Using Joint Longitudinal and Time-to-Event Models to Improve the Parameterization of Chronic Disease Microsimulation Models: an Application to Cardiovascular Disease.

ABSTRACT:

Background

Chronic disease microsimulation models often simulate disease incidence as a function of risk factors that evolve over time (e.g., blood pressure increasing with age) in order to facilitate decision analyses of different disease screening and prevention strategies. Existing models typically rely on incidence rates estimated with standard survival analysis techniques (e.g., proportional hazards from baseline data) that are not designed to be continually updated each model cycle. We introduce the use of joint longitudinal and time-to-event to parameterize microsimulations to avoid potential issues from using these existing methods. These joint models include random effects regressions to estimate the risk factor trajectories and a survival model to predict disease risk bas

SUBMITTER: Giardina J 

PROVIDER: S-EPMC11581079 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature