LBT11_BL

Time to First Increase in Liver Laboratory Test Result Meeting Hy’s Law Laboratory Critieria (with Respect to Baseline)

Output

Code
lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by(var = "ARMCD", ref_group = "ARM A") %>%
  count_occurrences(vars = "event_grp") %>%
  surv_time(
    vars = "AVAL",
    var_labels = paste0("Time to 1st LLT Event (", levels(anl$AVALU), ")"),
    is_event = "is_event",
    table_names = "time_to_event"
  ) %>%
  coxph_pairwise(
    vars = "AVAL",
    is_event = "is_event",
    var_labels = "Unstratified Analysis",
    control = control_coxph(pval_method = "log-rank"),
    table_names = "coxph_unstratified"
  )

result <- build_table(lyt, df = anl, alt_counts_df = adsl_safl)
result
                                      ARM A              ARM B              ARM C      
                                     (N=134)            (N=134)            (N=132)     
———————————————————————————————————————————————————————————————————————————————————————
Patients with LLT event (%)         14 (10.4%)         18 (13.4%)         15 (11.4%)   
Patients without LLT event (%)     120 (89.6%)        116 (86.6%)        117 (88.6%)   
Time to 1st LLT Event (DAYS)                                                           
  Median                                NA                 NA               721.0      
    95% CI                              NA            (681.0, NA)        (691.0, NA)   
  25% and 75%-ile                   608.0, NA          558.0, NA          644.0, NA    
  Range                          1.0 to 728.0 {1}   1.0 to 726.0 {1}   1.0 to 724.0 {1}
Unstratified Analysis                                                                  
  p-value (log-rank)                                     0.5013             0.6413     
  Hazard Ratio                                            1.27               0.84      
  95% CI                                              (0.63, 2.56)       (0.40, 1.75)  
———————————————————————————————————————————————————————————————————————————————————————

{1} - Censored observations: range minimum & maximum
———————————————————————————————————————————————————————————————————————————————————————

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R Code
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lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by(var = "ARMCD", ref_group = "ARM A") %>%
count_occurrences(vars = "event_grp") %>%
surv_time(
vars = "AVAL",
var_labels = paste0("Time to 1st LLT Event (", levels(anl$AVALU), ")"),
is_event = "is_event",
table_names = "time_to_event"
) %>%
coxph_pairwise(
vars = "AVAL",
is_event = "is_event",
var_labels = "Unstratified Analysis",
control = control_coxph(pval_method = "log-rank"),
table_names = "coxph_unstratified"
)

result <- build_table(lyt, df = anl, alt_counts_df = adsl_safl)
result
_webr_editor_2 = Object {code: "lyt <- basic_table(show_colcounts = TRUE) %>%\n sp…(lyt, df = anl, alt_counts_df = adsl_safl)\nresult", options: Object, indicator: Ke}
Code
lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by(var = "ARMCD", ref_group = "ARM A") %>%
  count_occurrences(vars = "event_grp") %>%
  surv_time(
    vars = "AVAL",
    var_labels = paste0("Time to 1st LLT Event (", levels(anl$AVALU), ")"),
    is_event = "is_event",
    table_names = "time_to_event"
  )

result <- build_table(lyt, df = anl, alt_counts_df = adsl_safl)
result
                                      ARM A              ARM B              ARM C      
                                     (N=134)            (N=134)            (N=132)     
———————————————————————————————————————————————————————————————————————————————————————
Patients with LLT event (%)         14 (10.4%)         18 (13.4%)         15 (11.4%)   
Patients without LLT event (%)     120 (89.6%)        116 (86.6%)        117 (88.6%)   
Time to 1st LLT Event (DAYS)                                                           
  Median                                NA                 NA               721.0      
    95% CI                              NA            (681.0, NA)        (691.0, NA)   
  25% and 75%-ile                   608.0, NA          558.0, NA          644.0, NA    
  Range                          1.0 to 728.0 {1}   1.0 to 726.0 {1}   1.0 to 724.0 {1}
———————————————————————————————————————————————————————————————————————————————————————

{1} - Censored observations: range minimum & maximum
———————————————————————————————————————————————————————————————————————————————————————

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
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lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by(var = "ARMCD", ref_group = "ARM A") %>%
count_occurrences(vars = "event_grp") %>%
surv_time(
vars = "AVAL",
var_labels = paste0("Time to 1st LLT Event (", levels(anl$AVALU), ")"),
is_event = "is_event",
table_names = "time_to_event"
)

result <- build_table(lyt, df = anl, alt_counts_df = adsl_safl)
result
_webr_editor_3 = Object {code: "lyt <- basic_table(show_colcounts = TRUE) %>%\n sp…(lyt, df = anl, alt_counts_df = adsl_safl)\nresult", options: Object, indicator: Ke}
Code
strata <- c("RACE", "SEX")

lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by(var = "ARMCD", ref_group = "ARM A") %>%
  count_occurrences(vars = "event_grp") %>%
  surv_time(
    vars = "AVAL",
    var_labels = paste0("Time to 1st LLT Event (", levels(anl$AVALU), ")"),
    is_event = "is_event",
    table_names = "time_to_event"
  ) %>%
  coxph_pairwise(
    vars = "AVAL",
    is_event = "is_event",
    var_labels = "Unstratified Analysis",
    control = control_coxph(pval_method = "log-rank"),
    table_names = "coxph_unstratified"
  ) %>%
  coxph_pairwise(
    vars = "AVAL",
    is_event = "is_event",
    var_labels = paste0("Stratified By: ", paste(strata, collapse = ", ")),
    strata = strata,
    table_names = "coxph_stratified"
  )

result <- build_table(lyt, df = anl, alt_counts_df = adsl_safl)
result
                                      ARM A              ARM B              ARM C      
                                     (N=134)            (N=134)            (N=132)     
———————————————————————————————————————————————————————————————————————————————————————
Patients with LLT event (%)         14 (10.4%)         18 (13.4%)         15 (11.4%)   
Patients without LLT event (%)     120 (89.6%)        116 (86.6%)        117 (88.6%)   
Time to 1st LLT Event (DAYS)                                                           
  Median                                NA                 NA               721.0      
    95% CI                              NA            (681.0, NA)        (691.0, NA)   
  25% and 75%-ile                   608.0, NA          558.0, NA          644.0, NA    
  Range                          1.0 to 728.0 {1}   1.0 to 726.0 {1}   1.0 to 724.0 {1}
Unstratified Analysis                                                                  
  p-value (log-rank)                                     0.5013             0.6413     
  Hazard Ratio                                            1.27               0.84      
  95% CI                                              (0.63, 2.56)       (0.40, 1.75)  
Stratified By: RACE, SEX                                                               
  p-value (log-rank)                                     0.3886             0.7970     
  Hazard Ratio                                            1.39               0.91      
  95% CI                                              (0.65, 2.97)       (0.43, 1.93)  
———————————————————————————————————————————————————————————————————————————————————————

{1} - Censored observations: range minimum & maximum
———————————————————————————————————————————————————————————————————————————————————————

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
lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by(var = "ARMCD", ref_group = "ARM A") %>%
count_occurrences(vars = "event_grp") %>%
surv_time(
vars = "AVAL",
var_labels = paste0("Time to 1st LLT Event (", levels(anl$AVALU), ")"),
is_event = "is_event",
table_names = "time_to_event"
)

result <- build_table(lyt, df = anl, alt_counts_df = adsl_safl)
result
_webr_editor_4 = Object {code: "lyt <- basic_table(show_colcounts = TRUE) %>%\n sp…(lyt, df = anl, alt_counts_df = adsl_safl)\nresult", options: Object, indicator: Ke}
Code
library(tern)
library(dplyr)

adsl <- random.cdisc.data::cadsl
adaette <- random.cdisc.data::cadaette

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

adsl_safl <- dplyr::filter(adsl, .data$SAFFL == "Y")

anl <- adaette %>%
  dplyr::filter(
    SAFFL == "Y",
    PARAMCD == "HYSTTEBL"
  ) %>%
  dplyr::mutate(
    AVAL = .data$AVAL * dplyr::case_when( # convert to days, if possible
      .data$AVALU == "WEEKS" ~ 7,
      .data$AVALU == "MONTHS" ~ 30.4375,
      .data$AVALU == "YEARS" ~ 365,
      TRUE ~ 1
    ),
    AVALU = factor(dplyr::case_when(
      .data$AVALU %in% c("WEEKS", "MONTHS", "YEARS") ~ factor("DAYS"),
      TRUE ~ .data$AVALU
    ), levels = "DAYS"),
    is_event = CNSR == 0, # this will be a LLT event
    event_grp = factor(
      dplyr::case_when(
        CNSR == 0 ~ "Patients with LLT event (%)",
        CNSR == 1 ~ "Patients without LLT event (%)"
      ),
      levels = c(
        "Patients with LLT event (%)",
        "Patients without LLT event (%)"
      )
    )
  )

teal App

Code
library(teal.modules.clinical)

## Data reproducible code
data <- teal_data()
data <- within(data, {
  library(dplyr)

  ADSL <- random.cdisc.data::cadsl
  ADAETTE <- random.cdisc.data::cadaette

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

  ADSL <- filter(ADSL, .data$SAFFL == "Y")
  ADAETTE <- filter(ADAETTE, .data$SAFFL == "Y")
})
datanames <- c("ADSL", "ADAETTE")
datanames(data) <- datanames
Warning: `datanames<-()` was deprecated in teal.data 0.7.0.
ℹ invalid to use `datanames()<-` or `names()<-` on an object of class
  `teal_data`. See ?names.teal_data
Code
join_keys(data) <- default_cdisc_join_keys[datanames]

## Reusable Configuration For Modules
ADSL <- data[["ADSL"]]
ADAETTE <- data[["ADAETTE"]]
arm_ref_comp <- list(
  ACTARMCD = list(
    ref = "ARM B",
    comp = c("ARM A", "ARM C")
  ),
  ARM = list(
    ref = "B: Placebo",
    comp = c("A: Drug X", "C: Combination")
  )
)

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_tte(
      label = "Time To LLT Event Table",
      dataname = "ADAETTE",
      arm_var = choices_selected(
        variable_choices(ADSL, c("ARM", "ARMCD", "ACTARMCD")),
        "ARM"
      ),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        value_choices(ADAETTE, "PARAMCD", "PARAM"),
        "HYSTTEBL"
      ),
      strata_var = choices_selected(
        variable_choices(ADSL, c("RACE", "SEX")),
        c("RACE", "SEX")
      ),
      time_points = choices_selected(0, NULL),
      event_desc_var = choices_selected("EVNTDESC", "EVNTDESC", fixed = TRUE)
    )
  )
)

shinyApp(app$ui, app$server)

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Reproducibility

Timestamp

[1] "2025-03-26 17:45:56 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
 bslib                   0.9.0    2025-01-30 [1] RSPM
 cachem                  1.1.0    2024-05-16 [1] RSPM
 callr                   3.7.6    2024-03-25 [1] RSPM
 checkmate               2.3.2    2024-07-29 [1] RSPM
 chromote                0.5.0    2025-03-21 [1] RSPM
 cli                     3.6.4    2025-02-13 [1] RSPM
 coda                    0.19-4.1 2024-01-31 [1] CRAN (R 4.4.2)
 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
 emmeans                 1.11.0   2025-03-20 [1] RSPM
 estimability            1.5.1    2024-05-12 [1] RSPM
 evaluate                1.0.3    2025-01-10 [1] RSPM
 fastmap                 1.2.0    2024-05-15 [1] RSPM
 fontawesome             0.5.3    2024-11-16 [1] RSPM
 forcats                 1.0.0    2023-01-29 [1] RSPM
 formatR                 1.14     2023-01-17 [1] CRAN (R 4.4.2)
 formatters            * 0.5.10   2025-01-09 [1] RSPM
 geepack                 1.3.12   2024-09-23 [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
 httpuv                  1.6.15   2024-03-26 [1] RSPM
 jquerylib               0.1.4    2021-04-26 [1] RSPM
 jsonlite                1.9.1    2025-03-03 [1] RSPM
 knitr                   1.50     2025-03-16 [1] RSPM
 later                   1.4.1    2024-11-27 [1] RSPM
 lattice                 0.22-6   2024-03-20 [2] CRAN (R 4.4.2)
 lifecycle               1.0.4    2023-11-07 [1] RSPM
 logger                  0.4.0    2024-10-22 [1] RSPM
 magrittr              * 2.0.3    2022-03-30 [1] RSPM
 MASS                    7.3-65   2025-02-28 [2] CRAN (R 4.4.2)
 Matrix                  1.7-3    2025-03-11 [1] CRAN (R 4.4.2)
 memoise                 2.0.1    2021-11-26 [1] RSPM
 mime                    0.13     2025-03-17 [1] RSPM
 multcomp                1.4-28   2025-01-29 [1] RSPM
 munsell                 0.5.1    2024-04-01 [1] RSPM
 mvtnorm                 1.3-3    2025-01-10 [1] RSPM
 nestcolor               0.1.3    2025-01-21 [1] RSPM
 nlme                    3.1-167  2025-01-27 [2] CRAN (R 4.4.2)
 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
 promises                1.3.2    2024-11-28 [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
 Rcpp                    1.0.14   2025-01-12 [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
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 sass                    0.4.9    2024-03-15 [1] RSPM
 scales                  1.3.0    2023-11-28 [1] RSPM
 sessioninfo             1.2.3    2025-02-05 [1] any (@1.2.3)
 shiny                 * 1.10.0   2024-12-14 [1] RSPM
 shinycssloaders         1.1.0    2024-07-30 [1] RSPM
 shinyjs                 2.1.0    2021-12-23 [1] RSPM
 shinyvalidate           0.1.3    2023-10-04 [1] RSPM
 shinyWidgets            0.9.0    2025-02-21 [1] RSPM
 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)
 teal                  * 0.16.0   2025-02-23 [1] RSPM
 teal.code             * 0.6.1    2025-02-14 [1] RSPM
 teal.data             * 0.7.0    2025-01-28 [1] RSPM
 teal.logger             0.3.2    2025-02-14 [1] RSPM
 teal.modules.clinical * 0.10.0   2025-02-28 [1] RSPM
 teal.reporter           0.4.0    2025-01-24 [1] RSPM
 teal.slice            * 0.6.0    2025-02-03 [1] RSPM
 teal.transform        * 0.6.0    2025-02-12 [1] RSPM
 teal.widgets            0.4.3    2025-01-31 [1] RSPM
 tern                  * 0.9.7    2025-01-17 [1] RSPM
 tern.gee                0.1.5    2024-08-23 [1] RSPM
 testthat                3.2.3    2025-01-13 [1] RSPM
 TH.data                 1.1-3    2025-01-17 [1] RSPM
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 xtable                  1.8-4    2019-04-21 [1] RSPM
 yaml                    2.3.10   2024-07-26 [1] RSPM
 zoo                     1.8-13   2025-02-22 [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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