Waterfall plot for RECIST data — waterfall

Creates a waterfall plot showing the change from baseline in target lesion size for individual patients, optionally grouped by treatment arm.

Usage

waterfall_plot(
  data,
  ...,
  y = "target_sum_diff_first",
  fill = "best_response",
  shape = NULL,
  arm = NULL,
  subjid = "SUBJID",
  resp_colors = c(CR = "#42b540", PR = "#006dd8", SD = "#925e9f", PD = "#ed0000", `NA` =
    "white"),
  warnings = getOption("grstat_wp_warnings", TRUE)
)

Arguments

data: A dataset containing RECIST best response data. Use calc_best_response to format your raw data.
...: Not used. Ensures that only named arguments are passed.
y: The column representing the numeric outcome (typically change in tumor size). Default is "target_sum_diff_first".
fill: The column indicating the filling color. Default is "best_response", the best response category.
shape: The column to use for an shape layer (e.g., indicating mutation status).
arm: The column indicating treatment arms for faceting.
subjid: The column identifying subjects. Default is "SUBJID".
resp_colors: Colors assigned to response categories.
warnings: Whether to display warnings.

Value

A ggplot object representing a waterfall plot of tumor size change by patient.

Examples

db = grstat_example(N=50)
data_best_resp = calc_best_response(db$recist)

#simple example
waterfall_plot(data_best_resp)


#facet by arm
data_best_resp %>%
  dplyr::left_join(db$enrolres, by="subjid") %>%
  waterfall_plot(arm="ARM")



#add symbols
#use the NA level to not show the case
set.seed(0)
data_symbols = db$recist %>%
  dplyr::summarise(
    new_lesion=ifelse(any(rcnew=="Yes", na.rm=TRUE), "New lesion", NA),
    example_event=cut(runif(1), breaks=c(0,0.05,0.1,1), labels=c("A", "B", NA)),
    .by=subjid
  )

data_best_resp %>%
  dplyr::left_join(data_symbols, by="subjid") %>%
  waterfall_plot(shape="new_lesion")


data_best_resp %>%
  dplyr::left_join(data_symbols, by="subjid") %>%
  waterfall_plot(shape="example_event") +
  ggplot2::labs(shape="Event")