چکیده:
Background and Objective: Cognitive trajectories in individuals with a baseline Clinical Dementia Rating (CDR) score of 0.5 vary widely, ranging from recovery (stable reverse migration) to resistance to recovery. Identifying predictors of these trajectories is essential for targeted interventions. This study aimed to investigate baseline structural MRI features and clinical factors associated with both rate of recovery and the likelihood of resistance to it, using a penalized mixture cure model (MCM).
Methods: Data from 185 individuals with a baseline CDR = 0.5 in the OASIS-3 database were analyzed. Structural MRI features and clinical measures were assessed using the latency and incidence components of an MCM. The latency component evaluated factors influencing recovery rates, while the incidence component identified predictors of resistance.
Results: The latency component revealed that increasing right rostral middle frontal thickness (HR = 2.06) was linked to faster recovery, while right frontal pole thickness (HR = 0.48) predicted slower recovery. The cure component identified left bankssts volume (OR = 2.21) as a key predictor of resistance, whereas left parsorbitalis thickness (OR = 0.56) was protective. Notably, right supramarginal thickness was paradoxically associated with both faster recovery (HR = 1.24) and increased resistance (OR = 1.48), potentially acting as a proxy for both compensatory mechanisms and maladaptive changes.
Conclusions: The MCM revealed complex, context-dependent roles of structural MRI features in recovery and resistance trajectories, with frontal and temporal regions pivotal to cognitive outcomes. These findings highlight the value of MCM in advancing personalized therapeutic strategies and understanding recovery dynamics.
Methods: Data from 185 individuals with a baseline CDR = 0.5 in the OASIS-3 database were analyzed. Structural MRI features and clinical measures were assessed using the latency and incidence components of an MCM. The latency component evaluated factors influencing recovery rates, while the incidence component identified predictors of resistance.
Results: The latency component revealed that increasing right rostral middle frontal thickness (HR = 2.06) was linked to faster recovery, while right frontal pole thickness (HR = 0.48) predicted slower recovery. The cure component identified left bankssts volume (OR = 2.21) as a key predictor of resistance, whereas left parsorbitalis thickness (OR = 0.56) was protective. Notably, right supramarginal thickness was paradoxically associated with both faster recovery (HR = 1.24) and increased resistance (OR = 1.48), potentially acting as a proxy for both compensatory mechanisms and maladaptive changes.
Conclusions: The MCM revealed complex, context-dependent roles of structural MRI features in recovery and resistance trajectories, with frontal and temporal regions pivotal to cognitive outcomes. These findings highlight the value of MCM in advancing personalized therapeutic strategies and understanding recovery dynamics.
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