LBT10_BL

Liver Laboratory Tests – Patients with Elevated Post-Baseline AST or ALT Levels at Two Consecutive Visits (with Respect to Baseline)

Output

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Code

tbl <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARMCD") %>%
  split_rows_by("PARAMCAT") %>%
  split_rows_by("PARAM", split_fun = drop_split_levels, child_labels = "hidden") %>%
  count_occurrences(
    vars = "AVALC_FORMAT",
    .stats = c("fraction"),
    denom = "n",
    drop = TRUE
  ) %>%
  build_table(anl, alt_counts_df = adsl)

criteria_fun <- function(tr) {
  row_label <- obj_label(tr)
  ifelse(row_label == "Criteria not met", TRUE, FALSE)
}

result <- tbl %>% trim_rows(criteria = criteria_fun)
result

                               ARM A            ARM B            ARM C     
                              (N=134)          (N=134)          (N=132)    
———————————————————————————————————————————————————————————————————————————
Total Bilirubin <= 2xULN                                                   
  ALT >3xULN at 2 Visits   25/134 (18.7%)   20/134 (14.9%)   27/132 (20.5%)
  AST >3xULN at 2 Visits   22/134 (16.4%)   14/134 (10.4%)   37/132 (28.0%)
Total Bilirubin > 2xULN                                                    
  ALT >3xULN at 2 Visits   26/134 (19.4%)   31/134 (23.1%)   23/132 (17.4%)
  AST >3xULN at 2 Visits   30/134 (22.4%)   27/134 (20.1%)   26/132 (19.7%)

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R Code

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

split_cols_by("ACTARMCD") %>%

split_rows_by("PARAMCAT") %>%

split_rows_by("PARAM", split_fun = drop_split_levels, child_labels = "hidden") %>%

count_occurrences(

vars = "AVALC_FORMAT",

.stats = c("fraction"),

denom = "n",

drop = TRUE

) %>%

build_table(anl, alt_counts_df = adsl)

criteria_fun <- function(tr) {

row_label <- obj_label(tr)

ifelse(row_label == "Criteria not met", TRUE, FALSE)

}

result <- tbl %>% trim_rows(criteria = criteria_fun)

result

_webr_editor_2 = Object {code: "tbl <- basic_table(show_colcounts = TRUE) %>%\n sp…tbl %>% trim_rows(criteria = criteria_fun)\nresult", options: Object, indicator: Ke}

Preview
Try this using WebR

Code

tbl2 <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARMCD") %>%
  split_rows_by("PARAMCAT", split_fun = remove_split_levels("Total Bilirubin > 2xULN")) %>%
  split_rows_by("PARAM", split_fun = drop_split_levels, child_labels = "hidden") %>%
  count_occurrences(
    vars = "AVALC_FORMAT",
    .stats = c("fraction"),
    denom = "n",
    drop = TRUE
  ) %>%
  build_table(anl, alt_counts_df = adsl)

criteria_fun <- function(tr) {
  row_label <- obj_label(tr)
  ifelse(row_label == "Criteria not met", TRUE, FALSE)
}

result <- tbl2 %>% trim_rows(criteria = criteria_fun)
result

                               ARM A            ARM B            ARM C     
                              (N=134)          (N=134)          (N=132)    
———————————————————————————————————————————————————————————————————————————
Total Bilirubin <= 2xULN                                                   
  ALT >3xULN at 2 Visits   25/134 (18.7%)   20/134 (14.9%)   27/132 (20.5%)
  AST >3xULN at 2 Visits   22/134 (16.4%)   14/134 (10.4%)   37/132 (28.0%)

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

tbl2 <- basic_table(show_colcounts = TRUE) %>%

split_cols_by("ACTARMCD") %>%

split_rows_by("PARAMCAT", split_fun = remove_split_levels("Total Bilirubin > 2xULN")) %>%

split_rows_by("PARAM", split_fun = drop_split_levels, child_labels = "hidden") %>%

count_occurrences(

vars = "AVALC_FORMAT",

.stats = c("fraction"),

denom = "n",

drop = TRUE

) %>%

build_table(anl, alt_counts_df = adsl)

criteria_fun <- function(tr) {

row_label <- obj_label(tr)

ifelse(row_label == "Criteria not met", TRUE, FALSE)

}

result <- tbl2 %>% trim_rows(criteria = criteria_fun)

result

_webr_editor_3 = Object {code: "tbl2 <- basic_table(show_colcounts = TRUE) %>%\n s…bl2 %>% trim_rows(criteria = criteria_fun)\nresult", options: Object, indicator: Ke}

Code

library(dplyr)
library(tern)

adsl <- random.cdisc.data::cadsl
adhy <- random.cdisc.data::cadhy

adhy_liver <- adhy %>%
  filter(PARAMCD %in% c(
    "BL2AL2CB", "BL2AS2CB", "BG2AL2CB", "BG2AS2CB", "B2A2L2CB", "B2A2S2CB", "B2A5L2CB", "B2A5S2CB"
  )) %>%
  mutate(PARAMCAT = case_when(
    PARAMCD %in% c("BL2AL2CB", "BL2AS2CB") ~ "Total Bilirubin <= 2xULN",
    PARAMCD %in% c("BG2AL2CB", "BG2AS2CB") ~ "Total Bilirubin > 2xULN",
    PARAMCD %in% c("B2A2L2CB", "B2A2S2CB") ~ "Total Bilirubin > 2xULN and Alkaline Phosphatase <= 2xULN",
    PARAMCD %in% c("B2A5L2CB", "B2A5S2CB") ~ "Total Bilirubin > 2xULN and Alkaline Phosphatase <= 5xULN"
  )) %>%
  mutate(AVALC_FORMAT = case_when(
    PARAMCD %in% c("BL2AL2CB", "BG2AL2CB", "B2A2L2CB", "B2A5L2CB") & AVALC == "Y" ~ "ALT >3xULN at 2 Visits",
    PARAMCD %in% c("BL2AS2CB", "BG2AS2CB", "B2A2S2CB", "B2A5S2CB") & AVALC == "Y" ~ "AST >3xULN at 2 Visits",
    TRUE ~ "Criteria not met"
  ))

# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.
adsl <- df_explicit_na(adsl)
anl <- df_explicit_na(adhy_liver)

Reproducibility

Timestamp

[1] "2025-03-26 17:43:49 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     2025-03-26
 pandoc   3.6.3 @ /usr/bin/ (via rmarkdown)
 quarto   1.6.42 @ /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               1.0.7   2024-09-26 [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        * 0.5.10  2025-01-09 [1] RSPM
 generics            0.1.3   2022-07-05 [1] RSPM
 ggplot2             3.5.1   2024-04-23 [1] RSPM
 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            1.9.1   2025-03-03 [1] RSPM
 knitr               1.50    2025-03-16 [1] RSPM
 lattice             0.22-6  2024-03-20 [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   2025-01-21 [1] RSPM
 pillar              1.10.1  2025-01-07 [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  2024-10-10 [1] RSPM
 rbibutils           2.3     2024-10-04 [1] RSPM
 Rdpack              2.6.3   2025-03-16 [1] RSPM
 rlang               1.1.5   2025-01-17 [1] RSPM
 rmarkdown           2.29    2024-11-04 [1] RSPM
 rtables           * 0.6.11  2025-01-10 [1] RSPM
 scales              1.3.0   2023-11-28 [1] RSPM
 sessioninfo         1.2.3   2025-02-05 [1] any (@1.2.3)
 stringi             1.8.4   2024-05-06 [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   2025-01-17 [1] RSPM
 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                0.51    2025-02-19 [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.

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

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Reproducibility

Timestamp

Session Info

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`.lock` file