Multistate models for the natural history of cancer progression.

ABSTRACT:

Background

Multistate models can be effectively used to characterise the natural history of cancer. Inference from such models has previously been useful for setting screening policies.

Methods

We introduce the basic elements of multistate models and the challenges of applying these models to cancer data. Through simulation studies, we examine (1) the impact of assuming time-homogeneous Markov transition intensities when the intensities depend on the time since entry to the current state (i.e., the process is time-inhomogenous semi-Markov) and (2) the effect on precancer risk estimation when observation times depend on an unmodelled intermediate disease state.

Results

In the settings we examined, we found that misspecifying a time-inhomogenous semi-Markov process as a

SUBMITTER: Cheung LC 

PROVIDER: S-EPMC9519900 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature