plot_km_fit: Kaplan Meier Plot of Curve-Fit

In gestate: Generalised Survival Trial Assessment Tool Environment

Kaplan Meier Plot of Curve-Fit

Description

This function creates a Kaplan Meier plot with the fitted curve from the output of event_prediction(), fit_tte_data() or fit_KM().
Where available, it will include fitting confidence intervals based upon the variance derived by the delta method.
Options are available to customise inclusion.

Usage

plot_km_fit(
  fit,
  data,
  Time = "Time",
  Event = "Event",
  censoringOne = FALSE,
  CI = 0.95,
  colour_CI = TRUE,
  maxT = NULL,
  xlim = NULL,
  ylim = c(0, 1),
  main = "Kaplan Meier Curve Fit Plot",
  fit_col = 2,
  km_col = 1,
  area_col = "skyblue",
  CI_col = 4,
  CI_lty = 2,
  no_legend = FALSE,
  legend_position = c("bottom_left", "top_right"),
  overlay = FALSE,
  ...
)

Arguments

fit	Full output list from event_prediction(), fit_tte_data() or fit_KM().
data	Name of patient-level data set, used to generate the KM plot.
Time	The column name for the times. Default is "Time"
Event	The column name for the events column (i.e. the binary variable denoting events vs censorings). Default is "Event"
censoringOne	Specify whether censoring is denoted in the Event column by a one (TRUE) or zero (FALSE). Default=FALSE (censorings denoted by 0, events by 1)
CI	Number between 0 and 1 for the size of Kaplan Meier confidence interval to calculate. Default is 0.95 (95 percent confidence interval).
colour_CI	Boolean for whether to colour the fitting confidence interval area. Default=TRUE (colour area)
maxT	Maximum time to calculate point estimate and CIs up to. Default=NULL (Calculate up to last time in patient data)
xlim	Standard graphical parameter for x-axis limits. Default=NULL (Plots from 0 to maximum patient time)
ylim	Graphical parameter for y-axis limits. Default=c(0,1) (Plots survival function from 0 to 1)
main	String for plot title. Default="Kaplan Meier Curve Fit Plot"
fit_col	Colour for fitting curve Default=2 (red)
km_col	Colour for km curve Default=1 (black)
area_col	Colour for CI area Default="skyblue" (sky blue)
CI_col	Colour for CI Default=4 (blue)
CI_lty	Line type for CI Default=2 (dashed)
no_legend	Boolean to turn off legend. Default is FALSE; legend shown.
legend_position	String with "top_right", or "bottom_left", corresponding to legend position in power plot. (Default="bottom_left").
overlay	Boolean whether to overlay on existing plot (vs start a new one). Default=FALSE
...	Additional graphical parameters.

Value

Returns NULL

Author(s)

James Bell

Examples

recruit <- PieceR(matrix(c(rep(1,12),10,15,25,30,45,60,55,50,65,60,55,30),ncol=2),1)
trial_long <- simulate_trials(active_ecurve=Weibull(50,0.8),control_ecurve=Weibull(50,0.8),
rcurve=recruit,fix_events=200, iterations=1,seed=12345,detailed_output=TRUE)
trial_short <- set_assess_time(data=trial_long,time=10,detailed_output = FALSE)

maxtime <- max(ceiling(trial_long[,"Assess"]))
events <- rep(NA,maxtime)
for (i in 1:maxtime){events[i] <- sum(1-set_assess_time(trial_long,i)[,"Censored"])}

predictions <- event_prediction(data=trial_short, Event="Censored", censoringOne=TRUE, 
type="Weibull", rcurve=recruit, max_time=60, cond_Events=49, cond_NatRisk=451, 
cond_Time=10, units="Months")

plot_km_fit(fit=predictions,data=trial_short,Event="Censored",censoringOne=TRUE,maxT=70)

gestate documentation built on April 26, 2023, 5:10 p.m.