Stockholm university
Department of Statistics

Seminar: Enoch Yi-Tung Chen, Karolinska Institutet

Seminar

Date: Wednesday 22 October 2025

Time: 13.00 – 14.00

Location: Campus Albano, Lecture room 2, house 1, level 2

A Multistate Model Incorporating Relative Survival Extrapolation and Mixed Time Scales for Health Technology Assessment

Abstract

Multistate models have been widely applied in health technology assessment. However, extrapolating survival in a multistate model setting presents challenges in terms of accurate predictions. 

We develop an individual-level continuous time multistate model that integrates relative survival extrapolation and mixed time scales. We illustrate our proposed model using an illness-death model. We model the transition rates using flexible parametric models. We provide computer code to simulate event times from models with mixed time scales. This feature allows us to incorporate relative survival extrapolation in a multistate setting. We compare several multistate models with different parametric models (standard vs. flexible parametric models), and survival frameworks (all-cause vs. relative survival framework) using a previous clinical trial as an illustrative example. 

In the example case study, the results agreed better with the observed data than the commonly applied approach using standard parametric models within an all-cause survival framework. The model provides an alternative to combine short-term trial data with long-term external data within a multistate model context in health technology assessment.

Reference:
Chen EYT, Dickman PW, Clements MS. A multistate model incorporating relative survival extrapolation and mixed time scales for health technology assessment. PharmacoEconomics. 2025; 43:297–310.

 https://doi.org/10.1007/s40273-024-01457-w

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Last updated: October 27, 2025

Source: Department of Statistics

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