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#' Forest Plot for Cox Proportional Hazards Model
#'
#' @description Drawing Forest Plot for Cox proportional hazards model. In two panels the model structure is presented.
#' @param model an object of class coxph.
#' @param data a dataset used to fit survival curves. If not supplied then data
#' will be extracted from 'fit' object.
#' @param main title of the plot.
#' @param cpositions relative positions of first three columns in the OX scale.
#' @param fontsize relative size of annotations in the plot. Default value: 0.7.
#' @param refLabel label for reference levels of factor variables.
#' @param noDigits number of digits for estimates and p-values in the plot.
#'
#' @return returns a ggplot2 object (invisibly)
#'
#' @author Przemyslaw Biecek (\email{przemyslaw.biecek@@gmail.com}),
#' Fabian Scheipl (\email{fabian.scheipl@@gmail.com})
#'
#' @examples
#' require("survival")
#' model <- coxph( Surv(time, status) ~ sex + rx + adhere,
#' data = colon )
#' ggforest(model)
#'
#' colon <- within(colon, {
#' sex <- factor(sex, labels = c("female", "male"))
#' differ <- factor(differ, labels = c("well", "moderate", "poor"))
#' extent <- factor(extent, labels = c("submuc.", "muscle", "serosa", "contig."))
#' })
#' bigmodel <-
#' coxph(Surv(time, status) ~ sex + rx + adhere + differ + extent + node4,
#' data = colon )
#' ggforest(bigmodel)
#'
#' @export
#' @import broom
#' @import grid
#' @import gridExtra
#' @importFrom grDevices axisTicks
#' @importFrom stats anova var
ggforest <- function(model, data = NULL,
main = "Hazard ratio", cpositions=c(0.02, 0.22, 0.4),
fontsize = 0.7, refLabel = "reference", noDigits=2) {
conf.high <- conf.low <- estimate <- NULL
stopifnot(inherits(model, "coxph"))
# get data and variables/terms from cox model
data <- .get_data(model, data = data)
terms <- attr(model$terms, "dataClasses")[-1]
# removed as requested in #388
# terms <- terms[intersect(names(terms),
# gsub(rownames(anova(model))[-1], pattern = "`", replacement = ""))]
# use broom to get some required statistics
coef <- as.data.frame(tidy(model, conf.int = TRUE))
gmodel <- glance(model)
# extract statistics for every variable
allTerms <- lapply(seq_along(terms), function(i){
var <- names(terms)[i]
if (terms[i] %in% c("factor", "character")) {
adf <- as.data.frame(table(data[, var]))
cbind(var = var, adf, pos = 1:nrow(adf))
}
else if (terms[i] == "numeric") {
data.frame(var = var, Var1 = "", Freq = nrow(data),
pos = 1)
}
else {
vars = grep(paste0("^", var, "*."), coef$term, value=TRUE)
data.frame(var = vars, Var1 = "", Freq = nrow(data),
pos = seq_along(vars))
}
})
allTermsDF <- do.call(rbind, allTerms)
colnames(allTermsDF) <- c("var", "level", "N", "pos")
inds <- apply(allTermsDF[,1:2], 1, paste0, collapse="")
# use broom again to get remaining required statistics
rownames(coef) <- gsub(coef$term, pattern = "`", replacement = "")
toShow <- cbind(allTermsDF, coef[inds,])[,c("var", "level", "N", "p.value", "estimate", "conf.low", "conf.high", "pos")]
toShowExp <- toShow[,5:7]
toShowExp[is.na(toShowExp)] <- 0
toShowExp <- format(exp(toShowExp), digits=noDigits)
toShowExpClean <- data.frame(toShow,
pvalue = signif(toShow[,4],noDigits+1),
toShowExp)
toShowExpClean$stars <- paste0(round(toShowExpClean$p.value, noDigits+1), " ",
ifelse(toShowExpClean$p.value < 0.05, "*",""),
ifelse(toShowExpClean$p.value < 0.01, "*",""),
ifelse(toShowExpClean$p.value < 0.001, "*",""))
toShowExpClean$ci <- paste0("(",toShowExpClean[,"conf.low.1"]," - ",toShowExpClean[,"conf.high.1"],")")
toShowExpClean$estimate.1[is.na(toShowExpClean$estimate)] = refLabel
toShowExpClean$stars[which(toShowExpClean$p.value < 0.001)] = "<0.001 ***"
toShowExpClean$stars[is.na(toShowExpClean$estimate)] = ""
toShowExpClean$ci[is.na(toShowExpClean$estimate)] = ""
toShowExpClean$estimate[is.na(toShowExpClean$estimate)] = 0
toShowExpClean$var = as.character(toShowExpClean$var)
toShowExpClean$var[duplicated(toShowExpClean$var)] = ""
# make label strings:
toShowExpClean$N <- paste0("(N=",toShowExpClean$N,")")
#flip order
toShowExpClean <- toShowExpClean[nrow(toShowExpClean):1, ]
rangeb <- range(toShowExpClean$conf.low, toShowExpClean$conf.high, na.rm = TRUE)
breaks <- axisTicks(rangeb/2, log = TRUE, nint = 7)
rangeplot <- rangeb
# make plot twice as wide as needed to create space for annotations
rangeplot[1] <- rangeplot[1] - diff(rangeb)
# increase white space on right for p-vals:
rangeplot[2] <- rangeplot[2] + .15 * diff(rangeb)
width <- diff(rangeplot)
# y-coordinates for labels:
y_variable <- rangeplot[1] + cpositions[1] * width
y_nlevel <- rangeplot[1] + cpositions[2] * width
y_cistring <- rangeplot[1] + cpositions[3] * width
y_stars <- rangeb[2]
x_annotate <- seq_len(nrow(toShowExpClean))
# geom_text fontsize is in mm (https://github.com/tidyverse/ggplot2/issues/1828)
annot_size_mm <- fontsize *
as.numeric(convertX(unit(theme_get()$text$size, "pt"), "mm"))
p <- ggplot(toShowExpClean, aes(seq_along(var), exp(estimate))) +
geom_rect(aes(xmin = seq_along(var) - .5, xmax = seq_along(var) + .5,
ymin = exp(rangeplot[1]), ymax = exp(rangeplot[2]),
fill = ordered(seq_along(var) %% 2 + 1))) +
scale_fill_manual(values = c("#FFFFFF33", "#00000033"), guide = "none") +
geom_point(pch = 15, size = 4) +
geom_errorbar(aes(ymin = exp(conf.low), ymax = exp(conf.high)), width = 0.15) +
geom_hline(yintercept = 1, linetype = 3) +
coord_flip(ylim = exp(rangeplot)) +
ggtitle(main) +
scale_y_log10(
name = "",
labels = sprintf("%g", breaks),
expand = c(0.02, 0.02),
breaks = breaks) +
theme_light() +
theme(panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.y = element_blank(),
legend.position = "none",
panel.border=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
plot.title = element_text(hjust = 0.5)) +
xlab("") +
annotate(geom = "text", x = x_annotate, y = exp(y_variable),
label = toShowExpClean$var, fontface = "bold", hjust = 0,
size = annot_size_mm) +
annotate(geom = "text", x = x_annotate, y = exp(y_nlevel), hjust = 0,
label = toShowExpClean$level, vjust = -0.1, size = annot_size_mm) +
annotate(geom = "text", x = x_annotate, y = exp(y_nlevel),
label = toShowExpClean$N, fontface = "italic", hjust = 0,
vjust = ifelse(toShowExpClean$level == "", .5, 1.1),
size = annot_size_mm) +
annotate(geom = "text", x = x_annotate, y = exp(y_cistring),
label = toShowExpClean$estimate.1, size = annot_size_mm,
vjust = ifelse(toShowExpClean$estimate.1 == "reference", .5, -0.1)) +
annotate(geom = "text", x = x_annotate, y = exp(y_cistring),
label = toShowExpClean$ci, size = annot_size_mm,
vjust = 1.1, fontface = "italic") +
annotate(geom = "text", x = x_annotate, y = exp(y_stars),
label = toShowExpClean$stars, size = annot_size_mm,
hjust = -0.2, fontface = "italic") +
annotate(geom = "text", x = 0.5, y = exp(y_variable),
label = paste0("# Events: ", gmodel$nevent, "; Global p-value (Log-Rank): ",
format.pval(gmodel$p.value.log, eps = ".001"), " \nAIC: ", round(gmodel$AIC,2),
"; Concordance Index: ", round(gmodel$concordance,2)),
size = annot_size_mm, hjust = 0, vjust = 1.2, fontface = "italic")
# switch off clipping for p-vals, bottom annotation:
gt <- ggplot_gtable(ggplot_build(p))
gt$layout$clip[gt$layout$name == "panel"] <- "off"
# grid.draw(gt)
# invisible(p)
ggpubr::as_ggplot(gt)
}
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