CMT02_PT

Concomitant Medications by Preferred Name (WHODrug Coding)

Standard Table
Data Setup

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Code

split_fun <- drop_split_levels

lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARM") %>%
  add_overall_col("All Patients") %>%
  analyze_num_patients(
    vars = "USUBJID",
    count_by = "CMSEQ",
    .stats = c("unique", "nonunique"),
    .labels = c(
      unique = "Total number of patients with at least one treatment",
      nonunique = "Total number of treatments"
    ),
    show_labels = "hidden"
  ) %>%
  count_occurrences(vars = "CMDECOD") %>%
  append_topleft(paste("\nOther Treatment"))

result <- build_table(lyt = lyt, df = adcm, alt_counts_df = adsl) %>%
  sort_at_path(
    path = c("CMDECOD"),
    scorefun = score_occurrences
  )

result

                                                        A: Drug X    B: Placebo    C: Combination   All Patients
Other Treatment                                          (N=134)       (N=134)        (N=132)         (N=400)   
————————————————————————————————————————————————————————————————————————————————————————————————————————————————
Total number of patients with at least one treatment   117 (87.3%)   116 (86.6%)    116 (87.9%)     349 (87.2%) 
Total number of treatments                                 415           414            460             1289    
medname C_2/2                                          52 (38.8%)    58 (43.3%)      60 (45.5%)     170 (42.5%) 
medname B_1/4                                          52 (38.8%)    57 (42.5%)      59 (44.7%)     168 (42.0%) 
medname A_2/3                                          53 (39.6%)    50 (37.3%)      56 (42.4%)     159 (39.8%) 
medname C_1/2                                          51 (38.1%)    50 (37.3%)      56 (42.4%)     157 (39.2%) 
medname B_4/4                                          50 (37.3%)    45 (33.6%)      55 (41.7%)     150 (37.5%) 
medname A_3/3                                          45 (33.6%)    54 (40.3%)      48 (36.4%)     147 (36.8%)

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
adcm <- random.cdisc.data::cadcm

adcm$CMSEQ <- as.factor(adcm$CMSEQ)

# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.
# If you want your missing levels to show as "No Coding Available", please use
adsl <- df_explicit_na(adsl, na_level = "No Coding Available")
adcm <- df_explicit_na(adcm, na_level = "No Coding Available")

# Keep only safety-evaluable patients and concomitant medications
adsl <- adsl %>%
  filter(SAFFL == "Y")

# Keep only concomitant medications
adcm <- adcm %>% filter(ATIREL == "CONCOMITANT")

Code

library(teal.modules.clinical)

adcm_keys <- c("STUDYID", "USUBJID", "ASTDTM", "CMSEQ", "ATC1", "ATC2", "ATC3", "ATC4")

## Data reproducible code
data <- teal_data()
data <- within(data, {
  ADSL <- random.cdisc.data::cadsl
  ADCM <- random.cdisc.data::cadcm
  ADCM$CMSEQ <- as.integer(ADCM$CMSEQ)

  ADSL <- df_explicit_na(ADSL)
  ADCM <- df_explicit_na(ADCM)
})
datanames <- c("ADSL", "ADCM")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]
join_keys(data)["ADCM", "ADCM"] <- adcm_keys

## Reusable Configuration For Modules
ADCM <- data[["ADCM"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_mult_events(
      label = "Concomitant Medications by Medication Class and Preferred Name",
      dataname = "ADCM",
      arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
      seq_var = choices_selected("CMSEQ", selected = "CMSEQ", fixed = TRUE),
      hlt = choices_selected(
        choices = variable_choices(ADCM, c("ATC1", "ATC2", "ATC3", "ATC4")),
        selected = c("ATC1")
      ),
      llt = choices_selected(
        choices = variable_choices(ADCM, c("CMDECOD")),
        selected = c("CMDECOD")
      ),
      add_total = TRUE,
      event_type = "treatment"
    )
  ),
  filter = teal_slices(
    teal_slice("ADSL", "SAFFL", selected = "Y"),
    teal_slice("ADCM", "ATIREL", selected = "CONCOMITANT")
  )
)

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

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

adcm_keys <- c("STUDYID", "USUBJID", "ASTDTM", "CMSEQ", "ATC1", "ATC2", "ATC3", "ATC4")

## Data reproducible code
data <- teal_data()
data <- within(data, {
  ADSL <- random.cdisc.data::cadsl
  ADCM <- random.cdisc.data::cadcm
  ADCM$CMSEQ <- as.integer(ADCM$CMSEQ)

  ADSL <- df_explicit_na(ADSL)
  ADCM <- df_explicit_na(ADCM)
})
datanames <- c("ADSL", "ADCM")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]
join_keys(data)["ADCM", "ADCM"] <- adcm_keys

## Reusable Configuration For Modules
ADCM <- data[["ADCM"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_mult_events(
      label = "Concomitant Medications by Medication Class and Preferred Name",
      dataname = "ADCM",
      arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
      seq_var = choices_selected("CMSEQ", selected = "CMSEQ", fixed = TRUE),
      hlt = choices_selected(
        choices = variable_choices(ADCM, c("ATC1", "ATC2", "ATC3", "ATC4")),
        selected = c("ATC1")
      ),
      llt = choices_selected(
        choices = variable_choices(ADCM, c("CMDECOD")),
        selected = c("CMDECOD")
      ),
      add_total = TRUE,
      event_type = "treatment"
    )
  ),
  filter = teal_slices(
    teal_slice("ADSL", "SAFFL", selected = "Y"),
    teal_slice("ADCM", "ATIREL", selected = "CONCOMITANT")
  )
)

shinyApp(app$ui, app$server)

Reproducibility

Timestamp

[1] "2024-11-02 18:07:27 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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 [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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