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ROCsurvcomp

Overview

ROCsurvcomp is an R package for comparing survival curves under non-proportional hazards (non-PH) using ROC-based methods. Traditional log-rank test may lose power when the proportional hazards assumption is violated. Other methods, such as the Fleming-Harrington (FH) family of weighted log-rank tests require prior knowledge of the underlying non-PH patterns, and incorrectly specified patterns may lead to a substantial loss of statistical power. This package provides alternative approaches for comparing survival curves based on ROC curve, without requiring prior knowledge of the underlying non-PH pattern, and can accommodate right, left, and doubly censored data.

Key Features

• Implements nonparametric and semiparametric kernel-based approaches for comparing two survival distributions
• Designed for handling non-proportional hazards settings
• Methods include:
  • ROC length-based test
  • Overlap coefficient (OVL)-based test
  • Joint ROC length-OVL-based test
• Supports right, left and doubly-censored survival data
• Permutation-based inference with two-sided hypothesis testing

Installation

You can install the package from GitHub:

# install.packages("remotes")    # if not installed
remotes::install_github("mmrahman13/ROCsurvcomp")

Usage

Basic Example

library(ROCsurvcomp)
library(PWEXP)

# Generating right-censored data with crossing survivals
set.seed(126)
n_trt <- 50
break_trt <- c(2, 4)
rate_trt <- c(log(2)/3, log(2)/7, log(2)/20)
rate.censor_trt <- c(log(2)/55, log(2)/62, log(2)/68)
event_trt <- PWEXP::rpwexp(n_trt, rate = rate_trt, breakpoint = break_trt)
censor_trt <- PWEXP::rpwexp(n_trt, rate = rate.censor_trt, breakpoint = break_trt)

n_ctrl <- 50
rate_ctrl <- log(2)/10
rate.censor_ctrl <- log(2)/58
event_ctrl <- rexp(n_ctrl, rate = rate_ctrl)
censor_ctrl <- rexp(n_ctrl, rate = rate.censor_ctrl)

# Observed time and censoring status (0 = event, 1 = right-censored)
time_trt <- pmin(event_trt, censor_trt)
status_trt <- ifelse(event_trt <= censor_trt, 0, 1)
time_ctrl <- pmin(event_ctrl, censor_ctrl)
status_ctrl <- ifelse(event_ctrl <= censor_ctrl, 0, 1)
time <- c(time_trt, time_ctrl)
status <- c(status_trt, status_ctrl)
group <- c(rep(1, n_trt), rep(2, n_ctrl))

# Run `surv.comp()` function
# Note: n_perm = 1000 is used here only for illustration purposes. Highly recommended n_perm to be set at 50,000 or more.
surv.comp(
  time = time,
  status = status,
  group = group,
  censor_type = "right",
  method = "joint_method",
  n_perm = 1000,
  progress = TRUE,
  plot = TRUE
)

Methodology

This package implements ROC-based approaches for comparing two survival curves:

• ROC Length: Measures separation between two distributions without relying on any stochastic ordering
• Overlap Coefficient (OVL): Quantifies the similarity between two distributions using the common area between two probability density functions
• Joint Test: Combines ROC length and OVL-based methods by constructing convex hull of the permuted samples based on their Euclidean distance from the origin.

These methods are especially useful when: - The proportional hazards assumption is violated - Treatment effects are not constant over time and no prior information about the pattern of effects is available - Survival curves cross.

Authors

Mohammod Mahmudur Rahman
PhD Student, Department of Biostatistics & Data Science
University of Kansas Medical Center

Leonidas Bantis
Associate Professor, Department of Biostatistics & Data Science
University of Kansas Medical Center

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.