Events by Term Plot

This function plots commonly occurred events by number of unique subjects with events. It creates basic summary of events and compares event occurrences between comparison and reference arms, and can be used for events data such as Adverse Events.

Usage

g_events_term_id(
  term,
  id,
  arm,
  arm_N,
  ref = levels(arm)[1],
  trt = levels(arm)[2],
  sort_by = c("term", "riskdiff", "meanrisk"),
  rate_range = c(0, 1),
  diff_range = c(-1, 1),
  reversed = FALSE,
  conf_level = 0.95,
  diff_ci_method = c("wald", "waldcc", "ac", "score", "scorecc", "mn", "mee", "blj",
    "ha", "beal"),
  axis_side = c("left", "right"),
  color = c(getOption("ggplot2.discrete.colour"), "blue", "red")[1:2],
  shape = c(16, 17),
  fontsize = 4,
  draw = TRUE
)

Arguments

term

character or factor vector, or data.frame
Represents events information. term can be a data.frame produced by create_flag_vars, with each column being a logical event indicator

id

(vector)
contains subject identifier. Length of id must be the same as the length or number of rows of terms. Usually it is ADAE$USUBJID.

arm

(factor)
vector that contains arm information in analysis data. For example, ADAE$ACTARMCD.

arm_N

(numeric vector)
Contains information of the number of patients in the levels of arm. This is useful if there are patients that have no adverse events can be accounted for with this argument.

ref

character indicates the name of the reference arm. Default is the first level of arm.

trt

character indicates the name of the treatment arm. Default is the second level of arm.

sort_by

character indicates how each term is sorted in the plot. Choose from "term" for alphabetic terms, "riskdiff" for risk difference, and "meanrisk" for mean risk. Default is "term".

rate_range

Numeric vector of length 2. Range for overall rate display

diff_range

Numeric vector of length 2. Range for rate difference display

reversed

logical whether to reverse the sorting by sort_by. Default is FALSE.

conf_level

(numeric)
the confidence interval level, default is 0.95.

diff_ci_method

(character)
the method used to calculate confidence interval. Default is "wald". Possible choices are methods supported in BinomDiffCI.

axis_side

character the side of the axis label, "left" or "right". Default is "left".

color

Color for the plot. vector of length 2. Color for reference and treatment arms respectively. Default set to c("blue", "red").

shape

Shape for the plot. vector of length 2. Shape for reference and treatment arms respectively. Default set to c(16, 17) per scale_shape.

fontsize

(numeric)
font size for the plot. It is the size used in ggplot2 with default unit "mm", if you want "points" you will need to divide the point number by ggplot2:::.pt.

draw

(logical)
whether to draw the plot.

Value

grob object

Details

there is no equivalent STREAM output

Author

Liming Li (Lil128) liming.li@roche.com

Molly He (hey59) hey59@gene.com

Examples

library(dplyr)
library(grid)
library(nestcolor)

ADSL <- osprey::rADSL
ADAE <- osprey::rADAE

# add additional dummy causality flags
ADAE <- ADAE %>%
  mutate(AEREL1 = (AEREL == "Y" & ACTARM == "A: Drug X")) %>%
  mutate(AEREL2 = (AEREL == "Y" & ACTARM == "B: Placebo"))
attr(ADAE[["AEREL1"]], "label") <- "AE related to A: Drug X"
attr(ADAE[["AEREL2"]], "label") <- "AE related to B: Placebo"

term <- ADAE$AEDECOD
id <- ADAE$USUBJID
arm <- ADAE$ACTARMCD
arm_N <- table(ADSL$ACTARMCD)
ref <- "ARM A"
trt <- "ARM C"

# Example 1
p1 <- g_events_term_id(
  term,
  id,
  arm,
  arm_N
)

grid::grid.newpage()
grid::grid.draw(p1)

# Example 2
p2 <- g_events_term_id(
  term,
  id,
  arm,
  arm_N,
  trt = trt,
  ref = ref,
  sort_by = "riskdiff",
  diff_ci_method = "ac",
  conf_level = 0.9
)

grid::grid.newpage()
grid::grid.draw(p2)

# Example 3
p3 <- g_events_term_id(
  term,
  id,
  arm,
  arm_N,
  sort_by = "meanrisk",
  axis_side = "right",
  fontsize = 5
)

grid::grid.newpage()
grid::grid.draw(p3)

# Example 4
term <- create_flag_vars(ADAE)
g_events_term_id(
  term,
  id,
  arm,
  arm_N,
  fontsize = 3
)