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Extract Survival Analysis Results from Kaplan-Meier Tables Using Person-Years Method

Overview

The mimicsurv package provides tools for survival analysis from published Kaplan-Meier tables using the person-years method. This package enables researchers to extract quantitative survival analysis results from published studies when individual patient data is not available.

It also includes simulation functions for method validation and support for mixed exponential distribution analysis.

Documentation

Quick Start Guide

📖 Getting Started with mimicsurv - Complete tutorial with examples

Real-World Case Studies

🏥 KEYNOTE-859 Clinical Trial Analysis - Reproducing survival results from a real pembrolizumab clinical trial

Reference Documentation

📚 Package Reference - Detailed function documentation

Installation

You can install the development version of mimicsurv from GitHub:

# Install devtools if you haven't already
install.packages("devtools")

# Install mimicsurv from GitHub
devtools::install_github("gosukehommaEX/mimicsurv")

Dependencies

This package requires the following R packages: - survival (automatically installed) - For vignettes: ggplot2, dplyr (suggested packages)

Features

  • Extract survival metrics from published Kaplan-Meier curves
  • Estimate hazard rates using the person-years method
  • Calculate median survival times when not explicitly reported
  • Mixed exponential distribution analysis for combining multiple subgroups
  • Simulation functions for method validation
  • Real-world examples including KEYNOTE-859 clinical trial analysis
  • Enable meta-analyses and comparative effectiveness research

Quick Example

Basic Survival Analysis from Kaplan-Meier Tables 

library(mimicsurv)

# Example data from a clinical trial
time_points <- c(0, 6, 12, 18, 24)
n_risk <- c(200, 150, 100, 60, 35)
n_censored <- c(0, 10, 20, 30, 40)

# Extract survival analysis results
result <- extractfromKM(time_points, n_risk, n_censored)

# View results
print(result$hazard_table)
cat("Median survival time:", result$median_survival, "months")

Mixed Exponential Distribution Analysis 

# Calculate overall median survival time from multiple subgroups
expected_events <- c(75, 120)  # Expected event counts for each subgroup
MST_subgroups <- c(6, 7.5)     # Median survival times for each subgroup

# Calculate overall median survival time
result_mixed <- mstfromExpdists(expected_events, MST_subgroups)

# View results
print(result_mixed$subgroup_summary)
print(paste("Overall MST:", round(result_mixed$MST_overall, 2), "months"))

Core Functions

  • extractfromKM(): Extract survival analysis results from Kaplan-Meier tables
  • mstfromExpdists(): Calculate overall median survival time from mixed exponential distributions
  • simPE(): Simulate survival data from piecewise exponential distributions
  • summaryKM(): Create Kaplan-Meier style summary tables from simulated data
  • getMediansurv(): Calculate median survival time from piecewise exponential parameters

Methodology

The package implements the person-years method for hazard estimation based on the following assumptions:

  • Piecewise exponential survival within each time interval
  • Non-informative censoring independent of the event process
  • Uniform distribution of events and censoring within intervals

For mixed exponential distributions, the package uses numerical methods to solve: S(t)=∑j=1kpjexp(−λjt)=0.5S(t) = \sum_{j=1}^{k} p_j \exp(-\lambda_j t) = 0.5

For detailed mathematical background, see the Getting Started vignette.

Use Cases

  • Systematic reviews and meta-analyses
  • Comparative effectiveness research
  • Health technology assessment
  • Clinical trial re-analysis and validation
  • Academic research when individual patient data (IPD) is unavailable
  • Combining survival data from multiple subgroups with different characteristics

Real-World Applications

The package includes a comprehensive case study analyzing the KEYNOTE-859 clinical trial, demonstrating how to:

  • Extract survival data from published Kaplan-Meier curves
  • Compare treatment arms (pembrolizumab vs. placebo)
  • Estimate hazard rates over time
  • Calculate median survival times
  • Visualize results with publication-ready figures

See the KEYNOTE-859 Analysis vignette for the complete workflow.

License

MIT + file LICENSE

Citation

If you use this package in your research, please cite:

Homma, G. (2025). mimicsurv: Extract Survival Analysis Results from
Kaplan-Meier Tables Using Person-Years Method. R package version 0.1.0.
https://github.com/gosukehommaEX/mimicsurv