A Semi-Parametric Marginal Cure Model for Long-Term Survivors

Music City Center 

Cure rate models, or two-component mixture models for long-term survivors, are widely used in survival analysis. Most applications focus on interpreting covariate effects on the cure fraction and conditional hazard rate. However, it remains challenging to directly interpret their effects on overall survival outcomes, especially when covariates influence both components simultaneously. We propose a marginal cure rate model that provides a general framework for studying covariate effects from a marginal perspective, offering clearer interpretations. Using novel reparameterizations, we directly relate covariates to the marginal mean hazard rate. To enhance flexibility, we introduce a semi-parametric model based on Bernstein polynomials, relaxing the parametric baseline hazard assumption for the conditional hazard function. The performance of our approach is assessed through extensive simulations and illustrated using SEER liver cancer data.

Bernstein polynomials

Cure fraction

Cure rate model

Liver Cancer

SEER registry 

Biometrics Section