LBT15

Laboratory Test Shifts to NCI CTCAE Grade 3-4 Post-Baseline

---

Standard Table

Preview

# Argument exclude_base_abn must be TRUE to include patients with normal or abnormal in the opposite
# direction in the denom.
# So for "High" direction, subjects with baseline grade 3-4 are not in the denom.
lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by(var = "ARM") %>%
  add_overall_col("All Patients") %>%
  split_rows_by(
    "PARCAT1",
    split_fun = drop_split_levels, label_pos = "topleft", split_label = obj_label(adlb$PARCAT1)
  ) %>%
  split_rows_by(
    "PARAM",
    split_fun = drop_split_levels, label_pos = "topleft", split_label = obj_label(adlb$PARAM)
  ) %>%
  count_abnormal(
    var = "ANRIND",
    abnormal = list(Low = "LOW", High = "HIGH"),
    variables = list(id = "USUBJID", baseline = "BNRIND"),
    exclude_base_abn = TRUE,
    .indent_mods = 4L
  ) %>%
  append_topleft("            Direction of Abnormality")

result <- build_table(lyt, adlb, alt_counts_df = adsl)
result

Category for Lab Test                                                                                      
  Parameter                                A: Drug X        B: Placebo     C: Combination    All Patients  
            Direction of Abnormality        (N=134)          (N=134)          (N=132)           (N=400)    
———————————————————————————————————————————————————————————————————————————————————————————————————————————
CHEMISTRY                                                                                                  
  Alanine Aminotransferase Measurement                                                                     
            Low                          32/127 (25.2%)    32/128 (25%)     32/128 (25%)    96/383 (25.1%) 
            High                             0/134            0/134            0/132             0/400     
  C-Reactive Protein Measurement                                                                           
            Low                          36/127 (28.3%)   36/127 (28.3%)   42/123 (34.1%)   114/377 (30.2%)
            High                         34/124 (27.4%)   33/128 (25.8%)    31/129 (24%)    98/381 (25.7%) 
IMMUNOLOGY                                                                                                 
  Immunoglobulin A Measurement                                                                             
            Low                              0/134            0/134            0/132             0/400     
            High                         33/128 (25.8%)   32/124 (25.8%)   28/120 (23.3%)    93/372 (25%)  

Try this using WebR

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.

Table Modifying Cut Point

Preview

result <- build_table(lyt, adlb_alt_cut, alt_counts_df = adsl)
result

Category for Lab Test                                                                                      
  Parameter                                A: Drug X        B: Placebo     C: Combination    All Patients  
            Direction of Abnormality        (N=134)          (N=134)          (N=132)           (N=400)    
———————————————————————————————————————————————————————————————————————————————————————————————————————————
CHEMISTRY                                                                                                  
  Alanine Aminotransferase Measurement                                                                     
            Low                          46/119 (38.7%)   54/123 (43.9%)    47/127 (37%)    147/369 (39.8%)
            High                             0/134            0/134            0/132             0/400     
  C-Reactive Protein Measurement                                                                           
            Low                          59/122 (48.4%)   56/118 (47.5%)   58/121 (47.9%)   173/361 (47.9%)
            High                         54/122 (44.3%)   46/122 (37.7%)   44/122 (36.1%)   144/366 (39.3%)
IMMUNOLOGY                                                                                                 
  Immunoglobulin A Measurement                                                                             
            Low                              0/134            0/134            0/132             0/400     
            High                         47/124 (37.9%)    54/120 (45%)    47/115 (40.9%)   148/359 (41.2%)

Try this using WebR

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.

Data Setup

Because the random.cdisc.data dataset adlb doesn’t have the PARCAT1 variable, this variable is created from LBCAT in pre-processing.

library(tern)
library(dplyr)
library(forcats)

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

adlb <- adlb %>%
  mutate(
    PARAM = with_label(.data$PARAM, "Laboratory Test"),
    ANRIND = with_label(.data$ANRIND, "Direction of Abnormality")
  ) %>%
  mutate(
    PARCAT1 = LBCAT
  ) %>%
  mutate(
    ANRIND = fct_collapse(.data$ATOXGR,
      "LOW" = c("-3", "-4"),
      "MODERATE/NORMAL" = c("-2", "-1", "0", "1", "2"),
      "HIGH" = c("3", "4")
    ),
    BNRIND = fct_collapse(.data$BTOXGR,
      "LOW" = c("-3", "-4"),
      "MODERATE/NORMAL" = c("-2", "-1", "0", "1", "2"),
      "HIGH" = c("3", "4")
    ),
    PARCAT1 = LBCAT
  ) %>%
  filter(ONTRTFL == "Y")


adlb_alt_cut <- adlb %>%
  mutate(
    ANRIND = fct_collapse(.data$ATOXGR,
      "LOW" = c("-2", "-3", "-4"),
      "MODERATE/NORMAL" = c("-1", "0", "1"),
      "HIGH" = c("2", "3", "4")
    ),
    BNRIND = fct_collapse(.data$BTOXGR,
      "LOW" = c("-2", "-3", "-4"),
      "MODERATE/NORMAL" = c("-1", "0", "1"),
      "HIGH" = c("2", "3", "4")
    )
  ) %>%
  filter(ONTRTFL == "Y")

adlb <- adlb %>% var_relabel(
  PARCAT1 = "Category for Lab Test",
  PARAM = "Parameter"
)

teal App

Preview

The current module tm_t_abnormality is only displaying rows that are not all-zero, so the result could be a little different from static output where all-zero rows can be shown.

library(teal.modules.clinical)

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

  ADSL <- random.cdisc.data::cadsl
  ADLB <- random.cdisc.data::cadlb %>%
    mutate(
      ANRIND = fct_collapse(ATOXGR,
        "LOW" = c("-3", "-4"),
        "MODERATE/NORMAL" = c("-2", "-1", "0", "1", "2"),
        "HIGH" = c("3", "4")
      ),
      BNRIND = fct_collapse(.data$BTOXGR,
        "LOW" = c("-3", "-4"),
        "MODERATE/NORMAL" = c("-2", "-1", "0", "1", "2"),
        "HIGH" = c("3", "4")
      )
    ) %>%
    filter(ONTRTFL == "Y") %>%
    col_relabel(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("PARAM")),
        selected = c("PARAM"),
        keep_order = TRUE
      ),
      grade = choices_selected(
        choices = variable_choices(ADLB, subset = "ANRIND"),
        selected = "ANRIND",
        fixed = TRUE
      ),
      baseline_var = choices_selected(
        choices = variable_choices(ADLB, subset = "BNRIND"),
        selected = "BNRIND",
        fixed = TRUE
      ),
      abnormal = list(Low = "LOW", High = "HIGH"),
      exclude_base_abn = TRUE
    )
  )
)

shinyApp(app$ui, app$server)

Try this using shinylive

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://pharmaverse.r-universe.dev", getOption("webr_pkg_repos")))

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

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

  ADSL <- random.cdisc.data::cadsl
  ADLB <- random.cdisc.data::cadlb %>%
    mutate(
      ANRIND = fct_collapse(ATOXGR,
        "LOW" = c("-3", "-4"),
        "MODERATE/NORMAL" = c("-2", "-1", "0", "1", "2"),
        "HIGH" = c("3", "4")
      ),
      BNRIND = fct_collapse(.data$BTOXGR,
        "LOW" = c("-3", "-4"),
        "MODERATE/NORMAL" = c("-2", "-1", "0", "1", "2"),
        "HIGH" = c("3", "4")
      )
    ) %>%
    filter(ONTRTFL == "Y") %>%
    col_relabel(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("PARAM")),
        selected = c("PARAM"),
        keep_order = TRUE
      ),
      grade = choices_selected(
        choices = variable_choices(ADLB, subset = "ANRIND"),
        selected = "ANRIND",
        fixed = TRUE
      ),
      baseline_var = choices_selected(
        choices = variable_choices(ADLB, subset = "BNRIND"),
        selected = "BNRIND",
        fixed = TRUE
      ),
      abnormal = list(Low = "LOW", High = "HIGH"),
      exclude_base_abn = TRUE
    )
  )
)

shinyApp(app$ui, app$server)

Reproducibility

Timestamp

[1] "2024-11-02 17:57:15 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)

─ Packages ───────────────────────────────────────────────────────────────────
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 teal.logger             0.3.0.9000  2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.logger.git@cd9cc7e)
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 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library

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