BRG01

Bar Chart

---

Plot of Frequency

Preview

anl <- adae %>%
  filter(AESER == "Y")
anl <- anl[!duplicated(anl$USUBJID), ]

plot <- ggplot(anl, aes(x = .data[["ACTARM"]])) +
  geom_bar(fill = getOption("ggplot2.discrete.fill")[1]) +
  geom_text(stat = "count", aes(label = ggplot2::after_stat(count)), vjust = -.5) +
  theme(plot.title = element_text(hjust = 0.5)) +
  ggtitle("Frequency of Subjects With Serious AEs: Safety-Evaluable Subjects") +
  xlab(paste0(getElement(vl_ae, "ACTARM"), " (N = ", denom, ")")) +
  ylab("Frequency")
plot

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Plot of Percentage

Preview

anl <- adae %>%
  filter(AESOC == "cl A")

anl <- anl[!duplicated(anl$USUBJID), ] %>%
  group_by(ACTARM) %>%
  summarise(n = n()) %>%
  mutate(N = patpop) %>%
  mutate(N = as.numeric(N)) %>%
  mutate(pct = round((n / N) * 100, 2))

plot <- ggplot(anl, aes(x = .data[["ACTARM"]])) +
  geom_col(aes(x = ACTARM, y = pct), fill = getOption("ggplot2.discrete.fill")[1]) +
  scale_y_continuous(labels = scales::comma) +
  geom_text(aes(y = pct, label = pct), stat = "identity", vjust = -0.5) +
  theme(plot.title = element_text(hjust = 0.5)) +
  ggtitle("Percent of Subjects With cl A Disorders: Safety-Evaluable Subjects") +
  xlab(paste0(getElement(vl_ae, "ACTARM"), " (N = ", denom, ")")) +
  ylab("Percent")
plot

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Plot of Frequency with Total Number of Subjects

Preview

anl <- adae %>%
  filter(AESOC == "cl A")
anl <- anl[!duplicated(anl$USUBJID), ]

anl <- anl %>%
  group_by(ACTARM) %>%
  mutate(n = n()) %>%
  mutate(xvarlabel = paste0(ACTARM, "\n\nN = ", n))

plot <- ggplot(anl, aes(x = .data[["xvarlabel"]])) +
  geom_bar(fill = getOption("ggplot2.discrete.fill")[1]) +
  theme(plot.title = element_text(hjust = 0.5)) +
  ggtitle("Frequency of Subjects With Serious AEs: Safety-Evaluable Subjects") +
  xlab(paste0(getElement(vl_ae, "ACTARM"), " (N = ", denom, ")")) +
  ylab("Frequency")
plot

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Experimental use!

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Plot of Frequency with Horizontal Bars

Preview

anl <- adae %>%
  filter(AESER == "Y")
anl <- anl[!duplicated(anl$USUBJID), ]

plot <- ggplot(anl, aes(x = .data[["ACTARM"]])) +
  geom_bar(fill = getOption("ggplot2.discrete.fill")[1]) +
  theme(plot.title = element_text(hjust = 0.5)) +
  ggtitle("Frequency of Subjects With Serious AEs: Safety-Evaluable Subjects") +
  xlab(paste0(getElement(vl_ae, "ACTARM"), " (N = ", denom, ")")) +
  ylab("Frequency") +
  coord_flip()
plot

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Plot of Percentage and Confidence Intervals

Preview

anl <- adlb %>%
  filter(PARAMCD == "ALT" & ANRIND == "HIGH")
anl <- anl[!duplicated(anl$USUBJID), ]

patpop5 <- as.data.frame(table(adsl$ACTARM)) %>%
  mutate(ACTARM = as.vector(Var1)) %>%
  mutate(TRTPOP = Freq) %>%
  select(ACTARM, TRTPOP)

anlpop <- as.data.frame(table(anl$ANRIND, anl$ACTARM)) %>%
  filter(Var1 == "HIGH") %>%
  mutate(ACTARM = as.vector(Var2)) %>%
  mutate(EVENTCOUNT = Freq) %>%
  select(ACTARM, EVENTCOUNT)

anl <- left_join(patpop5, anlpop, by = "ACTARM")
CIs <- binom.confint(x = anl$EVENTCOUNT, n = anl$TRTPOP, methods = "exact") 
anl <- cbind(anl, CIs[, 4:6])

plot <- ggplot(anl) +
  geom_bar(
    aes(x = ACTARM, y = mean * 100),
    stat = "identity",
    fill = getOption("ggplot2.discrete.fill")[1],
    alpha = 0.7
  ) +
  geom_errorbar(
    aes(x = ACTARM, ymin = lower * 100, ymax = upper * 100),
    width = 0.5,
    colour = "#20b4ff",
    alpha = 0.9,
    linewidth = 1.0
  ) +
  theme(plot.title = element_text(hjust = 0.5)) +
  ggtitle("Percent of Subjects with Abnormaly High ALT: Safety-Evaluable Subjects") +
  xlab(paste0(getElement(vl_ae, "ACTARM"), " (N = ", denom, ")")) +
  ylab("Percentage")
plot

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Plot of Percentage by Treatment and Covariate

Preview

anl <- adae %>%
  filter(AESER == "Y")

patpop6 <- dplyr::count(adsl, ACTARM, SEX, name = "N_arm_sex")

anl <- anl[!duplicated(anl$USUBJID), ] %>%
  group_by(ACTARM, SEX) %>%
  summarise(n = n(), .groups = "drop") %>%
  left_join(patpop6, by = c("ACTARM", "SEX")) %>%
  mutate(pct = round((n / N_arm_sex) * 100, 2))

plot <- ggplot(anl, aes(x = .data[["ACTARM"]], fill = .data[["SEX"]])) +
  geom_col(aes(y = pct), position = position_dodge()) +
  guides(fill = guide_legend(title = getElement(vl_ae, "SEX"))) +
  scale_y_continuous(labels = scales::comma) +
  theme(plot.title = element_text(hjust = 0.5)) +
  ggtitle("Percent of Subjects With Serious AEs: Safety-Evaluable Subjects") +
  xlab(paste0(getElement(vl_ae, "ACTARM"), " (N = ", denom, ")")) +
  ylab("Percent")
plot

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Plot of Percentage by Covariate and Treatment

Preview

anl <- adae %>%
  filter(AESER == "Y")

anl <- anl[!duplicated(anl$USUBJID), ] %>%
  group_by(SEX, ACTARM) %>%
  summarise(n = n(), .groups = "drop_last") %>%
  mutate(N = patpop) %>%
  mutate(N = as.numeric(N)) %>%
  mutate(pct = round((n / N) * 100, 2))

plot <- ggplot(anl, aes(x = .data[["SEX"]], fill = .data[["ACTARM"]])) +
  geom_col(aes(y = pct), position = position_dodge()) +
  guides(fill = guide_legend(title = getElement(vl_ae, "ACTARM"))) +
  scale_y_continuous(labels = scales::comma) +
  theme(plot.title = element_text(hjust = 0.5)) +
  ggtitle("Percent of Subjects With Serious AEs: Safety-Evaluable Subjects") +
  xlab(paste0(getElement(vl_ae, "SEX"), " (N = ", denom, ")")) +
  ylab("Percent")
plot

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Plot of Percentage with Mean and Median

Preview

anl1 <- adlb %>%
  filter(AVISIT == "BASELINE", PARAMCD == "CRP" & ANRIND == "HIGH")

anl <- anl1[!duplicated(anl1$USUBJID), ] %>%
  group_by(ACTARM) %>%
  summarise(n = n()) %>%
  mutate(N = patpop) %>%
  mutate(N = as.numeric(N)) %>%
  mutate(pct = round((n / N) * 100, 2))

graph <- ggplot(anl, aes(x = .data[["ACTARM"]])) +
  geom_col(aes(x = ACTARM, y = pct), fill = getOption("ggplot2.discrete.fill")[1]) +
  scale_y_continuous(labels = scales::comma, expand = expansion(c(0, .25))) +
  geom_text(aes(y = pct, label = pct), stat = "identity", vjust = -0.5) +
  theme(plot.title = element_text(hjust = 0.5)) +
  ggtitle("Percent of Subjects with Abnormaly High CRP at Baseline \n Safety-Evaluable Subjects") +
  xlab(paste0(getElement(vl_lb, "ACTARM"), " (N = ", denom, ")")) +
  ylab("Percent")

sd_w <- anl1 %>%
  group_by(ACTARM) %>%
  summarise(
    mean = round(mean(AVAL, na.rm = TRUE), 2),
    median = round(median(AVAL, na.rm = TRUE), 2)
  ) %>%
  arrange(ACTARM)

sd_l <- gather(sd_w, key = stat, value = value, mean:median)
sd_l <- sd_l %>% mutate(
  stat_lbl = case_when(
    stat == "mean" ~ "Mean",
    stat == "median" ~ "Median"
  )
)

sd_l$stat_lbl <- factor(sd_l$stat_lbl, levels = c("Median", "Mean"))

tbl_theme <- theme(
  panel.border = element_blank(),
  panel.grid.major = element_blank(),
  panel.grid.minor = element_blank(),
  axis.ticks = element_blank(),
  axis.title = element_blank(),
  axis.text.y = element_text(face = "plain"),
  axis.text.x = element_blank()
)

tbl <- ggplot(sd_l, aes(x = ACTARM, y = stat_lbl, label = value)) +
  geom_text(size = 3) +
  scale_y_discrete(labels = levels(sd_l$stat_lbl)) +
  theme_bw() +
  tbl_theme

plot <- cowplot::plot_grid(graph, tbl,
  rel_heights = c(4, 1),
  ncol = 1, nrow = 2, align = "v"
)
plot

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Plot of Categorical Variable

Preview

anl <- adae

anl <- anl %>%
  arrange(USUBJID, AETOXGRC) %>%
  group_by(USUBJID) %>%
  slice(n()) %>%
  ungroup()

anl <- anl[!duplicated(anl$USUBJID), ] %>%
  group_by(ACTARM, AETOXGRC) %>%
  summarise(n = n(), .groups = "drop_last") %>%
  mutate(N = patpop) %>%
  mutate(N = as.numeric(N)) %>%
  mutate(pct = round((n / N) * 100, 2))

plot <- ggplot(anl, aes(x = .data[["ACTARM"]], fill = .data[["AETOXGRC"]])) +
  geom_col(aes(y = pct)) +
  guides(fill = guide_legend(title = getElement(vl_ae, "AETOXGRC"))) +
  scale_y_continuous(labels = scales::comma) +
  theme(plot.title = element_text(hjust = 0.5)) +
  ggtitle("Percent of Subjects With AE by Highest \n NCI CTCAE Grade: Safety-Evaluable Subjects") +
  xlab(paste0(getElement(vl_ae, "ACTARM"), " (N = ", denom, ")")) +
  ylab("Percent")
plot

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Experimental use!

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Data Setup

library(binom)
library(dplyr)
library(ggplot2)
library(tidyr)
library(tern)
library(nestcolor)

adsl <- random.cdisc.data::cadsl

# filtered population
patpop_df <- adsl %>%
  group_by(STUDYID) %>%
  summarise(patpop = n())
patpop <- setNames(patpop_df$patpop, patpop_df$STUDYID)
denom <- patpop_df$patpop

adae <- random.cdisc.data::cadae %>%
  mutate(AETOXGRC = as.character(AETOXGR))
attributes(adae$AETOXGRC)$label <- "Analysis Toxicity Grade (C)"
vl_ae <- var_labels(adae)

adlb <- random.cdisc.data::cadlb
vl_lb <- var_labels(adlb)

Reproducibility

Timestamp

[1] "2024-11-02 17:55:07 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 ───────────────────────────────────────────────────────────────────
 package           * version date (UTC) lib source
 backports           1.5.0   2024-05-23 [1] CRAN (R 4.4.1)
 binom             * 1.1-1.1 2022-05-02 [1] CRAN (R 4.4.1)
 brio                1.1.5   2024-04-24 [1] CRAN (R 4.4.1)
 broom               1.0.7   2024-09-26 [1] CRAN (R 4.4.1)
 checkmate           2.3.2   2024-07-29 [1] CRAN (R 4.4.1)
 cli                 3.6.3   2024-06-21 [1] CRAN (R 4.4.1)
 codetools           0.2-20  2024-03-31 [2] CRAN (R 4.4.1)
 colorspace          2.1-1   2024-07-26 [1] CRAN (R 4.4.1)
 cowplot             1.1.3   2024-01-22 [1] CRAN (R 4.4.1)
 digest              0.6.37  2024-08-19 [1] CRAN (R 4.4.1)
 dplyr             * 1.1.4   2023-11-17 [1] CRAN (R 4.4.1)
 evaluate            1.0.1   2024-10-10 [1] CRAN (R 4.4.1)
 fansi               1.0.6   2023-12-08 [1] CRAN (R 4.4.1)
 farver              2.1.2   2024-05-13 [1] CRAN (R 4.4.1)
 fastmap             1.2.0   2024-05-15 [1] CRAN (R 4.4.1)
 formatters        * 0.5.9   2024-09-12 [1] CRAN (R 4.4.1)
 generics            0.1.3   2022-07-05 [1] CRAN (R 4.4.1)
 ggplot2           * 3.5.1   2024-04-23 [1] CRAN (R 4.4.1)
 glue                1.8.0   2024-09-30 [1] CRAN (R 4.4.1)
 gtable              0.3.6   2024-10-25 [1] CRAN (R 4.4.1)
 htmltools           0.5.8.1 2024-04-04 [1] CRAN (R 4.4.1)
 htmlwidgets         1.6.4   2023-12-06 [1] CRAN (R 4.4.1)
 jsonlite            1.8.9   2024-09-20 [1] CRAN (R 4.4.1)
 knitr               1.48    2024-07-07 [1] CRAN (R 4.4.1)
 labeling            0.4.3   2023-08-29 [1] CRAN (R 4.4.1)
 lattice             0.22-6  2024-03-20 [2] CRAN (R 4.4.1)
 lifecycle           1.0.4   2023-11-07 [1] CRAN (R 4.4.1)
 magrittr          * 2.0.3   2022-03-30 [1] CRAN (R 4.4.1)
 Matrix              1.7-0   2024-04-26 [1] CRAN (R 4.4.1)
 munsell             0.5.1   2024-04-01 [1] CRAN (R 4.4.1)
 nestcolor         * 0.1.2   2023-06-09 [1] CRAN (R 4.4.1)
 pillar              1.9.0   2023-03-22 [1] CRAN (R 4.4.1)
 pkgconfig           2.0.3   2019-09-22 [1] CRAN (R 4.4.1)
 purrr               1.0.2   2023-08-10 [1] CRAN (R 4.4.1)
 R6                  2.5.1   2021-08-19 [1] CRAN (R 4.4.1)
 random.cdisc.data   0.3.16  2024-11-02 [1] https://insightsengineering.r-universe.dev (R 4.4.1)
 rbibutils           2.3     2024-10-04 [1] CRAN (R 4.4.1)
 Rdpack              2.6.1   2024-08-06 [1] CRAN (R 4.4.1)
 rlang               1.1.4   2024-06-04 [1] CRAN (R 4.4.1)
 rmarkdown           2.28    2024-08-17 [1] CRAN (R 4.4.1)
 rtables           * 0.6.10  2024-09-20 [1] CRAN (R 4.4.1)
 scales              1.3.0   2023-11-28 [1] CRAN (R 4.4.1)
 sessioninfo         1.2.2   2021-12-06 [1] CRAN (R 4.4.1)
 stringi             1.8.4   2024-05-06 [1] CRAN (R 4.4.1)
 stringr             1.5.1   2023-11-14 [1] CRAN (R 4.4.1)
 survival            3.7-0   2024-06-05 [2] CRAN (R 4.4.1)
 tern              * 0.9.6   2024-09-24 [1] CRAN (R 4.4.1)
 testthat            3.2.1.1 2024-04-14 [1] CRAN (R 4.4.1)
 tibble              3.2.1   2023-03-20 [1] CRAN (R 4.4.1)
 tidyr             * 1.3.1   2024-01-24 [1] CRAN (R 4.4.1)
 tidyselect          1.2.1   2024-03-11 [1] CRAN (R 4.4.1)
 utf8                1.2.4   2023-10-22 [1] CRAN (R 4.4.1)
 vctrs               0.6.5   2023-12-01 [1] CRAN (R 4.4.1)
 withr               3.0.2   2024-10-28 [1] CRAN (R 4.4.1)
 xfun                0.49    2024-10-31 [1] CRAN (R 4.4.1)
 yaml                2.3.10  2024-07-26 [1] CRAN (R 4.4.1)

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

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