MSR62 Estimating Life Expectancy By Extrapolating Relative Survival: Comparison of the Flexible Parametric Model and the Rolling Extrapolation Algorithm Using Real-World Cancer Data

Abstract

In health technology assessments, life expectancy estimates are often used for evaluating the effectiveness of interventions. Due to limited follow-up data, parametric models are typically used to fit patient-level data but yield inaccurate extrapolation until lifetime. We aim to compare two relatively new approaches, the flexible parametric relative survival model (FPM) by Andersson et al. (2013) and the rolling extrapolation algorithm (REA) by Hwang et al. (2017), which incorporate relative survival framework into their extrapolation processes with the intention to provide more robust extrapolated survival for estimating life expectancy.