gestate (version 1.6.0)

plot_km_fit: 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,
  ...
)

Value

Returns NULL

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.

Author

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)