JPsurv Suite: Cancer Survival Analysis Tools

The JPsurv Suite provides statistical tools for analyzing population-based cancer survival, combining trend analysis and flexible survival modeling within a single framework. It includes JPsurv, which analyzes trends in survival by year of diagnosis using joinpoint models, and CanSurv, which supports detailed survival modeling, including parametric, Cox, and mixture cure models with diagnostic tools.

Tools in the JPsurv Suite

JPsurv

Analyzes trends in survival by year of diagnosis using joinpoint models, including options for conditional survival and non-proportional hazards.

• Learn more about JPsurv
• Video tutorials on how to conduct JPSurv analysis

CanSurv

Provides flexible survival modeling, including parametric, Cox, and mixture cure models, with tools for model diagnostics.

Learn more about CanSurv

Data

Compatible with population-based survival data, including outputs from SEER*Stat.

Supports both relative and cause-specific survival, with data formats depending on the tool.

What’s New

• Integration of CanSurv into the JPsurv Suite
• JPsurv tool supports conditional survival trends
• Options to relax proportional hazards assumptions in JPsurv tool
• Improved output flexibility in CanSurv