LBT04

Laboratory Abnormalities Not Present at Baseline

Standard Table
Data Setup

Preview
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Code

lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARM") %>%
  split_rows_by("PARAM",
    split_fun = drop_split_levels,
    label_pos = "topleft",
    split_label = obj_label(adlb_f$PARAM)
  ) %>%
  count_abnormal(
    var = "ANRIND",
    abnormal = list(Low = c("LOW", "LOW LOW"), High = c("HIGH", "HIGH HIGH")),
    exclude_base_abn = TRUE
  ) %>%
  append_varlabels(adlb_f, "ANRIND", indent = 1L)

result <- build_table(lyt = lyt, df = adlb_f, alt_counts_df = adsl)

result

Laboratory Test                          A: Drug X        B: Placebo     C: Combination
  Direction of Abnormality                (N=134)          (N=134)          (N=132)    
———————————————————————————————————————————————————————————————————————————————————————
Alanine Aminotransferase Measurement                                                   
  Low                                  57/113 (50.4%)    62/117 (53%)    61/123 (49.6%)
  High                                     0/134            0/134            0/132     
C-Reactive Protein Measurement                                                         
  Low                                  78/119 (65.5%)   71/113 (62.8%)   62/112 (55.4%)
  High                                 69/114 (60.5%)   57/112 (50.9%)   58/115 (50.4%)
Immunoglobulin A Measurement                                                           
  Low                                      0/134            0/134            0/132     
  High                                 64/119 (53.8%)   62/116 (53.4%)   62/113 (54.9%)

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.

Code

library(dplyr)
library(tern)

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

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

adlb_f <- adlb %>%
  filter(ONTRTFL == "Y", ANRIND != "<Missing>") %>%
  var_relabel(
    PARAM = "Laboratory Test",
    ANRIND = "Direction of Abnormality"
  )

Code

library(teal.modules.clinical)

## Data reproducible code
data <- teal_data()
data <- within(data, {
  ADSL <- random.cdisc.data::cadsl
  ADLB <- random.cdisc.data::cadlb %>%
    col_relabel(PARAM = "Laboratory Test", ANRIND = "Direction of Abnormality")
})
datanames <- c("ADSL", "ADLB")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]

## Reusable Configuration For Modules
ADSL <- data[["ADSL"]]
ADLB <- data[["ADLB"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_abnormality(
      label = "Abnormality Table",
      dataname = "ADLB",
      arm_var = choices_selected(
        choices = variable_choices(ADSL, subset = c("ARM", "ARMCD")),
        selected = "ARM"
      ),
      by_vars = choices_selected(
        choices = variable_choices(ADLB, subset = c("LBCAT", "PARAM", "AVISIT")),
        selected = c("LBCAT", "PARAM"),
        keep_order = TRUE
      ),
      grade = choices_selected(
        choices = variable_choices(ADLB, subset = "ANRIND"),
        selected = "ANRIND",
        fixed = TRUE
      ),
      abnormal = list(low = "LOW", high = "HIGH"),
      exclude_base_abn = TRUE
    )
  )
)

shinyApp(app$ui, app$server)

Experimental use!

shinylive allow you to modify to run shiny application entirely in the web browser. Modify the code below and click re-run the app to see the results. The performance is slighly worse and some of the features (e.g. downloading) might not work at all.

#| standalone: true
#| viewerHeight: 800
#| editorHeight: 200
#| components: [viewer, editor]
#| layout: vertical

# -- WEBR HELPERS --
options(webr_pkg_repos = c("r-universe" = "https://insightsengineering.r-universe.dev", getOption("webr_pkg_repos")))

# -- APP CODE --
library(teal.modules.clinical)

## Data reproducible code
data <- teal_data()
data <- within(data, {
  ADSL <- random.cdisc.data::cadsl
  ADLB <- random.cdisc.data::cadlb %>%
    col_relabel(PARAM = "Laboratory Test", ANRIND = "Direction of Abnormality")
})
datanames <- c("ADSL", "ADLB")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]

## Reusable Configuration For Modules
ADSL <- data[["ADSL"]]
ADLB <- data[["ADLB"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_abnormality(
      label = "Abnormality Table",
      dataname = "ADLB",
      arm_var = choices_selected(
        choices = variable_choices(ADSL, subset = c("ARM", "ARMCD")),
        selected = "ARM"
      ),
      by_vars = choices_selected(
        choices = variable_choices(ADLB, subset = c("LBCAT", "PARAM", "AVISIT")),
        selected = c("LBCAT", "PARAM"),
        keep_order = TRUE
      ),
      grade = choices_selected(
        choices = variable_choices(ADLB, subset = "ANRIND"),
        selected = "ANRIND",
        fixed = TRUE
      ),
      abnormal = list(low = "LOW", high = "HIGH"),
      exclude_base_abn = TRUE
    )
  )
)

shinyApp(app$ui, app$server)

Reproducibility

Timestamp

[1] "2024-11-02 18:16:18 UTC"

Session Info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.4.1 (2024-06-14)
 os       Ubuntu 22.04.5 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2024-11-02
 pandoc   3.4 @ /usr/bin/ (via rmarkdown)

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 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library

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

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Reproducibility

Timestamp

Session Info

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`teal` App

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