LBT08

Laboratory Test Results with Highest NCI CTCAE Grade at Any Time

Output

Standard Table
Data Setup

Note: The direction of the shift table for each lab test is based on metadata and NCI CTCAE specifications. In addition, the worst laboratory flags must be selected appropriately to match the direction of abnormality. For example, if any lab requires a shift table for both directions, then both worst_flag_low and worst_flag_high must be specified in h_adlb_worsen. If all labs requires a shift table for only one direction, then the matching worst lab flag variable must be selected in h_adlb_worsen.

Preview
Try this using WebR

Code

result <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ARMCD") %>%
  split_rows_by("PARAMCD", label_pos = "topleft", split_label = obj_label(df$PARAMCD)) %>%
  split_rows_by("GRADDR", label_pos = "topleft", split_label = obj_label(df$GRADDR)) %>%
  count_abnormal_lab_worsen_by_baseline(
    var = "ATOXGR",
    variables = list(
      id = "USUBJID",
      baseline_var = "BTOXGR",
      direction_var = "GRADDR"
    )
  ) %>%
  append_topleft("    Highest NCI CTCAE Grade") %>%
  build_table(df = df, alt_counts_df = adsl)

result

Parameter Code                                                                
  Direction of Abnormality        ARM A            ARM B            ARM C     
    Highest NCI CTCAE Grade      (N=134)          (N=134)          (N=132)    
——————————————————————————————————————————————————————————————————————————————
ALT                                                                           
  Low                                                                         
    1                         11/113 (9.7%)     9/117 (7.7%)    15/123 (12.2%)
    2                         15/119 (12.6%)   23/123 (18.7%)   16/127 (12.6%)
    3                         15/127 (11.8%)   22/128 (17.2%)   14/128 (10.9%)
    4                         17/130 (13.1%)   10/131 (7.6%)    18/130 (13.8%)
    Any                       58/130 (44.6%)   64/131 (48.9%)   63/130 (48.5%)
CRP                                                                           
  High                                                                        
    1                         18/114 (15.8%)   18/112 (16.1%)   19/115 (16.5%)
    2                         20/122 (16.4%)   13/122 (10.7%)   14/122 (11.5%)
    3                         23/124 (18.5%)   14/128 (10.9%)   20/129 (15.5%)
    4                         12/131 (9.2%)    20/132 (15.2%)   11/132 (8.3%) 
    Any                       73/131 (55.7%)   65/132 (49.2%)   64/132 (48.5%)
  Low                                                                         
    1                         20/119 (16.8%)   18/113 (15.9%)   11/112 (9.8%) 
    2                         24/122 (19.7%)   21/118 (17.8%)    17/121 (14%) 
    3                         26/127 (20.5%)   20/127 (15.7%)   22/123 (17.9%)
    4                         10/131 (7.6%)    16/132 (12.1%)   21/130 (16.2%)
    Any                       80/131 (61.1%)   75/132 (56.8%)   71/130 (54.6%)
IGA                                                                           
  High                                                                        
    1                         18/119 (15.1%)   11/116 (9.5%)    15/113 (13.3%)
    2                         15/124 (12.1%)   23/120 (19.2%)   19/115 (16.5%)
    3                         21/128 (16.4%)   21/124 (16.9%)   20/120 (16.7%)
    4                         12/132 (9.1%)    12/129 (9.3%)     9/131 (6.9%) 
    Any                        66/132 (50%)    67/129 (51.9%)   63/131 (48.1%)

Experimental use!

WebR is a tool allowing you to run R code in the web browser. Modify the code below and click run to see the results. Alternatively, copy the code and click here to open WebR in a new tab.

R Code

Start Over

Run Code

result <- basic_table(show_colcounts = TRUE) %>%

split_cols_by("ARMCD") %>%

split_rows_by("PARAMCD", label_pos = "topleft", split_label = obj_label(df$PARAMCD)) %>%

split_rows_by("GRADDR", label_pos = "topleft", split_label = obj_label(df$GRADDR)) %>%

count_abnormal_lab_worsen_by_baseline(

var = "ATOXGR",

variables = list(

id = "USUBJID",

baseline_var = "BTOXGR",

direction_var = "GRADDR"

)

) %>%

append_topleft(" Highest NCI CTCAE Grade") %>%

build_table(df = df, alt_counts_df = adsl)

result

_webr_editor_2 = Object {code: "result <- basic_table(show_colcounts = TRUE) %>%\n …uild_table(df = df, alt_counts_df = adsl)\n\nresult", options: Object, indicator: Ke}

Code

library(dplyr)
library(tern)

adsl <- random.cdisc.data::cadsl
adlb <- random.cdisc.data::cadlb

adlb <- adlb %>%
  mutate(
    GRADDR = case_when(
      PARAMCD == "ALT" ~ "L",
      PARAMCD == "CRP" ~ "B",
      PARAMCD == "IGA" ~ "H"
    )
  ) %>%
  filter(SAFFL == "Y" & ONTRTFL == "Y" & GRADDR != "")

adsl <- df_explicit_na(adsl)
adlb <- df_explicit_na(adlb)

df <- h_adlb_worsen(
  adlb,
  worst_flag_low = c("WGRLOFL" = "Y"),
  worst_flag_high = c("WGRHIFL" = "Y"),
  direction_var = "GRADDR"
)

attributes(df$GRADDR) <- list("label" = "Direction of Abnormality")

Reproducibility

Timestamp

[1] "2025-04-09 17:53:48 UTC"

Session Info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.4.2 (2024-10-31)
 os       Ubuntu 24.04.1 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2025-04-09
 pandoc   3.6.3 @ /usr/bin/ (via rmarkdown)
 quarto   1.6.43 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 package           * version     date (UTC) lib source
 backports           1.5.0       2024-05-23 [1] RSPM
 brio                1.1.5       2024-04-24 [1] RSPM
 broom               1.0.8       2025-03-28 [1] RSPM
 checkmate           2.3.2       2024-07-29 [1] RSPM
 cli                 3.6.4       2025-02-13 [1] RSPM
 codetools           0.2-20      2024-03-31 [2] CRAN (R 4.4.2)
 colorspace          2.1-1       2024-07-26 [1] RSPM
 curl                6.2.2       2025-03-24 [1] RSPM
 digest              0.6.37      2024-08-19 [1] RSPM
 dplyr             * 1.1.4       2023-11-17 [1] RSPM
 evaluate            1.0.3       2025-01-10 [1] RSPM
 fastmap             1.2.0       2024-05-15 [1] RSPM
 forcats             1.0.0       2023-01-29 [1] RSPM
 formatters        * 0.5.11.9000 2025-04-09 [1] https://p~
 generics            0.1.3       2022-07-05 [1] RSPM
 ggplot2             3.5.2       2025-04-09 [1] CRAN (R 4.4.2)
 glue                1.8.0       2024-09-30 [1] RSPM
 gtable              0.3.6       2024-10-25 [1] RSPM
 htmltools           0.5.8.1     2024-04-04 [1] RSPM
 htmlwidgets         1.6.4       2023-12-06 [1] RSPM
 jsonlite            2.0.0       2025-03-27 [1] RSPM
 knitr               1.50        2025-03-16 [1] RSPM
 lattice             0.22-7      2025-04-02 [2] CRAN (R 4.4.2)
 lifecycle           1.0.4       2023-11-07 [1] RSPM
 magrittr          * 2.0.3       2022-03-30 [1] RSPM
 Matrix              1.7-3       2025-03-11 [1] CRAN (R 4.4.2)
 munsell             0.5.1       2024-04-01 [1] RSPM
 nestcolor           0.1.3.9000  2025-04-09 [1] https://p~
 pillar              1.10.2      2025-04-05 [1] RSPM
 pkgcache            2.2.3       2024-09-12 [1] RSPM
 pkgconfig           2.0.3       2019-09-22 [1] RSPM
 processx            3.8.6       2025-02-21 [1] RSPM
 ps                  1.9.0       2025-02-18 [1] RSPM
 purrr               1.0.4       2025-02-05 [1] RSPM
 R6                  2.6.1       2025-02-15 [1] RSPM
 random.cdisc.data   0.3.16.9002 2025-04-09 [1] https://p~
 rbibutils           2.3         2024-10-04 [1] RSPM
 Rdpack              2.6.4       2025-04-09 [1] RSPM
 rlang               1.1.5       2025-01-17 [1] RSPM
 rmarkdown           2.29        2024-11-04 [1] RSPM
 rtables           * 0.6.11.9019 2025-04-09 [1] https://p~
 scales              1.3.0       2023-11-28 [1] RSPM
 sessioninfo         1.2.3       2025-02-05 [1] any (@1.2.3)
 stringi             1.8.7       2025-03-27 [1] RSPM
 stringr             1.5.1       2023-11-14 [1] RSPM
 survival            3.8-3       2024-12-17 [2] CRAN (R 4.4.2)
 tern              * 0.9.7.9018  2025-04-09 [1] https://p~
 testthat            3.2.3       2025-01-13 [1] RSPM
 tibble              3.2.1       2023-03-20 [1] RSPM
 tidyr               1.3.1       2024-01-24 [1] RSPM
 tidyselect          1.2.1       2024-03-11 [1] RSPM
 vctrs               0.6.5       2023-12-01 [1] RSPM
 xfun                0.52        2025-04-02 [1] RSPM
 yaml                2.3.10      2024-07-26 [1] RSPM

 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library
 [3] /github/home/R/x86_64-pc-linux-gnu-library/4.4
 * ── Packages attached to the search path.

──────────────────────────────────────────────────────────────────────────────

`.lock` file

Download the .lock file and use renv::restore() on it to recreate environment used to generate this website.

Download

Downloading webR

Output

Reproducibility

Timestamp

Session Info

.lock file

`.lock` file