R/toxFigures.R
In blakelanglais/ProAE: PRO-CTCAE Scoring, Analysis, and Graphical Tools
Defines functions
toxFigures
Documented in
toxFigures
#' Create PRO-CTCAE severity frequency distribution figures for individual
#' survey items and composite scores
#'
#'
#' Data format should be in 'long' format, where each PRO-CTCAE item is a
#' variable/column.
#'
#' @param dsn A data.frame object with PRO-CTCAE data
#' @param id_var A character string.Name of ID variable differentiating each
#' PRO-CTCAE survey/participant entered as a quoted string.
#' @param cycle_var A character string. Name of variable differentiating one
#' longitudinal/repeated. PRO-CTCAE survey from another, within an individual
#' ID.
#' @param baseline_val A number indicating the expected baseline cycle/time
#' point.
#' @param arm_var A character string. Name of arm variable differentiating
#' treatment groups. Must be character or factor class. Overall AUC
#' will be reported if no arm/grouping variable is provided. Defaults to
#' \code{NA}.
#' @param plot_limit A number. Limit the number of cycles to be plotted up to
#' and including a given cycle number. All available cycle time points are
#' plotted if no cycle number is provided. Defaults to \code{NA}.
#' @param colors A number. Specify the coloring scheme of symptom grades within
#' frequency bars. Options include: 1 = Blue and red color shading, 2 =
#' qualitative color shades (color blind friendly), 3 = black and white.
#' Defaults to 1.
#' @param label A number. Label frequency bars with sample size (n) or percent
#' shown on the y-axis. Label options include: \code{1} = sample size (n)
#' within each cycle (symptom grade 0 or higher), \code{2} = sample size (n)
#' within each cycle with present symptoms (symptom grade > 0), \code{3} =
#' sample size (n) within each cycle with severe symptoms (symptom grade >=
#' 3), \code{4} = percent of subjects within each cycle with present
#' symptoms (symptom grade > 0), \code{5} = percent of subjects within each
#' cycle with severe symptoms (symptom grade >= 3). No labels will be applied
#' if not specified. Defaults to \code{NA}.
#' @param summary_only Logical. Only display the summary measures in figures /
#' Suppress the individual time points from plotting. Defaults to
#' \code{FALSE}.
#' @param cycles_only Logical. Only display the longitudinal time points in
#' figures / Suppress the summary measures from plotting. Defaults to
#' \code{FALSE}.
#' @param x_label A character string. Label for the x axis of the plot. Defaults
#' to \code{"Randomized Treatment Assignment"} if \code{arm_var} is specified,
#' defaults to \code{"Overall"} if not \code{arm_var} is specified.
#' @param x_lab_angle A integer between 0 and 360. Allows the user to rotate the
#' x axis labels in order to fit long arm names (0 or 45 recommended).
#' Defaults to \code{0}.
#' @param x_lab_vjust A number. A ggplot2 object option. Allows the user to
#' vertically adjusts the x axis labels in order to fit arm names. Defaults to
#' \code{1}.
#' @param x_lab_hjust A number. A ggplot2 object option. Allows the user to
#' horizontally adjusts the x axis labels in order to fit arm names. Defaults
#' to \code{0}.
#' @param plot_data Logical. Return the data used to construct plots as element
#' of the returned object. Defaults to \code{FALSE}.
#' @return A list object. The returned object is a (k X 2) or (k x 3) nested
#' list. Where k is the number of PRO-CTCAE item groups (e.g. pain, fatigue,
#' nausea); list[[1 ... i ... k]]. For each list item there are 2 or 3
#' elements. The 1st element of each list item is the name of the PRO-CTCAE
#' item group returned as a string. The 2nd element is the PRO-CTCAE figure as
#' a ggplot object. The 3rd (and optional) element is the data used to
#' construct the ggplot figure, available via \code{plot_data}.
#' @importFrom magrittr %>%
#' @examples
#' fig_acute = toxFigures(dsn = ProAE::tox_acute[c(1:300, 1101:1400),],
#' cycle_var = "Cycle",
#' baseline_val = 1,
#' arm_var = "arm",
#' id_var = "id",
#' label = 0,
#' x_lab_angle = -45,
#' x_lab_vjust = .3,
#' x_lab_hjust = .2,
#' colors = 2)
#' fig_acute[[1]]
#' @export
toxFigures = function(dsn,
id_var,
cycle_var,
baseline_val,
arm_var=NA,
plot_limit=NA,
colors=1,
label=0,
summary_only=FALSE,
cycles_only=FALSE,
x_lab_angle=0,
x_lab_vjust=1,
x_lab_hjust=0,
x_label = "Randomized Treatment Assignment",
plot_data=FALSE){
# ----------------------------------------------------------------
# -- Checks 1/2
# ----------------------------------------------------------------
## -- Assign binding for data.frame variables used within ggplot2 objects as global variables
grade_comp = NULL
grade_item = NULL
arm = NULL
bar_lab_opt = NULL
## -- Required parameters
if(exists("dsn")){
if(!is.data.frame(dsn)){
stop("param dsn must be provided as a data.frame object")
}
} else {stop("param dsn not provided")}
if(exists("id_var")){
if(!is.character(id_var)){
stop("param id_var must be provided as a character string")
} else if (!(id_var %in% colnames(dsn))){
stop(paste0("param id_var (", id_var, ") not found as a variable in dsn (", deparse(substitute(dsn)), ")"))
}
} else {stop("param id_var not provided")}
if(exists("cycle_var")){
if(!is.character(cycle_var)){
stop("param cycle_var must be provided as a character string")
} else if (!(cycle_var %in% colnames(dsn))){
stop(paste0("param cycle_var (", cycle_var, ") not found as a variable in dsn (", deparse(substitute(dsn)), ")"))
}
} else {stop("param cycle_var not provided")}
if(exists("baseline_val")){
if(!(is.numeric(baseline_val) | is.integer(baseline_val) | length(baseline_val)==1)){
stop("param baseline_val must be provided as a single number, of class numeric or integer")
}
} else {stop("param baseline_val not provided")}
## -- Check for any duplicate individuals within cycles
if(any(duplicated(dsn[,c(id_var, cycle_var)]))){
stop(paste0("Duplicate observations were found within id_var and cycle_var combinations (", id_var, " and ", cycle_var, ")"))
}
# ----------------------------------------------------------------
# -- Defaults
# ----------------------------------------------------------------
if(is.na(arm_var)){
arm_var = "overall_"
if(x_label=="Randomized Treatment Assignment"){
x_label = "Overall"
}
}
if(summary_only==TRUE & cycles_only==TRUE){
summary_only = TRUE
}
## -------------------------------------------------------------
## --- Reference data sets
## -------------------------------------------------------------
proctcae_vars[, ] = lapply(proctcae_vars[, ], as.character)
# ================================================================
# ==== ACCOMMODATION FOR 27A HAIR LOSS AMOUNT ====================
# ================================================================
## -- Item 27 asks about hair loss and is referenced as an 'amount'
## -- However this item utilizes the Interference response bank.
## -- This is accommodated here by treating it as Interference then
## -- resulting plot is manually labeled 'Amount' BTL - 20AUG2020
proctcae_vars[proctcae_vars$name=="PROCTCAE_27A_SCL",]$short_label = "Hair Loss Interference"
# ================================================================
# ================================================================
# ================================================================
# ----------------------------------------------------------------
# -- Get existing PROCTCAE variables in dsn
# ----------------------------------------------------------------
## - Individual items
dsn_items0 = toupper(names(dsn)[toupper(names(dsn)) %in% proctcae_vars$name])
dsn_items = dsn_items0[! dsn_items0 %in% as.character(proctcae_vars$name[proctcae_vars$fmt %in% c("yn_2_fmt", "yn_3_fmt", "yn_4_fmt")])]
## - Composites
proctcae_vars_comp0 = proctcae_vars[,-1] %>% dplyr::mutate_if(is.factor, as.character)
# proctcae_vars_comp0 = proctcae_vars[,-1]
proctcae_vars_comp0 = proctcae_vars_comp0[!proctcae_vars_comp0$name %in% as.character(proctcae_vars_comp0$name[proctcae_vars_comp0$fmt %in% c("yn_2_fmt",
"yn_3_fmt",
"yn_4_fmt")]),]
proctcae_vars_comp = c()
proctcae_vars_comp$name = paste0(substr(proctcae_vars_comp0$name, 1, nchar(proctcae_vars_comp0$name)-5), "_COMP")
proctcae_vars_comp$short_label = sub(proctcae_vars_comp0$short_label, pattern = " [[:alpha:]]*$", replacement = "")
proctcae_vars_comp = unique(data.frame(proctcae_vars_comp, stringsAsFactors=FALSE))
dsn_comps = toupper(names(dsn)[toupper(names(dsn)) %in% proctcae_vars_comp$name])
# ----------------------------------------------------------------
# -- Checks 2/2
# ----------------------------------------------------------------
## -- Confirm there are available PRO-CTCAE variables within dsn with expected naming convention
if(identical(dsn_items, character(0)) & identical(dsn_comps, character(0))){
stop(paste0("No PRO-CTCAE variables found within dsn (", deparse(substitute(dsn)), ") meeting the expected naming convention"))
}
# ----------------------------------------------------------------
# -- Cluster available items and composites together
# ----------------------------------------------------------------
## -- Available PRO-CTCAE items and composites available in dsn
refset = data.frame(name = c(dsn_items, dsn_comps))
refset$number = as.integer(gsub("[^0-9]", "", refset$name))
refset$rank = ifelse(grepl("COMP", refset$name), 4,
ifelse(grepl("A_", refset$name), 1,
ifelse(grepl("B_", refset$name), 2, 3)))
refset = refset[order(refset$number,refset$rank),]
refset = merge(x=refset,
y= data.frame(number = unique(refset$number),
group_rank = 1:length(unique(refset$number)),
stringsAsFactors=FALSE),
by="number", all.x=TRUE)
## -- All non-indicator PRO-CTCAE with possible composites
reflabs0 = data.frame(name=proctcae_vars$name,
short_label = proctcae_vars$short_label,
lab = unlist(lapply(strsplit(proctcae_vars$short_label, split=" "), 1, FUN=utils::tail)),
stringsAsFactors=FALSE)
reflabs0$group_lab = ifelse(reflabs0$lab=="Severity", trimws(gsub("Severity","", reflabs0$short_label)),
ifelse(reflabs0$lab=="Frequency", trimws(gsub("Frequency","", reflabs0$short_label)),
trimws(gsub("Interference","", reflabs0$short_label))))
reflabs0 = reflabs0[!grepl("_IND", reflabs0$name),]
reflabs0$comp_name = paste0(substr(reflabs0$name,1,nchar(reflabs0$name)-5),"_COMP")
reflabs1 = unique(reflabs0[c("group_lab", 'comp_name')])
names(reflabs1) = c("group_lab","name")
reflabs1$lab = "Composite"
reflabs = rbind.data.frame(reflabs0[c("name", "group_lab", "lab")],
reflabs1[c("name", "group_lab", "lab")],
stringsAsFactors=FALSE)
refset = merge(x=refset,
y=reflabs,
by= "name", all.x=TRUE)
refset = refset[order(refset$number,refset$rank),]
# ----------------------------------------------------------------
# -- For each available PRO-CTCAE item grouping [i], process
# ----------------------------------------------------------------
for (i in 1:max(refset$group_rank)){
if(i==1){list_out = vector(mode='list', max(refset$group_rank))}
# ----------------------------------------------------------------
# -- For each PRO-CTCAE item within the grouping [j], process
# ----------------------------------------------------------------
group_i = refset[refset$group_rank==i,]
plot_combined0 = data.frame()
for (j in 1:NROW(group_i)){
item = as.character(group_i$name[j])
if(arm_var != "overall_"){
dsn0 = stats::na.omit(dsn[,c(id_var, cycle_var, arm_var, item)])
} else if (arm_var == "overall_"){
dsn0 = stats::na.omit(dsn[,c(id_var, cycle_var, item)])
dsn0$overall_ = "Overall"
}
# ----------------------------------------------------------------
# -- Construct summary measures
# ----------------------------------------------------------------
## -- Maximum grade post baseline
max_post0 = stats::aggregate(dsn0[dsn0[,cycle_var]>baseline_val, item],
by = list(dsn0[dsn0[,cycle_var]>baseline_val,id_var]),
FUN=max)
colnames(max_post0) = c(id_var, item)
max_post0[,cycle_var] = "Maximum*"
max_post1 = unique(merge(x=max_post0, y=dsn0[,c(id_var, arm_var)], by=id_var, all.x = TRUE))
## -- Baseline adjusted
base_adj0 = dsn0[dsn0[,cycle_var]==baseline_val, c(id_var, item)]
colnames(base_adj0)[2] = "base_val"
base_adj1 = merge(x=dsn0, y=base_adj0, by=id_var, all.x=TRUE)
base_adj2 = stats::aggregate(base_adj1[base_adj1[,cycle_var]>baseline_val, item],
by = list(base_adj1[base_adj1[,cycle_var]>baseline_val,id_var]),
FUN=max)
colnames(base_adj2) = c(id_var, "max_post_bl")
base_adj2 = merge(x=base_adj1, y=unique(base_adj2), by=id_var, all.x=TRUE)
base_adj2$bl_adjusted = ifelse(!is.na(base_adj2$max_post_bl) & base_adj2$base_val >= base_adj2$max_post_bl,
0, base_adj2$max_post_bl)
base_adj3 = unique(base_adj2[!is.na(base_adj2$bl_adjusted),c(id_var, arm_var, "bl_adjusted")])
base_adj3[,cycle_var] = "Adjusted**"
colnames(base_adj3)[colnames(base_adj3) == "bl_adjusted"] = item
dsn1 = rbind.data.frame(dsn0, max_post1, base_adj3)
# ----------------------------------------------------------------
# -- Create labels for the bars
# ----------------------------------------------------------------
if(label==0){
labs = dsn1[,c(cycle_var, arm_var)]
labs$bar_lab_opt = NA
} else if(label==1){
labs = stats::aggregate(dsn1[dsn1[,item]>=0,item],
by=list(dsn1[dsn1[,item]>=0,cycle_var],
dsn1[dsn1[,item]>=0,arm_var]),
FUN=length)
} else if(label %in% c(2,4)){
labs = stats::aggregate(dsn1[dsn1[,item]>0,item],
by=list(dsn1[dsn1[,item]>0,cycle_var],
dsn1[dsn1[,item]>0,arm_var]),
FUN=length)
} else if(label %in% c(3,5)){
labs = stats::aggregate(dsn1[dsn1[,item]>=3,item],
by=list(dsn1[dsn1[,item]>=3,cycle_var],
dsn1[dsn1[,item]>=3,arm_var]),
FUN=length)
}
names(labs) = c(cycle_var, arm_var, "bar_lab_opt")
# -- Force zero counts
combo_counts = data.frame(table(dsn1[,cycle_var], dsn1[,arm_var]), stringsAsFactors=FALSE)
names(combo_counts) = c(cycle_var, arm_var, "total")
combo_counts$flag = 1
labs2 = merge(x=labs, y=combo_counts, by=c(cycle_var, arm_var), all.y = TRUE)
if(any(is.na(labs2$bar_lab_opt))){
labs2[is.na(labs2$bar_lab_opt),]$bar_lab_opt = 0
}
if(label %in% c(4,5)){
labs2[labs2$bar_lab_opt!=0,]$bar_lab_opt=round(labs2[labs2$bar_lab_opt!=0,]$bar_lab_opt/labs2[labs2$bar_lab_opt!=0,]$total,digits=2)*100
}
dsn2 = merge(dsn1, labs2, by = c(cycle_var, arm_var))
# -- Only one label per cycle/arm combination
high = by(dsn2, INDICES = list(dsn2[,cycle_var], dsn2[,arm_var]), FUN = utils::tail, n=1)
high2 = do.call("rbind", as.list(high))
row_keeps = as.integer(rownames(high2))
dsn2[!(1:NROW(dsn2) %in% row_keeps),]$bar_lab_opt = NA
# ----------------------------------------------------------------
# -- Create labels for the cycle_var facets
# ----------------------------------------------------------------
dsn2$cycle_var_v_plot=factor(ifelse(dsn2[,cycle_var]=="Maximum*",
"Maximum*",
ifelse(dsn2[,cycle_var]=="Adjusted**", "Adjusted**",
paste0(cycle_var," ", dsn2[,cycle_var]))),
levels=c(paste0(cycle_var," ", min(dsn0[,cycle_var]):max(dsn0[,cycle_var])),
"Maximum*",
"Adjusted**"))
dsn2$lab = group_i$lab[j]
dsn2$item = item
colnames(dsn2)[4] = "grade"
# -- Append
plot_combined0 = rbind.data.frame(plot_combined0, dsn2, stringsAsFactors=FALSE)
}
plot_combined0$grade_item = ifelse(plot_combined0$lab!="Composite", plot_combined0$grade, NA)
plot_combined0$grade_comp = ifelse(plot_combined0$lab=="Composite", plot_combined0$grade, NA)
plot_combined0$item_lab = factor(plot_combined0$lab, levels=unique(plot_combined0$lab))
# ----------------------------------------------------------------
# -- Color palette options
# ----------------------------------------------------------------
if(colors==1){
# -- Default
item_col0 = "white"
item_col1 = "#90B0D9"
item_col2 = "#4D7EBF"
item_col3 = "#13478C"
item_col4 = "#142233"
comp_col0 = "white"
comp_col1 = "#E5BFC6"
comp_col2 = "#D9576E"
comp_col3 = "#99293D"
colset1 = c(
"0" = item_col0,
"1" = item_col1,
"2" = item_col2,
"3" = item_col3,
"4" = item_col4
)
colset2 = c(
"0" = comp_col0,
"1" = comp_col1,
"2" = comp_col2,
"3" = comp_col3
)
} else if(colors==2){
# -- Qualitative (color-blind friendly)
item_col0 = "white"
item_col1 = "#0571B0"
item_col2 = "#92C5DE"
item_col3 = "#F4A582"
item_col4 = "#CA0020"
comp_col0 = "white"
comp_col1 = "#A6DBA0"
comp_col2 = "#C2A5CF"
comp_col3 = "#7B3294"
colset1 = c(
"0" = item_col0,
"1" = item_col1,
"2" = item_col2,
"3" = item_col3,
"4" = item_col4
)
colset2 = c(
"0" = comp_col0,
"1" = comp_col1,
"2" = comp_col2,
"3" = comp_col3
)
} else if(colors==3){
# -- Black and white
item_col0 = "white"
item_col1 = "#E6E6E6"
item_col2 = "#BDBDBD"
item_col3 = "#636363"
item_col4 = "#000000"
comp_col0 = "white"
comp_col1 = "#BDBDBD"
comp_col2 = "#636363"
comp_col3 = "#000000"
colset1 = c(
"0" = item_col0,
"1" = item_col1,
"2" = item_col2,
"3" = item_col3,
"4" = item_col4
)
colset2 = c(
"0" = comp_col0,
"1" = comp_col1,
"2" = comp_col2,
"3" = comp_col3
)
}
## -- Line color adjustments
colset1_line = colset1
colset1_line[1] = "grey"
colset2_line = colset2
colset2_line[1] = "grey"
## -- Optional title
title_i = refset[refset$group_rank==i,]$group_lab[1]
plot_combined0$grade_item = ifelse(plot_combined0$lab!="Composite", plot_combined0$grade, NA)
plot_combined0$grade_comp = ifelse(plot_combined0$lab=="Composite", plot_combined0$grade, NA)
plot_combined0$item_lab = factor(plot_combined0$lab, levels=unique(plot_combined0$lab))
# -- Legend components
facets = factor(unique(plot_combined0$lab), levels = c("Frequency", "Severity", "Interference", "Composite"))
foot_note = ""
ptsize1="15pt"
ptsize2="10pt"
for (k in facets){
if(k=="Frequency"){
freq0 = paste0("<span style='font-size:",ptsize1,"'>\U23CD </span>Never / ")
freq1 = paste0("<span style='font-size:",ptsize2,";color:", item_col1, ";'>\U25A0</span> Rarely / ")
freq2 = paste0("<span style='font-size:",ptsize2,";color:", item_col2, ";'>\U25A0</span> Occasionally / ")
freq3 = paste0("<span style='font-size:",ptsize2,";color:", item_col3, ";'>\U25A0</span> Frequently / ")
freq4 = paste0("<span style='font-size:",ptsize2,";color:", item_col4, ";'>\U25A0</span> Almost constantly")
foot_note = paste0(foot_note, "**Frequency:** ", freq0, freq1, freq2, freq3, freq4, "<br>")
} else if(k=="Severity"){
sev0 = paste0("<span style='font-size:",ptsize1,";'>\U23CD </span>None / ")
sev1 = paste0("<span style='font-size:",ptsize2,";color:", item_col1, "'>\U25A0</span> Mild / ")
sev2 = paste0("<span style='font-size:",ptsize2,";color:", item_col2, ";'>\U25A0</span> Moderate / ")
sev3 = paste0("<span style='font-size:",ptsize2,";color:", item_col3, ";'>\U25A0</span> Severe / ")
sev4 = paste0("<span style='font-size:",ptsize2,";color:", item_col4, ";'>\U25A0</span> Very severe")
foot_note = paste0(foot_note, "**Severity:** ", sev0, sev1, sev2, sev3, sev4, "<br>")
} else if(k=="Interference"){
int0 = paste0("<span style='font-size:",ptsize1,";'>\U23CD </span>Not at all / ")
int1 = paste0("<span style='font-size:",ptsize2,";color:", item_col1, ";'>\U25A0</span> A little bit / ")
int2 = paste0("<span style='font-size:",ptsize2,";color:", item_col2, ";'>\U25A0</span> Somewhat / ")
int3 = paste0("<span style='font-size:",ptsize2,";color:", item_col3, ";'>\U25A0</span> Quite a bit / ")
int4 = paste0("<span style='font-size:",ptsize2,";color:", item_col4, ";'>\U25A0</span> Very much")
# ================================================================
# ==== ACCOMMODATION FOR 27A HAIR LOSs AMOUNT =====================
# ================================================================
if(refset[refset$group_rank==i,]$group_lab[1]=="Hair Loss"){
foot_note = paste0(foot_note, "**Amount:** ", int0, int1, int2, int3, int4, "<br>")
} else {
foot_note = paste0(foot_note, "**Interference:** ", int0, int1, int2, int3, int4, "<br>")
}
# ================================================================
# ================================================================
# ================================================================
} else if(k=="Composite"){
comp0 = paste0("<span style='font-size:",ptsize1,";'>\U23CD </span>0 / ")
comp1 = paste0("<span style='font-size:",ptsize2,";color:", comp_col1 ,";'>\U25A0</span> 1 / ")
comp2 = paste0("<span style='font-size:",ptsize2,";color:", comp_col2 ,";'>\U25A0</span> 2 / ")
comp3 = paste0("<span style='font-size:",ptsize2,";color:", comp_col3 ,";'>\U25A0</span> 3 ")
foot_note = paste0(foot_note, "**Composite Grade:** ", comp0, comp1, comp2, comp3, "<br>")
}
}
foot1 = "\\*Maximum score or grade reported post-baseline per patient.<br>"
foot2a = "\\*\\*Maximum score or grade reported post-baseline per patient when"
if(summary_only == TRUE){
foot2b = " including only scores<br> that were worse than the patient's baseline score."
} else {
foot2b = " including only scores that were worse than the patient's baseline score."
}
# -- Label footnote addition
label_foot = ""
if(label %in% c(2,4)){
foot_grade = 1
}
if(label %in% c(3,5)){
foot_grade = 3
}
if(label %in% c(2,3)){
foot_symbol = "(n)"
foot_type = "number"
y_scale_lab = c("0","25","50","75","100", "n ")
}
if(label %in% c(4,5)){
foot_symbol = "(%)"
foot_type = "percent"
y_scale_lab = c("0","25","50","75","100", "% ")
}
if(label==1){
label_foot = "Column labels (n) show the number of subjects with an observed symptom score or grade.<br>"
y_scale_lab = c("0","25","50","75","100", "n ")
} else if (label %in% c(2, 3, 4, 5)){
label_foot = paste0("Column labels ", foot_symbol, " show the ", foot_type,
" of subjects with symptom score or grade ",
foot_grade," or greater.<br>")
}
if(cycles_only==TRUE){
foot_note = paste0(foot_note, label_foot)
} else if(cycles_only==FALSE){
foot_note = paste0(foot_note, label_foot, foot1, foot2a, foot2b)
}
## ----------------------------------------------------------------
## -- Conditional ggplot object combinations
## ----------------------------------------------------------------
# -- Restrict the cycles to be plotted
if(!is.na(plot_limit)){
plot_combined0$cycle_plot_lim = as.integer(gsub("[^0-9]", "", plot_combined0[,cycle_var]))
plot_combined0=plot_combined0[(!is.na(plot_combined0$cycle_plot_lim)&plot_combined0$cycle_plot_lim<=plot_limit)|plot_combined0[,cycle_var] %in% c("Adjusted**","Maximum*"),]
}
# -- Only show summary measures
if(summary_only==TRUE){
plot_combined0 = plot_combined0[plot_combined0[,cycle_var] %in% c("Adjusted**", "Maximum*"),]
}
# -- Do not show summary measures
if(cycles_only==TRUE){
plot_combined0 = plot_combined0[!(plot_combined0[,cycle_var] %in% c("Adjusted**", "Maximum*")),]
}
names(plot_combined0)[names(plot_combined0) == arm_var] = "arm"
if(arm_var=="overall_"){plot_combined0$arm=""}
# ================================================================
# ==== ACCOMMODATION FOR 27A HAIR LOSs AMOUNT ====================
# ================================================================
if(refset[refset$group_rank==i,]$group_lab[1]=="Hair Loss"){
levels(plot_combined0$item_lab) = c("Amount", "Composite", "Interference")
plot_combined0[plot_combined0$lab=="Interference",]$item_lab = "Amount"
}
# ================================================================
# ================================================================
# ================================================================
# ----------------------------------------------------------------
# -- No labels requested
# ----------------------------------------------------------------
if(label==0){
# ----------------------------------------------------------------
# --
# ----------------------------------------------------------------
if("Composite" %in% unique(plot_combined0$lab) &
sum(c("Frequency", "Severity", "Interference", "Amount") %in% unique(plot_combined0$lab))>0){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(arm)) +
## -- Individual items
ggplot2::scale_fill_manual(values = colset1,
limits = names(colset1),
guide = ggplot2::guide_legend(order = 2)) +
ggplot2::scale_color_manual(values = colset1_line) +
ggplot2::geom_bar(data = plot_combined0[!is.na(plot_combined0$grade_item),],
ggplot2::aes(fill = as.factor(grade_item), color=as.factor(grade_item)), position = "fill", width = .8) +
ggnewscale::new_scale(new_aes = "fill") +
ggnewscale::new_scale(new_aes = "color") +
# ## -- Composite items
ggplot2::scale_fill_manual(values = colset2,
limits = names(colset2),
guide = ggplot2::guide_legend(order = 3)) +
ggplot2::scale_color_manual(values = colset2_line) +
ggplot2::geom_bar(data = plot_combined0[!is.na(plot_combined0$grade_comp),],
ggplot2::aes(fill = as.factor(grade_comp), color=as.factor(grade_comp)), position = "fill", width = .8) +
ggplot2:: scale_y_continuous(labels = c("0","25","50","75","100"),
breaks = c(0, .25, .5, .75, 1),
limits = c(0, 1.01)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
# ----------------------------------------------------------------
# -- Individual items only
# ----------------------------------------------------------------
else if(!("Composite" %in% unique(plot_combined0$lab))){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(arm)) +
## -- Individual items
ggplot2::scale_fill_manual(values = colset1,
limits = names(colset1),
guide = ggplot2::guide_legend(order = 2)) +
ggplot2::scale_color_manual(values = colset1_line) +
ggplot2::geom_bar(ggplot2::aes(fill = as.factor(grade_item), color=as.factor(grade_item)), position = "fill", width = .8) +
ggplot2::scale_y_continuous(labels = c("0","25","50","75","100"),
breaks = c(0, .25, .5, .75, 1),
limits = c(0, 1.01)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
# ----------------------------------------------------------------
# -- Composite items only
# ----------------------------------------------------------------
else if("Composite" %in% unique(plot_combined0$lab)&
sum(c("Frequency", "Severity", "Interference", "Amount") %in% unique(plot_combined0$lab))==0){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(x=arm)) +
## -- Composite items
ggplot2::scale_fill_manual(values = colset2,
limits = names(colset2),
guide = ggplot2::guide_legend(order = 3)) +
ggplot2::scale_color_manual(values = colset2_line) +
ggplot2::geom_bar(ggplot2::aes(fill = as.factor(grade_comp), color=as.factor(grade_comp)), position = "fill", width = .8) +
ggplot2::scale_y_continuous(labels = c("0","25","50","75","100"),
breaks = c(0, .25, .5, .75, 1),
limits = c(0, 1.01)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
}
# ----------------------------------------------------------------
# -- Labels requested
# ----------------------------------------------------------------
else if(label!=0){
# ----------------------------------------------------------------
# -- Individual and composite items
# ----------------------------------------------------------------
if("Composite" %in% unique(plot_combined0$lab) &
sum(c("Frequency", "Severity", "Interference", "Amount") %in% unique(plot_combined0$lab))>0){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(x=arm)) +
## -- Individual items
ggplot2::scale_fill_manual(values = colset1,
limits = names(colset1),
guide = ggplot2::guide_legend(order = 2)) +
ggplot2::scale_color_manual(values = colset1_line) +
ggplot2::geom_bar(data = plot_combined0[!is.na(plot_combined0$grade_item),],
ggplot2::aes(fill = as.factor(grade_item), color=as.factor(grade_item)), position = "fill", width = .8) +
ggnewscale::new_scale(new_aes = "fill") +
ggnewscale::new_scale(new_aes = "color") +
## -- Composite items
ggplot2::scale_fill_manual(values = colset2,
limits = names(colset2),
guide = ggplot2::guide_legend(order = 3)) +
ggplot2::scale_color_manual(values = colset2_line) +
ggplot2::geom_bar(data = plot_combined0[!is.na(plot_combined0$grade_comp),],
ggplot2::aes(fill = as.factor(grade_comp), color=as.factor(grade_comp)), position = "fill", width = .8) +
## -- Customize
ggplot2::geom_hline(yintercept=1.04, linetype="solid", color = "darkgrey") +
ggplot2::geom_text(ggplot2::aes(y= 1.13, label=bar_lab_opt), size=3, na.rm=TRUE) +
ggplot2::scale_y_continuous(labels = y_scale_lab,
breaks = c(0, .25, .5, .75, 1, 1.13),
limits = c(0, 1.14)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
# ----------------------------------------------------------------
# -- Individual items only
# ----------------------------------------------------------------
else if(!("Composite" %in% unique(plot_combined0$lab))){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(x=arm)) +
## -- Individual items
ggplot2::scale_fill_manual(values = colset1,
limits = names(colset1),
guide = ggplot2::guide_legend(order = 2)) +
ggplot2::scale_color_manual(values = colset1_line) +
ggplot2::geom_bar(ggplot2::aes(fill = as.factor(grade_item), color=as.factor(grade_item)), position = "fill", width = .8) +
## -- Customize
ggplot2::geom_hline(yintercept=1.04, linetype="solid", color = "darkgrey") +
ggplot2::geom_text(ggplot2::aes(y= 1.13, label=bar_lab_opt), size=3, na.rm=TRUE) +
ggplot2::scale_y_continuous(labels = y_scale_lab,
breaks = c(0, .25, .5, .75, 1, 1.13),
limits = c(0, 1.14)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
# ----------------------------------------------------------------
# -- Composite items only
# ----------------------------------------------------------------
else if("Composite" %in% unique(plot_combined0$lab)&
sum(c("Frequency", "Severity", "Interference", "Amount") %in% unique(plot_combined0$lab))==0){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(x=arm)) +
## -- Composite items
ggplot2::scale_fill_manual(values = colset2,
limits = names(colset2),
guide = ggplot2::guide_legend(order = 3)) +
ggplot2::scale_color_manual(values = colset2_line) +
ggplot2::geom_bar(ggplot2::aes(fill = as.factor(grade_comp), color=as.factor(grade_comp)), position = "fill", width = .8) +
## -- Customize
ggplot2::geom_hline(yintercept=1.04, linetype="solid", color = "darkgrey") +
ggplot2::geom_text(ggplot2::aes(y= 1.13, label=bar_lab_opt), size=3, na.rm=TRUE) +
ggplot2::scale_y_continuous(labels = y_scale_lab,
breaks = c(0, .25, .5, .75, 1, 1.13),
limits = c(0, 1.14)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
}
list_out[[i]] = list()
list_out[[i]][[1]] = refset[refset$group_rank==i,]$group_lab[1]
list_out[[i]][[2]] = figure_i
if(plot_data == TRUE){
list_out[[i]][[3]] = plot_combined0[, !(names(plot_combined0) %in% "null")]
}
}
## -- Reference table for user to view the indexing of PRO-CTCAE item groups withing the list output
for (i in 1:length(list_out)){
if (i==1) {fig_tab = data.frame()}
list_deat = data.frame(PRO_AE = list_out[[i]][[1]], item_index=i)
fig_tab = rbind(fig_tab, list_deat)
}
## -- Reference table
print(fig_tab)
## -- Object return
invisible(list_out)
}
blakelanglais/ProAE documentation built on Dec. 19, 2021, 9:52 a.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions toxFigures
Documented in toxFigures
#' Create PRO-CTCAE severity frequency distribution figures for individual
#' survey items and composite scores
#'
#'
#' Data format should be in 'long' format, where each PRO-CTCAE item is a
#' variable/column.
#'
#' @param dsn A data.frame object with PRO-CTCAE data
#' @param id_var A character string.Name of ID variable differentiating each
#' PRO-CTCAE survey/participant entered as a quoted string.
#' @param cycle_var A character string. Name of variable differentiating one
#' longitudinal/repeated. PRO-CTCAE survey from another, within an individual
#' ID.
#' @param baseline_val A number indicating the expected baseline cycle/time
#' point.
#' @param arm_var A character string. Name of arm variable differentiating
#' treatment groups. Must be character or factor class. Overall AUC
#' will be reported if no arm/grouping variable is provided. Defaults to
#' \code{NA}.
#' @param plot_limit A number. Limit the number of cycles to be plotted up to
#' and including a given cycle number. All available cycle time points are
#' plotted if no cycle number is provided. Defaults to \code{NA}.
#' @param colors A number. Specify the coloring scheme of symptom grades within
#' frequency bars. Options include: 1 = Blue and red color shading, 2 =
#' qualitative color shades (color blind friendly), 3 = black and white.
#' Defaults to 1.
#' @param label A number. Label frequency bars with sample size (n) or percent
#' shown on the y-axis. Label options include: \code{1} = sample size (n)
#' within each cycle (symptom grade 0 or higher), \code{2} = sample size (n)
#' within each cycle with present symptoms (symptom grade > 0), \code{3} =
#' sample size (n) within each cycle with severe symptoms (symptom grade >=
#' 3), \code{4} = percent of subjects within each cycle with present
#' symptoms (symptom grade > 0), \code{5} = percent of subjects within each
#' cycle with severe symptoms (symptom grade >= 3). No labels will be applied
#' if not specified. Defaults to \code{NA}.
#' @param summary_only Logical. Only display the summary measures in figures /
#' Suppress the individual time points from plotting. Defaults to
#' \code{FALSE}.
#' @param cycles_only Logical. Only display the longitudinal time points in
#' figures / Suppress the summary measures from plotting. Defaults to
#' \code{FALSE}.
#' @param x_label A character string. Label for the x axis of the plot. Defaults
#' to \code{"Randomized Treatment Assignment"} if \code{arm_var} is specified,
#' defaults to \code{"Overall"} if not \code{arm_var} is specified.
#' @param x_lab_angle A integer between 0 and 360. Allows the user to rotate the
#' x axis labels in order to fit long arm names (0 or 45 recommended).
#' Defaults to \code{0}.
#' @param x_lab_vjust A number. A ggplot2 object option. Allows the user to
#' vertically adjusts the x axis labels in order to fit arm names. Defaults to
#' \code{1}.
#' @param x_lab_hjust A number. A ggplot2 object option. Allows the user to
#' horizontally adjusts the x axis labels in order to fit arm names. Defaults
#' to \code{0}.
#' @param plot_data Logical. Return the data used to construct plots as element
#' of the returned object. Defaults to \code{FALSE}.
#' @return A list object. The returned object is a (k X 2) or (k x 3) nested
#' list. Where k is the number of PRO-CTCAE item groups (e.g. pain, fatigue,
#' nausea); list[[1 ... i ... k]]. For each list item there are 2 or 3
#' elements. The 1st element of each list item is the name of the PRO-CTCAE
#' item group returned as a string. The 2nd element is the PRO-CTCAE figure as
#' a ggplot object. The 3rd (and optional) element is the data used to
#' construct the ggplot figure, available via \code{plot_data}.
#' @importFrom magrittr %>%
#' @examples
#' fig_acute = toxFigures(dsn = ProAE::tox_acute[c(1:300, 1101:1400),],
#' cycle_var = "Cycle",
#' baseline_val = 1,
#' arm_var = "arm",
#' id_var = "id",
#' label = 0,
#' x_lab_angle = -45,
#' x_lab_vjust = .3,
#' x_lab_hjust = .2,
#' colors = 2)
#' fig_acute[[1]]
#' @export
toxFigures = function(dsn,
id_var,
cycle_var,
baseline_val,
arm_var=NA,
plot_limit=NA,
colors=1,
label=0,
summary_only=FALSE,
cycles_only=FALSE,
x_lab_angle=0,
x_lab_vjust=1,
x_lab_hjust=0,
x_label = "Randomized Treatment Assignment",
plot_data=FALSE){
# ----------------------------------------------------------------
# -- Checks 1/2
# ----------------------------------------------------------------
## -- Assign binding for data.frame variables used within ggplot2 objects as global variables
grade_comp = NULL
grade_item = NULL
arm = NULL
bar_lab_opt = NULL
## -- Required parameters
if(exists("dsn")){
if(!is.data.frame(dsn)){
stop("param dsn must be provided as a data.frame object")
}
} else {stop("param dsn not provided")}
if(exists("id_var")){
if(!is.character(id_var)){
stop("param id_var must be provided as a character string")
} else if (!(id_var %in% colnames(dsn))){
stop(paste0("param id_var (", id_var, ") not found as a variable in dsn (", deparse(substitute(dsn)), ")"))
}
} else {stop("param id_var not provided")}
if(exists("cycle_var")){
if(!is.character(cycle_var)){
stop("param cycle_var must be provided as a character string")
} else if (!(cycle_var %in% colnames(dsn))){
stop(paste0("param cycle_var (", cycle_var, ") not found as a variable in dsn (", deparse(substitute(dsn)), ")"))
}
} else {stop("param cycle_var not provided")}
if(exists("baseline_val")){
if(!(is.numeric(baseline_val) | is.integer(baseline_val) | length(baseline_val)==1)){
stop("param baseline_val must be provided as a single number, of class numeric or integer")
}
} else {stop("param baseline_val not provided")}
## -- Check for any duplicate individuals within cycles
if(any(duplicated(dsn[,c(id_var, cycle_var)]))){
stop(paste0("Duplicate observations were found within id_var and cycle_var combinations (", id_var, " and ", cycle_var, ")"))
}
# ----------------------------------------------------------------
# -- Defaults
# ----------------------------------------------------------------
if(is.na(arm_var)){
arm_var = "overall_"
if(x_label=="Randomized Treatment Assignment"){
x_label = "Overall"
}
}
if(summary_only==TRUE & cycles_only==TRUE){
summary_only = TRUE
}
## -------------------------------------------------------------
## --- Reference data sets
## -------------------------------------------------------------
proctcae_vars[, ] = lapply(proctcae_vars[, ], as.character)
# ================================================================
# ==== ACCOMMODATION FOR 27A HAIR LOSS AMOUNT ====================
# ================================================================
## -- Item 27 asks about hair loss and is referenced as an 'amount'
## -- However this item utilizes the Interference response bank.
## -- This is accommodated here by treating it as Interference then
## -- resulting plot is manually labeled 'Amount' BTL - 20AUG2020
proctcae_vars[proctcae_vars$name=="PROCTCAE_27A_SCL",]$short_label = "Hair Loss Interference"
# ================================================================
# ================================================================
# ================================================================
# ----------------------------------------------------------------
# -- Get existing PROCTCAE variables in dsn
# ----------------------------------------------------------------
## - Individual items
dsn_items0 = toupper(names(dsn)[toupper(names(dsn)) %in% proctcae_vars$name])
dsn_items = dsn_items0[! dsn_items0 %in% as.character(proctcae_vars$name[proctcae_vars$fmt %in% c("yn_2_fmt", "yn_3_fmt", "yn_4_fmt")])]
## - Composites
proctcae_vars_comp0 = proctcae_vars[,-1] %>% dplyr::mutate_if(is.factor, as.character)
# proctcae_vars_comp0 = proctcae_vars[,-1]
proctcae_vars_comp0 = proctcae_vars_comp0[!proctcae_vars_comp0$name %in% as.character(proctcae_vars_comp0$name[proctcae_vars_comp0$fmt %in% c("yn_2_fmt",
"yn_3_fmt",
"yn_4_fmt")]),]
proctcae_vars_comp = c()
proctcae_vars_comp$name = paste0(substr(proctcae_vars_comp0$name, 1, nchar(proctcae_vars_comp0$name)-5), "_COMP")
proctcae_vars_comp$short_label = sub(proctcae_vars_comp0$short_label, pattern = " [[:alpha:]]*$", replacement = "")
proctcae_vars_comp = unique(data.frame(proctcae_vars_comp, stringsAsFactors=FALSE))
dsn_comps = toupper(names(dsn)[toupper(names(dsn)) %in% proctcae_vars_comp$name])
# ----------------------------------------------------------------
# -- Checks 2/2
# ----------------------------------------------------------------
## -- Confirm there are available PRO-CTCAE variables within dsn with expected naming convention
if(identical(dsn_items, character(0)) & identical(dsn_comps, character(0))){
stop(paste0("No PRO-CTCAE variables found within dsn (", deparse(substitute(dsn)), ") meeting the expected naming convention"))
}
# ----------------------------------------------------------------
# -- Cluster available items and composites together
# ----------------------------------------------------------------
## -- Available PRO-CTCAE items and composites available in dsn
refset = data.frame(name = c(dsn_items, dsn_comps))
refset$number = as.integer(gsub("[^0-9]", "", refset$name))
refset$rank = ifelse(grepl("COMP", refset$name), 4,
ifelse(grepl("A_", refset$name), 1,
ifelse(grepl("B_", refset$name), 2, 3)))
refset = refset[order(refset$number,refset$rank),]
refset = merge(x=refset,
y= data.frame(number = unique(refset$number),
group_rank = 1:length(unique(refset$number)),
stringsAsFactors=FALSE),
by="number", all.x=TRUE)
## -- All non-indicator PRO-CTCAE with possible composites
reflabs0 = data.frame(name=proctcae_vars$name,
short_label = proctcae_vars$short_label,
lab = unlist(lapply(strsplit(proctcae_vars$short_label, split=" "), 1, FUN=utils::tail)),
stringsAsFactors=FALSE)
reflabs0$group_lab = ifelse(reflabs0$lab=="Severity", trimws(gsub("Severity","", reflabs0$short_label)),
ifelse(reflabs0$lab=="Frequency", trimws(gsub("Frequency","", reflabs0$short_label)),
trimws(gsub("Interference","", reflabs0$short_label))))
reflabs0 = reflabs0[!grepl("_IND", reflabs0$name),]
reflabs0$comp_name = paste0(substr(reflabs0$name,1,nchar(reflabs0$name)-5),"_COMP")
reflabs1 = unique(reflabs0[c("group_lab", 'comp_name')])
names(reflabs1) = c("group_lab","name")
reflabs1$lab = "Composite"
reflabs = rbind.data.frame(reflabs0[c("name", "group_lab", "lab")],
reflabs1[c("name", "group_lab", "lab")],
stringsAsFactors=FALSE)
refset = merge(x=refset,
y=reflabs,
by= "name", all.x=TRUE)
refset = refset[order(refset$number,refset$rank),]
# ----------------------------------------------------------------
# -- For each available PRO-CTCAE item grouping [i], process
# ----------------------------------------------------------------
for (i in 1:max(refset$group_rank)){
if(i==1){list_out = vector(mode='list', max(refset$group_rank))}
# ----------------------------------------------------------------
# -- For each PRO-CTCAE item within the grouping [j], process
# ----------------------------------------------------------------
group_i = refset[refset$group_rank==i,]
plot_combined0 = data.frame()
for (j in 1:NROW(group_i)){
item = as.character(group_i$name[j])
if(arm_var != "overall_"){
dsn0 = stats::na.omit(dsn[,c(id_var, cycle_var, arm_var, item)])
} else if (arm_var == "overall_"){
dsn0 = stats::na.omit(dsn[,c(id_var, cycle_var, item)])
dsn0$overall_ = "Overall"
}
# ----------------------------------------------------------------
# -- Construct summary measures
# ----------------------------------------------------------------
## -- Maximum grade post baseline
max_post0 = stats::aggregate(dsn0[dsn0[,cycle_var]>baseline_val, item],
by = list(dsn0[dsn0[,cycle_var]>baseline_val,id_var]),
FUN=max)
colnames(max_post0) = c(id_var, item)
max_post0[,cycle_var] = "Maximum*"
max_post1 = unique(merge(x=max_post0, y=dsn0[,c(id_var, arm_var)], by=id_var, all.x = TRUE))
## -- Baseline adjusted
base_adj0 = dsn0[dsn0[,cycle_var]==baseline_val, c(id_var, item)]
colnames(base_adj0)[2] = "base_val"
base_adj1 = merge(x=dsn0, y=base_adj0, by=id_var, all.x=TRUE)
base_adj2 = stats::aggregate(base_adj1[base_adj1[,cycle_var]>baseline_val, item],
by = list(base_adj1[base_adj1[,cycle_var]>baseline_val,id_var]),
FUN=max)
colnames(base_adj2) = c(id_var, "max_post_bl")
base_adj2 = merge(x=base_adj1, y=unique(base_adj2), by=id_var, all.x=TRUE)
base_adj2$bl_adjusted = ifelse(!is.na(base_adj2$max_post_bl) & base_adj2$base_val >= base_adj2$max_post_bl,
0, base_adj2$max_post_bl)
base_adj3 = unique(base_adj2[!is.na(base_adj2$bl_adjusted),c(id_var, arm_var, "bl_adjusted")])
base_adj3[,cycle_var] = "Adjusted**"
colnames(base_adj3)[colnames(base_adj3) == "bl_adjusted"] = item
dsn1 = rbind.data.frame(dsn0, max_post1, base_adj3)
# ----------------------------------------------------------------
# -- Create labels for the bars
# ----------------------------------------------------------------
if(label==0){
labs = dsn1[,c(cycle_var, arm_var)]
labs$bar_lab_opt = NA
} else if(label==1){
labs = stats::aggregate(dsn1[dsn1[,item]>=0,item],
by=list(dsn1[dsn1[,item]>=0,cycle_var],
dsn1[dsn1[,item]>=0,arm_var]),
FUN=length)
} else if(label %in% c(2,4)){
labs = stats::aggregate(dsn1[dsn1[,item]>0,item],
by=list(dsn1[dsn1[,item]>0,cycle_var],
dsn1[dsn1[,item]>0,arm_var]),
FUN=length)
} else if(label %in% c(3,5)){
labs = stats::aggregate(dsn1[dsn1[,item]>=3,item],
by=list(dsn1[dsn1[,item]>=3,cycle_var],
dsn1[dsn1[,item]>=3,arm_var]),
FUN=length)
}
names(labs) = c(cycle_var, arm_var, "bar_lab_opt")
# -- Force zero counts
combo_counts = data.frame(table(dsn1[,cycle_var], dsn1[,arm_var]), stringsAsFactors=FALSE)
names(combo_counts) = c(cycle_var, arm_var, "total")
combo_counts$flag = 1
labs2 = merge(x=labs, y=combo_counts, by=c(cycle_var, arm_var), all.y = TRUE)
if(any(is.na(labs2$bar_lab_opt))){
labs2[is.na(labs2$bar_lab_opt),]$bar_lab_opt = 0
}
if(label %in% c(4,5)){
labs2[labs2$bar_lab_opt!=0,]$bar_lab_opt=round(labs2[labs2$bar_lab_opt!=0,]$bar_lab_opt/labs2[labs2$bar_lab_opt!=0,]$total,digits=2)*100
}
dsn2 = merge(dsn1, labs2, by = c(cycle_var, arm_var))
# -- Only one label per cycle/arm combination
high = by(dsn2, INDICES = list(dsn2[,cycle_var], dsn2[,arm_var]), FUN = utils::tail, n=1)
high2 = do.call("rbind", as.list(high))
row_keeps = as.integer(rownames(high2))
dsn2[!(1:NROW(dsn2) %in% row_keeps),]$bar_lab_opt = NA
# ----------------------------------------------------------------
# -- Create labels for the cycle_var facets
# ----------------------------------------------------------------
dsn2$cycle_var_v_plot=factor(ifelse(dsn2[,cycle_var]=="Maximum*",
"Maximum*",
ifelse(dsn2[,cycle_var]=="Adjusted**", "Adjusted**",
paste0(cycle_var," ", dsn2[,cycle_var]))),
levels=c(paste0(cycle_var," ", min(dsn0[,cycle_var]):max(dsn0[,cycle_var])),
"Maximum*",
"Adjusted**"))
dsn2$lab = group_i$lab[j]
dsn2$item = item
colnames(dsn2)[4] = "grade"
# -- Append
plot_combined0 = rbind.data.frame(plot_combined0, dsn2, stringsAsFactors=FALSE)
}
plot_combined0$grade_item = ifelse(plot_combined0$lab!="Composite", plot_combined0$grade, NA)
plot_combined0$grade_comp = ifelse(plot_combined0$lab=="Composite", plot_combined0$grade, NA)
plot_combined0$item_lab = factor(plot_combined0$lab, levels=unique(plot_combined0$lab))
# ----------------------------------------------------------------
# -- Color palette options
# ----------------------------------------------------------------
if(colors==1){
# -- Default
item_col0 = "white"
item_col1 = "#90B0D9"
item_col2 = "#4D7EBF"
item_col3 = "#13478C"
item_col4 = "#142233"
comp_col0 = "white"
comp_col1 = "#E5BFC6"
comp_col2 = "#D9576E"
comp_col3 = "#99293D"
colset1 = c(
"0" = item_col0,
"1" = item_col1,
"2" = item_col2,
"3" = item_col3,
"4" = item_col4
)
colset2 = c(
"0" = comp_col0,
"1" = comp_col1,
"2" = comp_col2,
"3" = comp_col3
)
} else if(colors==2){
# -- Qualitative (color-blind friendly)
item_col0 = "white"
item_col1 = "#0571B0"
item_col2 = "#92C5DE"
item_col3 = "#F4A582"
item_col4 = "#CA0020"
comp_col0 = "white"
comp_col1 = "#A6DBA0"
comp_col2 = "#C2A5CF"
comp_col3 = "#7B3294"
colset1 = c(
"0" = item_col0,
"1" = item_col1,
"2" = item_col2,
"3" = item_col3,
"4" = item_col4
)
colset2 = c(
"0" = comp_col0,
"1" = comp_col1,
"2" = comp_col2,
"3" = comp_col3
)
} else if(colors==3){
# -- Black and white
item_col0 = "white"
item_col1 = "#E6E6E6"
item_col2 = "#BDBDBD"
item_col3 = "#636363"
item_col4 = "#000000"
comp_col0 = "white"
comp_col1 = "#BDBDBD"
comp_col2 = "#636363"
comp_col3 = "#000000"
colset1 = c(
"0" = item_col0,
"1" = item_col1,
"2" = item_col2,
"3" = item_col3,
"4" = item_col4
)
colset2 = c(
"0" = comp_col0,
"1" = comp_col1,
"2" = comp_col2,
"3" = comp_col3
)
}
## -- Line color adjustments
colset1_line = colset1
colset1_line[1] = "grey"
colset2_line = colset2
colset2_line[1] = "grey"
## -- Optional title
title_i = refset[refset$group_rank==i,]$group_lab[1]
plot_combined0$grade_item = ifelse(plot_combined0$lab!="Composite", plot_combined0$grade, NA)
plot_combined0$grade_comp = ifelse(plot_combined0$lab=="Composite", plot_combined0$grade, NA)
plot_combined0$item_lab = factor(plot_combined0$lab, levels=unique(plot_combined0$lab))
# -- Legend components
facets = factor(unique(plot_combined0$lab), levels = c("Frequency", "Severity", "Interference", "Composite"))
foot_note = ""
ptsize1="15pt"
ptsize2="10pt"
for (k in facets){
if(k=="Frequency"){
freq0 = paste0("<span style='font-size:",ptsize1,"'>\U23CD </span>Never / ")
freq1 = paste0("<span style='font-size:",ptsize2,";color:", item_col1, ";'>\U25A0</span> Rarely / ")
freq2 = paste0("<span style='font-size:",ptsize2,";color:", item_col2, ";'>\U25A0</span> Occasionally / ")
freq3 = paste0("<span style='font-size:",ptsize2,";color:", item_col3, ";'>\U25A0</span> Frequently / ")
freq4 = paste0("<span style='font-size:",ptsize2,";color:", item_col4, ";'>\U25A0</span> Almost constantly")
foot_note = paste0(foot_note, "**Frequency:** ", freq0, freq1, freq2, freq3, freq4, "<br>")
} else if(k=="Severity"){
sev0 = paste0("<span style='font-size:",ptsize1,";'>\U23CD </span>None / ")
sev1 = paste0("<span style='font-size:",ptsize2,";color:", item_col1, "'>\U25A0</span> Mild / ")
sev2 = paste0("<span style='font-size:",ptsize2,";color:", item_col2, ";'>\U25A0</span> Moderate / ")
sev3 = paste0("<span style='font-size:",ptsize2,";color:", item_col3, ";'>\U25A0</span> Severe / ")
sev4 = paste0("<span style='font-size:",ptsize2,";color:", item_col4, ";'>\U25A0</span> Very severe")
foot_note = paste0(foot_note, "**Severity:** ", sev0, sev1, sev2, sev3, sev4, "<br>")
} else if(k=="Interference"){
int0 = paste0("<span style='font-size:",ptsize1,";'>\U23CD </span>Not at all / ")
int1 = paste0("<span style='font-size:",ptsize2,";color:", item_col1, ";'>\U25A0</span> A little bit / ")
int2 = paste0("<span style='font-size:",ptsize2,";color:", item_col2, ";'>\U25A0</span> Somewhat / ")
int3 = paste0("<span style='font-size:",ptsize2,";color:", item_col3, ";'>\U25A0</span> Quite a bit / ")
int4 = paste0("<span style='font-size:",ptsize2,";color:", item_col4, ";'>\U25A0</span> Very much")
# ================================================================
# ==== ACCOMMODATION FOR 27A HAIR LOSs AMOUNT =====================
# ================================================================
if(refset[refset$group_rank==i,]$group_lab[1]=="Hair Loss"){
foot_note = paste0(foot_note, "**Amount:** ", int0, int1, int2, int3, int4, "<br>")
} else {
foot_note = paste0(foot_note, "**Interference:** ", int0, int1, int2, int3, int4, "<br>")
}
# ================================================================
# ================================================================
# ================================================================
} else if(k=="Composite"){
comp0 = paste0("<span style='font-size:",ptsize1,";'>\U23CD </span>0 / ")
comp1 = paste0("<span style='font-size:",ptsize2,";color:", comp_col1 ,";'>\U25A0</span> 1 / ")
comp2 = paste0("<span style='font-size:",ptsize2,";color:", comp_col2 ,";'>\U25A0</span> 2 / ")
comp3 = paste0("<span style='font-size:",ptsize2,";color:", comp_col3 ,";'>\U25A0</span> 3 ")
foot_note = paste0(foot_note, "**Composite Grade:** ", comp0, comp1, comp2, comp3, "<br>")
}
}
foot1 = "\\*Maximum score or grade reported post-baseline per patient.<br>"
foot2a = "\\*\\*Maximum score or grade reported post-baseline per patient when"
if(summary_only == TRUE){
foot2b = " including only scores<br> that were worse than the patient's baseline score."
} else {
foot2b = " including only scores that were worse than the patient's baseline score."
}
# -- Label footnote addition
label_foot = ""
if(label %in% c(2,4)){
foot_grade = 1
}
if(label %in% c(3,5)){
foot_grade = 3
}
if(label %in% c(2,3)){
foot_symbol = "(n)"
foot_type = "number"
y_scale_lab = c("0","25","50","75","100", "n ")
}
if(label %in% c(4,5)){
foot_symbol = "(%)"
foot_type = "percent"
y_scale_lab = c("0","25","50","75","100", "% ")
}
if(label==1){
label_foot = "Column labels (n) show the number of subjects with an observed symptom score or grade.<br>"
y_scale_lab = c("0","25","50","75","100", "n ")
} else if (label %in% c(2, 3, 4, 5)){
label_foot = paste0("Column labels ", foot_symbol, " show the ", foot_type,
" of subjects with symptom score or grade ",
foot_grade," or greater.<br>")
}
if(cycles_only==TRUE){
foot_note = paste0(foot_note, label_foot)
} else if(cycles_only==FALSE){
foot_note = paste0(foot_note, label_foot, foot1, foot2a, foot2b)
}
## ----------------------------------------------------------------
## -- Conditional ggplot object combinations
## ----------------------------------------------------------------
# -- Restrict the cycles to be plotted
if(!is.na(plot_limit)){
plot_combined0$cycle_plot_lim = as.integer(gsub("[^0-9]", "", plot_combined0[,cycle_var]))
plot_combined0=plot_combined0[(!is.na(plot_combined0$cycle_plot_lim)&plot_combined0$cycle_plot_lim<=plot_limit)|plot_combined0[,cycle_var] %in% c("Adjusted**","Maximum*"),]
}
# -- Only show summary measures
if(summary_only==TRUE){
plot_combined0 = plot_combined0[plot_combined0[,cycle_var] %in% c("Adjusted**", "Maximum*"),]
}
# -- Do not show summary measures
if(cycles_only==TRUE){
plot_combined0 = plot_combined0[!(plot_combined0[,cycle_var] %in% c("Adjusted**", "Maximum*")),]
}
names(plot_combined0)[names(plot_combined0) == arm_var] = "arm"
if(arm_var=="overall_"){plot_combined0$arm=""}
# ================================================================
# ==== ACCOMMODATION FOR 27A HAIR LOSs AMOUNT ====================
# ================================================================
if(refset[refset$group_rank==i,]$group_lab[1]=="Hair Loss"){
levels(plot_combined0$item_lab) = c("Amount", "Composite", "Interference")
plot_combined0[plot_combined0$lab=="Interference",]$item_lab = "Amount"
}
# ================================================================
# ================================================================
# ================================================================
# ----------------------------------------------------------------
# -- No labels requested
# ----------------------------------------------------------------
if(label==0){
# ----------------------------------------------------------------
# --
# ----------------------------------------------------------------
if("Composite" %in% unique(plot_combined0$lab) &
sum(c("Frequency", "Severity", "Interference", "Amount") %in% unique(plot_combined0$lab))>0){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(arm)) +
## -- Individual items
ggplot2::scale_fill_manual(values = colset1,
limits = names(colset1),
guide = ggplot2::guide_legend(order = 2)) +
ggplot2::scale_color_manual(values = colset1_line) +
ggplot2::geom_bar(data = plot_combined0[!is.na(plot_combined0$grade_item),],
ggplot2::aes(fill = as.factor(grade_item), color=as.factor(grade_item)), position = "fill", width = .8) +
ggnewscale::new_scale(new_aes = "fill") +
ggnewscale::new_scale(new_aes = "color") +
# ## -- Composite items
ggplot2::scale_fill_manual(values = colset2,
limits = names(colset2),
guide = ggplot2::guide_legend(order = 3)) +
ggplot2::scale_color_manual(values = colset2_line) +
ggplot2::geom_bar(data = plot_combined0[!is.na(plot_combined0$grade_comp),],
ggplot2::aes(fill = as.factor(grade_comp), color=as.factor(grade_comp)), position = "fill", width = .8) +
ggplot2:: scale_y_continuous(labels = c("0","25","50","75","100"),
breaks = c(0, .25, .5, .75, 1),
limits = c(0, 1.01)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
# ----------------------------------------------------------------
# -- Individual items only
# ----------------------------------------------------------------
else if(!("Composite" %in% unique(plot_combined0$lab))){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(arm)) +
## -- Individual items
ggplot2::scale_fill_manual(values = colset1,
limits = names(colset1),
guide = ggplot2::guide_legend(order = 2)) +
ggplot2::scale_color_manual(values = colset1_line) +
ggplot2::geom_bar(ggplot2::aes(fill = as.factor(grade_item), color=as.factor(grade_item)), position = "fill", width = .8) +
ggplot2::scale_y_continuous(labels = c("0","25","50","75","100"),
breaks = c(0, .25, .5, .75, 1),
limits = c(0, 1.01)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
# ----------------------------------------------------------------
# -- Composite items only
# ----------------------------------------------------------------
else if("Composite" %in% unique(plot_combined0$lab)&
sum(c("Frequency", "Severity", "Interference", "Amount") %in% unique(plot_combined0$lab))==0){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(x=arm)) +
## -- Composite items
ggplot2::scale_fill_manual(values = colset2,
limits = names(colset2),
guide = ggplot2::guide_legend(order = 3)) +
ggplot2::scale_color_manual(values = colset2_line) +
ggplot2::geom_bar(ggplot2::aes(fill = as.factor(grade_comp), color=as.factor(grade_comp)), position = "fill", width = .8) +
ggplot2::scale_y_continuous(labels = c("0","25","50","75","100"),
breaks = c(0, .25, .5, .75, 1),
limits = c(0, 1.01)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
}
# ----------------------------------------------------------------
# -- Labels requested
# ----------------------------------------------------------------
else if(label!=0){
# ----------------------------------------------------------------
# -- Individual and composite items
# ----------------------------------------------------------------
if("Composite" %in% unique(plot_combined0$lab) &
sum(c("Frequency", "Severity", "Interference", "Amount") %in% unique(plot_combined0$lab))>0){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(x=arm)) +
## -- Individual items
ggplot2::scale_fill_manual(values = colset1,
limits = names(colset1),
guide = ggplot2::guide_legend(order = 2)) +
ggplot2::scale_color_manual(values = colset1_line) +
ggplot2::geom_bar(data = plot_combined0[!is.na(plot_combined0$grade_item),],
ggplot2::aes(fill = as.factor(grade_item), color=as.factor(grade_item)), position = "fill", width = .8) +
ggnewscale::new_scale(new_aes = "fill") +
ggnewscale::new_scale(new_aes = "color") +
## -- Composite items
ggplot2::scale_fill_manual(values = colset2,
limits = names(colset2),
guide = ggplot2::guide_legend(order = 3)) +
ggplot2::scale_color_manual(values = colset2_line) +
ggplot2::geom_bar(data = plot_combined0[!is.na(plot_combined0$grade_comp),],
ggplot2::aes(fill = as.factor(grade_comp), color=as.factor(grade_comp)), position = "fill", width = .8) +
## -- Customize
ggplot2::geom_hline(yintercept=1.04, linetype="solid", color = "darkgrey") +
ggplot2::geom_text(ggplot2::aes(y= 1.13, label=bar_lab_opt), size=3, na.rm=TRUE) +
ggplot2::scale_y_continuous(labels = y_scale_lab,
breaks = c(0, .25, .5, .75, 1, 1.13),
limits = c(0, 1.14)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
# ----------------------------------------------------------------
# -- Individual items only
# ----------------------------------------------------------------
else if(!("Composite" %in% unique(plot_combined0$lab))){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(x=arm)) +
## -- Individual items
ggplot2::scale_fill_manual(values = colset1,
limits = names(colset1),
guide = ggplot2::guide_legend(order = 2)) +
ggplot2::scale_color_manual(values = colset1_line) +
ggplot2::geom_bar(ggplot2::aes(fill = as.factor(grade_item), color=as.factor(grade_item)), position = "fill", width = .8) +
## -- Customize
ggplot2::geom_hline(yintercept=1.04, linetype="solid", color = "darkgrey") +
ggplot2::geom_text(ggplot2::aes(y= 1.13, label=bar_lab_opt), size=3, na.rm=TRUE) +
ggplot2::scale_y_continuous(labels = y_scale_lab,
breaks = c(0, .25, .5, .75, 1, 1.13),
limits = c(0, 1.14)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
# ----------------------------------------------------------------
# -- Composite items only
# ----------------------------------------------------------------
else if("Composite" %in% unique(plot_combined0$lab)&
sum(c("Frequency", "Severity", "Interference", "Amount") %in% unique(plot_combined0$lab))==0){
figure_i = ggplot2::ggplot(plot_combined0, ggplot2::aes(x=arm)) +
## -- Composite items
ggplot2::scale_fill_manual(values = colset2,
limits = names(colset2),
guide = ggplot2::guide_legend(order = 3)) +
ggplot2::scale_color_manual(values = colset2_line) +
ggplot2::geom_bar(ggplot2::aes(fill = as.factor(grade_comp), color=as.factor(grade_comp)), position = "fill", width = .8) +
## -- Customize
ggplot2::geom_hline(yintercept=1.04, linetype="solid", color = "darkgrey") +
ggplot2::geom_text(ggplot2::aes(y= 1.13, label=bar_lab_opt), size=3, na.rm=TRUE) +
ggplot2::scale_y_continuous(labels = y_scale_lab,
breaks = c(0, .25, .5, .75, 1, 1.13),
limits = c(0, 1.14)) +
ggplot2::facet_grid(item_lab~cycle_var_v_plot) +
ggplot2::xlab(x_label) +
ggplot2::ylab("Percent of Total Frequency") +
ggplot2::labs(caption = foot_note) +
ggplot2::theme(
plot.caption = ggtext::element_markdown(hjust=0, lineheight = -20),
plot.title.position = "plot",
plot.caption.position = "plot",
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 0)),
axis.title.x = ggplot2::element_text(margin = ggplot2::margin(t = 10, r = 0, b = 0, l = 0)),
axis.text.x = ggplot2::element_text(angle = x_lab_angle, vjust=x_lab_vjust, hjust=x_lab_hjust),
legend.position="none",
legend.box = "vertical",
legend.direction = "horizontal",
legend.box.just = "left",
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_rect(color="grey", fill="white"),
strip.background = ggplot2::element_rect(colour="grey", fill="#ededed"),
strip.text.y = ggplot2::element_text(angle=90))
}
}
list_out[[i]] = list()
list_out[[i]][[1]] = refset[refset$group_rank==i,]$group_lab[1]
list_out[[i]][[2]] = figure_i
if(plot_data == TRUE){
list_out[[i]][[3]] = plot_combined0[, !(names(plot_combined0) %in% "null")]
}
}
## -- Reference table for user to view the indexing of PRO-CTCAE item groups withing the list output
for (i in 1:length(list_out)){
if (i==1) {fig_tab = data.frame()}
list_deat = data.frame(PRO_AE = list_out[[i]][[1]], item_index=i)
fig_tab = rbind(fig_tab, list_deat)
}
## -- Reference table
print(fig_tab)
## -- Object return
invisible(list_out)
}
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