Plot Adjusted Restricted Mean Time Lost Curves

A function to graphically display the Restricted Mean Time Lost (RMTL) over time, using confounder-adjusted survival curves which were previously estimated using the adjustedsurv function, or cause-specific confounder-adjusted CIFs which were previously estimated using the adjustedcif function. As the other plot functions in this package, it internally uses the ggplot2 package and allows a variety of options. Alternatively plots the difference between or ratio of two adjusted RMTL curves.

Usage

plot_rmtl_curve(adj, times=NULL, conf_int=FALSE,
                conf_level=0.95, interpolation="steps",
                contrast="none", group_1=NULL, group_2=NULL,
                max_t=Inf, color=TRUE, linetype=FALSE,
                facet=FALSE, size=1, alpha=1, xlab="Time",
                ylab="RMTL", title=NULL, subtitle=NULL,
                legend.title="Group", legend.position="right",
                gg_theme=ggplot2::theme_classic(),
                custom_colors=NULL, custom_linetypes=NULL,
                conf_int_alpha=0.4,
                line_at_ref=TRUE, line_at_ref_size=0.7,
                line_at_ref_color="grey",
                line_at_ref_linetype="dashed",
                line_at_ref_alpha=1, ...)

Arguments

adj: An adjustedsurv object created using the adjustedsurv function, or an adjustedcif object created using the adjustedcif function.
times: A vector of points in time, passed to the to argument of the adjusted_rmtl function or NULL (default). If NULL, the adjusted RMTL is estimated at all points at which an event occurred. Otherwise it is estimated at times.
conf_int: A logical variable indicating whether the bootstrap confidence intervals should be drawn.
conf_level: Corresponds to the argument of the same name in the adjusted_rmtl function.
interpolation: Corresponds to the argument of the same name in the adjusted_rmtl function.
contrast: Which contrast between two adjusted RMST curves should be plotted. Should be one of c("none", "diff", "ratio"). See argument of the same name in the adjusted_rmst function.
group_1: A single character string specifying one of the possible levels of variable. This can be used in conjunction with the group_2 argument to control how the difference or ratio should be calculated when using either contrast="diff" or contrast="ratio". Ignored when contrast="none" (default). See argument of the same name in the adjusted_rmtl function.
group_2: See argument group_1.
max_t: A number indicating the latest survival time which is to be plotted.
color: A logical variable indicating whether the curves should be colored differently. The custom_colors argument can be used to directly specify which colors to use. Set to FALSE to keep the plot black and white. If contrast="diff" or contrast="ratio" are used, a character string specifying a color that should be used for the plot can be supplied to this argument directly.
linetype: A logical variable indicating whether the curves should have different linetypes. The custom_linetypes argument can be used to directly specify which linetypes to use. Set to FALSE to keep all lines solid. If contrast="diff" or contrast="ratio" are used, a character string specifying a linetype that should be used for the plot can be supplied to this argument directly.
facet: A logical variable indicating whether the curves should be in different facets.
size: A number controlling the thickness of the RMTL curves.
alpha: A number controlling the transparency level of the RMTL curves.
xlab: A character string to be used as the X-Axis label of the plot.
ylab: A character string to be used as the Y-Axis label of the plot.
title: A character string to be used as the title of the plot. Set to NULL if no title should be used.
subtitle: A character string to be used as the subtitle of the plot. Set to NULL if no subtitle should be used.
legend.title: A character string to be used as the title of the legend. Set to NULL if no legend should be included.
legend.position: A character string specifying the position of the legend. Ignored if legend_title=NULL.
gg_theme: A ggplot2 theme object which will be used for the plot.
custom_colors: A (named) vector to specify the colors of each adjusted RMTL curve and possibly its confidence region. Set to NULL to use the ggplot2 default values. Ignored if color=FALSE.
custom_linetypes: A (named) vector to specify the linetype of each adjusted RMTL curve. Set to NULL to use the ggplot2 default values. Ignored if color=FALSE. Ignored if linetype=FALSE.
conf_int_alpha: A number indicating the level of transparency that should be used when drawing the confidence regions.
line_at_ref: Whether to draw a line at the reference value. This line is drawn at 0 if contrast="diff" and at 1 if contrast="ratio". This and all associated argument are ignored otherwise.
line_at_ref_size: A single number specifying the thickness of the line at the reference value.
line_at_ref_color: A single character string specifying the color of the line at the reference value.
line_at_ref_linetype: A single character string specifying the linetype of the line at the reference value.
line_at_ref_alpha: A single number between 0 and 1 specifying the transparency level of the line at the reference value.
...: Currently not used.

Details

This function simply calls the adjusted_rmtl for a range of to values, getting adjusted RMTL estimates over the whole range of the survival curves or CIFs. Those estimates are then plotted as a curve with the adjusted RMTL replacing the survival probability or the failure probability on the Y-Axis. For a brief description on the RMTL and how it is calculated in this package, see the documentation of the adjusted_rmtl function. Literature describing the RMTL Curve Plots in more detail is given in the references section.

If confidence intervals are specified and there are many points in time in times, this function might get somewhat slow. It will be even slower if multiple imputation was also used when creating the adjustedsurv or adjustedcif object.

Value

Returns a ggplot2 object.

References

Lihui Zhao, Brian Claggett, Lu Tian, Hajime Uno, Marc A. Pfeffer, Scott D. Solomon, Lorenzo Trippa, and L. J. Wei (2016). "On the Restricted Mean Survival Time Curve in Survival Analysis". In: Biometrics 72.1, pp. 215-221

Author

Robin Denz

Examples

library(adjustedCurves)
library(survival)

if (requireNamespace("ggplot2") & requireNamespace("riskRegression")) {

library(ggplot2)

set.seed(42)

# simulate some data as example
sim_dat <- sim_confounded_surv(n=50, max_t=1.2)
sim_dat$group <- as.factor(sim_dat$group)

# estimate a cox-regression for the outcome
cox_mod <- coxph(Surv(time, event) ~ x1 + x2 + x3 + x4 + x5 + x6 + group,
                 data=sim_dat, x=TRUE)


# use it to calculate adjusted survival curves with bootstrapping
adjsurv <- adjustedsurv(data=sim_dat,
                        variable="group",
                        ev_time="time",
                        event="event",
                        method="direct",
                        outcome_model=cox_mod,
                        conf_int=TRUE,
                        bootstrap=TRUE,
                        n_boot=15) # should be much bigger in reality

# plot the curves with default values
plot_rmtl_curve(adjsurv)

# plot with confidence intervals
plot_rmtl_curve(adjsurv, conf_int=TRUE)

# plot with difference instead
plot_rmtl_curve(adjsurv, contrast="diff")

# plot with some custom options
plot_rmtl_curve(adjsurv, max_t=0.5, linetype=TRUE,
                custom_colors=c("green", "blue"))
}