Joint latent class model for longitudinal data and interval-censored semi-competing events: Application to dementia

• Published in: Biometrics Vol. 72; no. 4; pp. 1123 - 1135
• Main Authors: Rouanet, Anaïs, Joly, Pierre, Dartigues, Jean-François, Proust-Lima, Cécile, Jacqmin-Gadda, Hélène
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.12.2016; Wiley-Blackwell
• Subjects: Aging; Aging - physiology; BIOMETRIC METHODOLOGY; biometry; Cognition Disorders; Cognitive ability; cohort studies; Computer simulation; Data processing; Death; Dementia; Dementia disorders; elderly; Geriatrics; Health risk assessment; Humans; Illness-death; Interval censoring; Joint model; Latent class analysis; Longitudinal Studies; Markers; Markov chains; Maximum likelihood estimates; Mixed model; Models, Statistical; mortality; Older people; Parameter estimation; Risk; Risk analysis; Risk factors; Semi-competing risks; statistical models; Illness-death; Interval censoring; Joint model; Mixed model; Semi-competing risks
• ISSN: 0006-341X; 1541-0420; 1541-0420
• DOI: 10.1111/biom.12530

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 intervalcensored since dementia is assessed intermittently. So subjects can develop dementia and die between two visits without being diagnosed. To study predementia 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 marker and the times-to-events is captured by latent classes, homogeneous sub-groups with specific risks of death, dementia, and profiles of cognitive decline. We propose Markovian and semi-Markovian versions. Both approaches are compared to a joint latent-class model for competing risks through a simulation study, and applied in a prospective cohort study of cerebral and functional ageing to distinguish different profiles of cognitive decline associated with risks of dementia and death. The comparison highlights that among subjects with dementia, mortality depends more on age than on duration of dementia. This model distinguishes the so-called terminal predeath decline (among healthy subjects) from the predementia decline.