4               
[31] withr_3.0.2              Rdpack_2.6.2             digest_0.6.37           
[34] grid_4.4.2               cowplot_1.1.3            lifecycle_1.0.4         
[37] vctrs_0.6.5              evaluate_1.0.3           glue_1.8.0              
[40] farver_2.1.2             nestcolor_0.1.3          codetools_0.2-20        
[43] survival_3.8-3           random.cdisc.data_0.3.16 colorspace_2.1-1        
[46] rmarkdown_2.29           purrr_1.0.4              tools_4.4.2             
[49] pkgconfig_2.0.3          htmltools_0.5.8.1

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