FSTG01

Subgroup Analysis of Best Overall Response

Output

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Code

df <- extract_rsp_subgroups(
  variables = list(
    rsp = "is_rsp",
    arm = "ARM",
    subgroups = c("SEX", "BMRKR2"),
    strata = "STRATA2"
  ),
  data = anl_rsp_arms_ab,
  conf_level = 0.95
)

result <- basic_table() %>%
  tabulate_rsp_subgroups(df, vars = c("n_tot", "n", "n_rsp", "prop", "or", "ci"))

plot <- g_forest(tbl = result)
plot

Experimental use!

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Code

anl_rsp_comb_arms_ac <- anl %>%
  mutate(is_rsp = AVALC %in% c("CR", "PR")) %>%
  filter(ARMCD %in% c("ARM B", "ARM A", "ARM C")) %>%
  mutate(
    ARMCD = relevel(ARMCD, ref = "ARM B") %>%
      droplevels() %>%
      combine_levels(levels = c("ARM A", "ARM C")),
    ARM = relevel(ARM, ref = "B: Placebo") %>%
      droplevels() %>%
      combine_levels(levels = c("A: Drug X", "C: Combination")),
    # reorder levels of SEX
    SEX = forcats::fct_relevel(SEX, "M", "F"),
    # reorder levels of STRATA1 by frequency
    STRATA1 = forcats::fct_infreq(STRATA1)
  ) %>%
  droplevels()
var_labels(anl_rsp_comb_arms_ac) <- c(anl_labels, is_rsp = "Is Responder")

df <- extract_rsp_subgroups(
  variables = list(
    rsp = "is_rsp",
    arm = "ARMCD",
    subgroups = c("SEX", "BMRKR2"),
    strata = "STRATA2"
  ),
  data = anl_rsp_comb_arms_ac,
  conf_level = 0.95
)

result <- basic_table() %>%
  tabulate_rsp_subgroups(df, vars = c("n_tot", "n", "n_rsp", "prop", "or", "ci"))

plot <- g_forest(tbl = result)
plot

Experimental use!

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Code

df <- extract_rsp_subgroups(
  variables = list(
    rsp = "is_rsp",
    arm = "ARM",
    subgroups = c("SEX", "BMRKR2"),
    strata = "STRATA2"
  ),
  data = anl_rsp_arms_ab,
  conf_level = 0.90
)

result <- basic_table() %>%
  tabulate_rsp_subgroups(df, vars = c("n_tot", "or", "ci"))

plot <- g_forest(tbl = result)
plot

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.

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Code

df <- extract_rsp_subgroups(
  variables = list(
    rsp = "is_rsp",
    arm = "ARM",
    subgroups = c("SEX", "BMRKR2"),
    strata = "STRATA2"
  ),
  data = anl_rsp_arms_ab,
  conf_level = 0.95
)

result <- basic_table() %>%
  tabulate_rsp_subgroups(df, vars = c("n_tot", "n", "n_rsp", "prop", "or", "ci"))

plot <- g_forest(
  tbl = result,
  col_symbol_size = NULL
)
plot

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.

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Code

anl_cr_arms_ab <- anl %>%
  mutate(is_rsp = AVALC == "CR") %>%
  filter(ARMCD %in% c("ARM B", "ARM A")) %>%
  mutate(
    ARMCD = relevel(ARMCD, ref = "ARM B") %>%
      droplevels(),
    ARM = relevel(ARM, ref = "B: Placebo") %>%
      droplevels()
  ) %>%
  droplevels()
var_labels(anl_cr_arms_ab) <- c(anl_labels, is_rsp = "Is CR")

df <- extract_rsp_subgroups(
  variables = list(
    rsp = "is_rsp",
    arm = "ARM",
    subgroups = c("SEX", "BMRKR2"),
    strata = "STRATA2"
  ),
  data = anl_cr_arms_ab,
  conf_level = 0.95
)

result <- basic_table() %>%
  tabulate_rsp_subgroups(df, vars = c("n_tot", "n", "n_rsp", "prop", "or", "ci"))

plot <- g_forest(tbl = result)
plot

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)
library(nestcolor)

adsl_f <- random.cdisc.data::cadsl %>%
  select(STUDYID, USUBJID, ARMCD, ARM, SEX, BMRKR2, STRATA1, STRATA2)

adrs_f <- random.cdisc.data::cadrs %>%
  filter(PARAMCD == "INVET") %>%
  select(STUDYID, USUBJID, PARAMCD, AVISIT, AVALC)

anl <- inner_join(adsl_f, adrs_f, by = c("STUDYID", "USUBJID"))
anl <- df_explicit_na(anl)
anl_labels <- var_labels(anl)

anl_rsp_arms_ab <- anl %>%
  mutate(is_rsp = AVALC %in% c("CR", "PR")) %>%
  filter(ARMCD %in% c("ARM B", "ARM A")) %>%
  mutate(
    ARMCD = relevel(ARMCD, ref = "ARM B") %>%
      droplevels(),
    ARM = relevel(ARM, ref = "B: Placebo") %>%
      droplevels()
  ) %>%
  droplevels()
var_labels(anl_rsp_arms_ab) <- c(anl_labels, is_rsp = "Is Responder")

Code

library(teal.modules.clinical)

## Data reproducible code
data <- teal_data()
data <- within(data, {
  ADSL <- random.cdisc.data::cadsl
  ADRS <- random.cdisc.data::cadrs
})
datanames <- c("ADSL", "ADRS")
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]

arm_ref_comp <- list(
  ARM = list(
    ref = "B: Placebo",
    comp = c("A: Drug X", "C: Combination")
  ),
  ARMCD = list(
    ref = "ARM B",
    comp = c("ARM A", "ARM C")
  )
)

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

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_g_forest_rsp(
      label = "Forest Response",
      dataname = "ADRS",
      arm_var = choices_selected(
        variable_choices(ADSL, c("ARM", "ARMCD")),
        "ARMCD"
      ),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        value_choices(ADRS, "PARAMCD", "PARAM"),
        "BESRSPI"
      ),
      subgroup_var = choices_selected(
        variable_choices(ADSL, names(ADSL)),
        c("BMRKR2", "SEX")
      ),
      strata_var = choices_selected(
        variable_choices(ADSL, c("STRATA1", "STRATA2")),
        "STRATA2"
      ),
      plot_height = c(600L, 200L, 2000L),
      plot_width = c(1100L, 200L, 2000L)
    )
  )
)

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.

#| '!! shinylive warning !!': |
#|   shinylive does not work in self-contained HTML documents.
#|   Please set `embed-resources: false` in your metadata.
#| 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, {
  ADSL <- random.cdisc.data::cadsl
  ADRS <- random.cdisc.data::cadrs
})
datanames <- c("ADSL", "ADRS")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]

arm_ref_comp <- list(
  ARM = list(
    ref = "B: Placebo",
    comp = c("A: Drug X", "C: Combination")
  ),
  ARMCD = list(
    ref = "ARM B",
    comp = c("ARM A", "ARM C")
  )
)

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

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_g_forest_rsp(
      label = "Forest Response",
      dataname = "ADRS",
      arm_var = choices_selected(
        variable_choices(ADSL, c("ARM", "ARMCD")),
        "ARMCD"
      ),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        value_choices(ADRS, "PARAMCD", "PARAM"),
        "BESRSPI"
      ),
      subgroup_var = choices_selected(
        variable_choices(ADSL, names(ADSL)),
        c("BMRKR2", "SEX")
      ),
      strata_var = choices_selected(
        variable_choices(ADSL, c("STRATA1", "STRATA2")),
        "STRATA2"
      ),
      plot_height = c(600L, 200L, 2000L),
      plot_width = c(1100L, 200L, 2000L)
    )
  )
)

shinyApp(app$ui, app$server)

Reproducibility

Timestamp

[1] "2025-08-13 17:40:45 UTC"

Session Info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.5.0 (2025-04-11)
 os       Ubuntu 24.04.2 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2025-08-13
 pandoc   3.7.0.2 @ /usr/bin/ (via rmarkdown)
 quarto   1.7.32 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 package               * version     date (UTC) lib source
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 evaluate                1.0.4       2025-06-18 [1] RSPM
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 glue                    1.8.0       2024-09-30 [1] RSPM
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 logger                  0.4.0       2024-10-22 [1] RSPM
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 Matrix                  1.7-3       2025-03-11 [1] CRAN (R 4.5.0)
 memoise                 2.0.1       2021-11-26 [1] RSPM
 mime                    0.13        2025-03-17 [1] RSPM
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 pkgconfig               2.0.3       2019-09-22 [1] RSPM
 processx                3.8.6       2025-02-21 [1] RSPM
 promises                1.3.3       2025-05-29 [1] RSPM
 ps                      1.9.1       2025-04-12 [1] RSPM
 purrr                   1.1.0       2025-07-10 [1] RSPM
 R6                      2.6.1       2025-02-15 [1] RSPM
 ragg                    1.4.0       2025-04-10 [1] RSPM
 random.cdisc.data       0.3.16.9006 2025-08-13 [1] https://p~
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 RColorBrewer            1.1-3       2022-04-03 [1] RSPM
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 Rdpack                  2.6.4       2025-04-09 [1] RSPM
 rlang                   1.1.6       2025-04-11 [1] RSPM
 rmarkdown               2.29        2024-11-04 [1] RSPM
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 survival                3.8-3       2024-12-17 [2] CRAN (R 4.5.0)
 systemfonts             1.2.3       2025-04-30 [1] RSPM
 teal                  * 0.16.0.9026 2025-08-13 [1] https://p~
 teal.code             * 0.6.1.9006  2025-08-13 [1] https://p~
 teal.data             * 0.7.0.9006  2025-08-13 [1] https://p~
 teal.logger             0.4.0.9001  2025-08-13 [1] https://p~
 teal.modules.clinical * 0.10.0.9016 2025-08-13 [1] https://p~
 teal.reporter           0.4.0.9009  2025-08-13 [1] https://p~
 teal.slice            * 0.6.0.9012  2025-08-13 [1] https://p~
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 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library
 [3] /github/home/R/x86_64-pc-linux-gnu-library/4.5
 * ── Packages attached to the search path.

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

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Output

teal App

Reproducibility

Timestamp

Session Info

.lock file

`teal` App

`.lock` file