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Compare two staging systems using Groome criteria (Groome et al., 2001). Calculates four key metrics: hazard consistency, hazard discrimination, sample balance, and outcome prediction. Provides overall rank to determine which staging system performs better. Includes C-index comparison, radar charts, and side-by-side Kaplan-Meier curves.

Usage

groomecompare(
  data,
  time,
  event,
  stage1,
  stage2,
  eventValue = "1",
  stage1name = "Staging System 1",
  stage2name = "Staging System 2",
  radarplot = TRUE,
  barplot = FALSE,
  kmplots = TRUE,
  detailedmetrics = TRUE,
  hazardratios = TRUE,
  samplesize = TRUE,
  cindexcompare = TRUE,
  bootstrap = FALSE,
  nboot = 1000,
  seed = 12345
)

Arguments

data

.

time

a (non-negative valued) vector of survival times

event

the status indicator (0=censored, 1=event)

stage1

first staging system to compare (e.g., ypTNM stage)

stage2

second staging system to compare (e.g., RPA stage)

eventValue

the value representing an event

stage1name

descriptive name for first staging system

stage2name

descriptive name for second staging system

radarplot

.

barplot

.

kmplots

.

detailedmetrics

.

hazardratios

.

samplesize

.

cindexcompare

.

bootstrap

.

nboot

.

seed

.

Value

A results object containing:

results$instructionsa html
results$summarya table
results$detailedmetrics$consistencya table
results$detailedmetrics$discriminationa table
results$hazardratios$hrs1a table
results$hazardratios$hrs2a table
results$samplesizea table
results$cindexcomparea table
results$radarplotan image
results$barplotan image
results$kmplot1an image
results$kmplot2an image
results$bootstrapa table
results$noticesa html

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$summary$asDF

as.data.frame(results$summary)