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Merge branch 'main' into 105_table_09_tplyr
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‎NAMESPACE

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@@ -4,6 +4,7 @@ export(alt_counts_df_preproc)
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export(basic_table_annot)
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export(make_fig_01)
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export(make_fig_02)
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export(make_fig_14)
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export(make_table_02)
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export(make_table_02_gtsum)
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export(make_table_02_tplyr)

‎NEWS.md

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`make_table_06`, `make_table_07`, `make_table_08`, `make_table_09`, `make_table_10`, `make_table_11`, `make_table_12`,
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`make_table_13`, `make_table_14`, `make_table_15`, `make_table_16`, `make_table_17`, `make_table_18`, `make_table_20`,
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`make_table_21`, `make_table_22`, `make_table_32`, `make_table_33`, `make_table_34`, `make_table_35`.
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* Added new functions for creating standard FDA figures: `make_fig_01`, `make_fig_02`.
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* Added new functions for creating standard FDA figures: `make_fig_01`, `make_fig_02`, `make_fig_14`.
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* Added helper functions used within table functions:
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* `basic_table_annot` for adding basic table annotations (titles, footnotes, column counts).
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* `split_cols_by_arm` for splitting columns by arm with option to add total column.

‎R/argument_convention.R

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#' @param xticks (`vector` of `numeric`)\cr x-axis tick positions. If `NA` (default), tick mark positions are
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#' automatically calculated.
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#' @param x_lab (`character`)\cr x-axis label.
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#' @param yticks (`vector` of `numeric`)\cr y-axis tick positions. If `NA` (default), tick mark positions are
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#' automatically calculated.
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#' @param y_lab (`character`)\cr y-axis label.
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#'
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#' @name argument_convention

‎R/fda-fig_14.R

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#' FDA Figure 14: Mean and 95% Confidence Interval of Systolic Blood Pressure Over Time
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#' by Treatment Arm, Safety Population, Trial X
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#'
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#' @details
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#' * `df` must contain the variables `AVAL` and `PARAMCD`, and the variables specified by `arm_var`,
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#' `saffl_var`, `visit_var`, and `add_cond`.
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#' * Flag variables (i.e. `XXXFL`) are expected to have two levels: `"Y"` (true) and `"N"` (false). Missing values in
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#' flag variables are treated as `"N"`.
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#' * It is assumed that `df` contains one unique record per patient.
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#'
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#' @inheritParams argument_convention
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#' @param add_table (`flag`)\cr whether "Mean Value" and "Number of Patients" tables should be printed under the plot
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#' @param visit_var (`character`)\cr visit variable to put on the x-axis
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#' @param paramcd_val (`character`)\cr value of `PARAMCD` to plot
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#' @param add_cond (`expr`)\cr expression that provides additional filters for the analysis
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#' (for instance on `ATPT` or `VSPOS`)
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#' @param annotations (named `list` of `character`)\cr list of annotations to add to the figure. Valid annotation types
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#' are `title`, `subtitles`, and `caption`. Each name-value pair should use the annotation type as name and the
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#' desired string as value.
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#'
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#' @return A `ggplot2` object.
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#'
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#' @examples
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#' advs <- random.cdisc.data::cadvs
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#'
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#' fig <- make_fig_14(
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#' df = advs,
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#' add_cond = bquote("ONTRTFL == 'Y' | ABLFL == 'Y'"),
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#' add_table = TRUE,
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#' yticks = c(135, 140, 145, 150, 155, 160)
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#' )
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#' fig
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#'
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#' @export
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make_fig_14 <- function(df,
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arm_var = "ARM",
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saffl_var = "SAFFL",
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visit_var = "AVISIT",
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paramcd_val = "SYSBP",
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add_cond = NULL,
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x_lab = "",
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y_lab = NULL,
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yticks = NA,
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ggtheme = NULL,
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add_table = TRUE,
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annotations = NULL) {
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checkmate::assert_subset(c(arm_var, saffl_var, visit_var), names(df))
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assert_flag_variables(df, saffl_var)
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df <- df %>%
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as_tibble() %>%
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filter(
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.data[[saffl_var]] == "Y",
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PARAMCD == {{ paramcd_val }},
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!is.na(AVAL)
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) %>%
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df_explicit_na()
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if (!(is.null({{ add_cond }}))) {
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df <- df %>%
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filter(!!rlang::parse_expr(add_cond))
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}
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if (is.null({{ y_lab }})) {
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y_param <- unique(df$PARAM)
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y_avalu <- unique(df$AVALU)
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y_lab <- paste0("Mean Value (95% CI)", "\n", y_param, " (", y_avalu, ")")
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}
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df <- df %>%
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group_by(!!sym(arm_var), !!sym(visit_var), .drop = TRUE) %>%
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summarise(
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mean = mean(AVAL, na.rm = TRUE),
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sd = sd(AVAL, na.rm = TRUE),
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n = n()
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) %>%
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mutate(
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se = sd / sqrt(n),
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lower_ci = mean - qt(1 - (0.05 / 2), n - 1) * se,
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upper_ci = mean + qt(1 - (0.05 / 2), n - 1) * se
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) %>%
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ungroup()
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g <-
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ggplot(
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data = df,
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aes(
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x = !!sym(visit_var),
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y = mean,
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group = .data[[arm_var]],
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color = .data[[arm_var]]
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)
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) +
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geom_point(position = position_dodge(width = 0.5)) +
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geom_line(position = position_dodge(width = 0.5)) +
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geom_errorbar(
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aes(
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ymin = lower_ci,
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ymax = upper_ci
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),
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position = position_dodge(width = 0.5)
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) +
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labs(
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title = annotations[["title"]],
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subtitle = annotations[["subtitle"]],
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caption = annotations[["caption"]],
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x = x_lab,
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y = y_lab
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) +
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theme(
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legend.position = "bottom",
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legend.title = element_blank(),
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plot.margin = unit(c(0.05, 0.05, 0, 0.025), "npc")
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)
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if (any(!is.na(yticks))) {
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g <- g +
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scale_y_continuous(breaks = yticks, limits = c(min(yticks), max(yticks)))
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}
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if (!is.null(ggtheme)) g <- g + ggtheme
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if (add_table) {
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g_legend <- cowplot::get_legend(g)
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g <- g + theme(legend.position = "none")
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tbl_n <- df %>%
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mutate(meanr = sprintf("%.1f", mean)) %>%
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arrange(desc(!!sym(arm_var)))
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g_tbl1 <- ggplot(tbl_n, aes(x = !!sym(visit_var), y = !!sym(arm_var))) +
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theme(
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axis.title.x = element_blank(),
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axis.title.y = element_blank(),
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axis.ticks.x = element_blank(),
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axis.ticks.y = element_blank(),
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panel.background = element_blank(),
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axis.text.x = element_blank(),
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panel.border = element_rect(color = "black", fill = NA, linewidth = 0.5),
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plot.margin = unit(c(0.1, 0.05, 0, 0.025), "npc"),
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plot.title = element_text(size = 10)
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) +
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labs(title = "Mean Value")
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for (i in seq_len(nrow(tbl_n))) {
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g_tbl1 <- g_tbl1 +
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annotate("text", label = as.character(tbl_n$meanr[i]), x = tbl_n[[visit_var]][i], y = tbl_n[[arm_var]][i])
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}
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g_tbl2 <- ggplot(tbl_n, aes(x = !!sym(visit_var), y = !!sym(arm_var))) +
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theme(
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axis.title.x = element_blank(),
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axis.title.y = element_blank(),
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axis.ticks.x = element_blank(),
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axis.ticks.y = element_blank(),
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panel.background = element_blank(),
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axis.text.x = element_blank(),
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panel.border = element_rect(color = "black", fill = NA, linewidth = 0.2),
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plot.margin = unit(c(0.1, 0.05, 0, 0.025), "npc"),
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plot.title = element_text(size = 10)
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) +
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labs(title = "Number of Patients with Data")
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for (i in seq_len(nrow(tbl_n))) {
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g_tbl2 <- g_tbl2 +
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annotate("text", label = as.character(tbl_n$n[i]), x = tbl_n[[visit_var]][i], y = tbl_n[[arm_var]][i])
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}
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cowplot::plot_grid(
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g,
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g_tbl1,
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g_tbl2,
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g_legend,
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align = "v",
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axis = "l",
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ncol = 1,
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rel_heights = c(0.60, 0.15, 0.15, 0.1)
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)
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} else {
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g
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}
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}

‎R/fda-table_22.R

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#' AGE >= 65 & AGE < 75 ~ ">=65 to <75",
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#' AGE >= 75 ~ ">=75"
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#' )) %>% formatters::with_label("Age Group, years")) %>%
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#' formatters::var_relabel(
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#' AGE = "Age, years"
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#' )
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#' formatters::var_relabel(AGE = "Age, years")
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#'
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#' adae <- random.cdisc.data::cadae
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#'

‎_quarto.yml

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- quarto/table-templates/template-table_35.qmd
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- quarto/figure-templates/template-fig_01.qmd
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- quarto/figure-templates/template-fig_02.qmd
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- quarto/figure-templates/template-fig_14.qmd
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- text: About
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file: quarto/about.qmd
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- text: Resources

‎man/argument_convention.Rd

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‎man/make_fig_14.Rd

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‎man/make_table_22.Rd

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‎quarto/assets/images/screenshots/fig_14.png

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‎quarto/figure-templates/template-fig_14.qmd

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---
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title: FDA Figure 14
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subtitle: Mean and 95% Confidence Interval of Systolic Blood Pressure Over Time by Treatment Arm, Safety Population, Trial X
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format: html
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---
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::: panel-tabset
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## Spec. Screenshot
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![](../assets/images/screenshots/fig_14.png){fig-align="center"}
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## ggplot2 Figure
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```{r fig, message=FALSE, warning=FALSE, fig.height=7, fig.width=9}
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# Load Libraries & Data
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library(falcon)
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advs <- random.cdisc.data::cadvs
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make_fig_14(
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df = advs,
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add_cond = bquote("ONTRTFL == 'Y' | ABLFL == 'Y'"),
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add_table = TRUE,
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yticks = c(135, 140, 145, 150, 155, 160)
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)
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```
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## Figure Setup
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```{r fig, eval=FALSE, echo=TRUE}
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```
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## Function Details
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### `make_fig_14()`
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------------------------------------------------------------------------
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Required variables:
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- **`df`**: The variables `AVAL` and `PARAMCD`, and the variables specified by `arm_var`, `saffl_var`, and `visit_var`.
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| Argument | Description | Default |
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|:--------------|:------------------------------------------|:--------------|
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| `df` | (`data.frame`) Dataset (typically ADVS) required to build table. | *No default* |
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| `arm_var` | (`character`) Arm variable used to split table into columns. | `"ARM"` |
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| `saffl_var` | (`character`) Flag variable used to indicate inclusion in safety population. | `"SAFFL"` |
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| `visit_var` | (`character`) Visit variable to put on the x-axis. | `"AVISIT"` |
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| `paramcd_val` | (`character`) Value of `PARAMCD` to plot. | `"SYSBP"` |
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| `add_cond` | (`expression`) Additional filter for the analysis (e.g on ATPT or VSPOS). | `NULL` |
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| `x_lab` | (`character`) x-axis label. | `paste0("Time from first dose (", u_trtdur, ")")` |
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| `y_lab` | (`character`) y-axis label. | `"Percent of Patients (%)"` |
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| `yticks` | (`vector` of `numeric`) y-axis tick positions. If `NA` (default), tick mark positions are automatically calculated. | `NA` |
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| `ggtheme` | (`function`) Function from `ggplot2` to apply over the plot. | `NULL` |
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| `add_table` | (`flag`) whether "Number of Patients" table should be printed under the plot. | `TRUE` |
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| `annotations` | (named `list` of `character`) List of annotations to add to the table. Valid annotation types are `title`, `subtitles`, and `caption`. Each name-value pair should use the annotation type as name and the desired string as value. | `NULL` |
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Source code for this function is available [here](https://github.com/pharmaverse/falcon/blob/main/R/fda-fig_14.R).
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:::

‎quarto/index-templates.qmd

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### **FDA Figures**
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- [FDA Figure 1 -- Time to Permanent Discontinuation of Study Drug, Safety Population, Pooled Analyses](figure-templates/template-fig_01.qmd)
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- [FDA Figure 2 -- Time to Last Follow Up, Safety Population, Pooled Analyses](figure-templates/template-fig_02.qmd)
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- [FDA Figure 14 -- Mean and 95% Confidence Interval of Systolic Blood Pressure Over Time by Treatment Arm, Safety Population, Trial X](figure-templates/template-fig_14.qmd)
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