survivalContour: Visualizing predicted survival via colored contour plots

TL;DR

This paper introduces survivalContour, a visualization tool using colored contour plots to illustrate how continuous covariates affect predicted survival outcomes, supporting various models including machine learning approaches.

Contribution

It provides a novel graphical method and software implementation for visualizing survival predictions across different models, enhancing interpretability.

Findings

Supports Cox, Fine-Gray, random survival forests, and neural networks.

Enables intuitive visualization of covariate effects on survival.

Available as an R package and Shiny app.

Abstract

Advances in survival analysis have facilitated unprecedented flexibility in data modeling, yet there remains a lack of tools for graphically illustrating the influence of continuous covariates on predicted survival outcomes. We propose the utilization of a colored contour plot to depict the predicted survival probabilities over time, and provide a Shiny app and R package as implementations of this tool. Our approach is capable of supporting conventional models, including the Cox and Fine-Gray models. However, its capability shines when coupled with cutting-edge machine learning models such as random survival forests and deep neural networks.