Joint latent class model for longitudinal data and interval-censored semi-competing events: Application to dementia
Ana\"is Rouanet, Pierre Joly, Jean-Fran\c{c}ois Dartigues, C\'ecile, Proust-Lima, H\'el\`ene Jacqmin-Gadda

TL;DR
This paper introduces a joint latent class model for analyzing longitudinal cognitive data and semi-competing risks like dementia and death, accounting for interval censoring and heterogeneity in aging populations.
Contribution
It develops a novel joint model combining multivariate mixed models with illness-death models, handling interval censoring and semi-competing risks in aging studies.
Findings
Mortality depends more on age than dementia duration among demented subjects.
The model distinguishes terminal pre-death decline from pre-dementia decline.
Application to cohort data reveals different cognitive decline profiles associated with risks.
Abstract
Joint models are used in ageing studies to investigate the association between longitudinal markers and a time-to-event, and have been extended to multiple markers and/or competing risks. The competing risk of death must be considered in the elderly because death and dementia have common risk factors. Moreover, in cohort studies, time-to-dementia is interval-censored because dementia is only assessed intermittently. So subjects can become demented and die between two follow-up visits without being diagnosed. To study pre-dementia cognitive decline, we propose a joint latent class model combining a (possibly multivariate) mixed model and an illness-death model handling both interval censoring (by accounting for a possible unobserved transition to dementia) and semi-competing risks. Parameters are estimated by maximum likelihood handling interval censoring. The correlation between the…
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Taxonomy
TopicsStatistical Methods and Inference · Bayesian Methods and Mixture Models · Statistical Methods and Bayesian Inference
