CPMT2

Cox Proportional Hazards Model Tables with Multiple Covariates

CPM

We prepare the data similarly as in CPMT1.

Code

library(tern)
library(dplyr)

adtte <- random.cdisc.data::cadtte %>%
  df_explicit_na() %>%
  filter(PARAMCD == "OS", BEP01FL == "Y") %>%
  mutate(
    AVAL = day2month(AVAL),
    AVALU = "Months",
    is_event = CNSR == 0
  ) %>%
  var_relabel(
    BMRKR1 = "Biomarker (Continuous)",
    BMRKR2 = "Biomarker (Categorical)"
  )

The multivariate Cox Proportional Hazards model can be displayed in a summary table using the summarize_coxreg function from tern with the multivar argument set to TRUE. Like the corresponding model fitting function fit_coxreg_multivar(), we specify the time, event, arm and covariates in a variables list, and any further customizations via the control argument. Note that the default confidence level is 95% but this can be customized via the conf_level element in control.

Rather than fitting the model and then tidying the output via the broom::tidy() function, we can directly input these three arguments into the summarize_coxreg() function to summarize the model fit in a table layout, building the table with our pre-processed adtte data set.

Code

result <- basic_table() %>%
  summarize_coxreg(
    variables = list(
      time = "AVAL",
      event = "is_event",
      arm = "ARM",
      covariates = c("AGE", "BMRKR1", "BMRKR2")
    ),
    multivar = TRUE
  ) %>%
  append_topleft("Effect/Covariate Included in the Model") %>%
  build_table(adtte)

result

Effect/Covariate Included in the Model                 Hazard Ratio      95% CI      p-value
————————————————————————————————————————————————————————————————————————————————————————————
Treatment:                                                                                  
  Description of Planned Arm (reference = A: Drug X)                                 0.0164 
    B: Placebo                                             1.15       (0.66, 1.99)   0.6217 
    C: Combination                                         1.95       (1.19, 3.21)   0.0080 
Covariate:                                                                                  
  Age                                                                                       
    All                                                    1.01       (0.98, 1.04)   0.4993 
  Biomarker (Continuous)                                                                    
    All                                                    1.01       (0.96, 1.07)   0.6755 
  Biomarker (Categorical) (reference = LOW)                                          0.7350 
    MEDIUM                                                 1.01       (0.62, 1.67)   0.9558 
    HIGH                                                   0.84       (0.50, 1.40)   0.5054

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] generics_0.1.3                knitr_1.48                   
[17] forcats_1.0.0                 rbibutils_2.2.16             
[19] htmlwidgets_1.6.4             backports_1.5.0              
[21] checkmate_2.3.2               tibble_3.2.1                 
[23] car_3.1-2                     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                     Rdpack_2.6.1                 
[33] digest_0.6.37                 grid_4.4.1                   
[35] lifecycle_1.0.4               vctrs_0.6.5                  
[37] evaluate_0.24.0               glue_1.7.0                   
[39] codetools_0.2-20              abind_1.4-8                  
[41] survival_3.7-0                carData_3.0-5                
[43] random.cdisc.data_0.3.15.9009 fansi_1.0.6                  
[45] colorspace_2.1-1              purrr_1.0.2                  
[47] rmarkdown_2.28                tools_4.4.1                  
[49] pkgconfig_2.0.3               htmltools_0.5.8.1

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