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.

翻译：生存分析领域的进展为数据建模提供了前所未有的灵活性，但现有工具仍难以通过图形直观展示连续协变量对预测生存结局的影响。我们提出使用彩色等高线图来描绘随时间变化的预测生存概率，并开发了Shiny应用程序及R包作为该工具的实现方案。该方法支持传统模型（包括Cox模型与Fine-Gray模型），但其核心优势在于与随机生存森林、深度神经网络等前沿机器学习模型结合时尤为突出。