History-restricted marginal structural model and latent class growth analysis of treatment trajectories for a time-dependent outcome.

ABSTRACT: In previous work, we introduced a framework that combines latent class growth analysis (LCGA) with marginal structural models (LCGA-MSM). LCGA-MSM first summarizes the numerous time-varying treatment patterns into a few trajectory groups and then allows for a population-level causal interpretation of the group differences. However, the LCGA-MSM framework is not suitable when the outcome is time-dependent. In this study, we propose combining a nonparametric history-restricted marginal structural model (HRMSM) with LCGA. HRMSMs can be seen as an application of standard MSMs on multiple time intervals. To the best of our knowledge, we also present the first application of HRMSMs with a time-to-event outcome. It was previously noted that HRMSMs could pose interpretation problems in survival an

SUBMITTER: Diop A 

PROVIDER: S-EPMC11661564 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature