Abstract
Significant progress has been made in expanding our understanding of prodromal Parkinson disease (PD), particularly for recognition of early motor and nonmotor signs and symptoms. Although identification of these prodromal features may improve our understanding of the earliest stages of PD, they are individually insufficient for early disease detection and enrollment of participants in prevention trials in most cases because of low sensitivity, specificity, and positive predictive value. Composite cohorts, composed of individuals with multiple co-occurring prodromal features, are an important resource for conducting prodromal PD research and eventual prevention trials because they are more representative of the population at risk for PD, allow investigators to evaluate the efficacy of an intervention across individuals with varying prodromal feature patterns, are able to produce larger sample sizes, and capture individuals at different stages of prodromal PD. A key challenge in identifying individuals with prodromal disease for composite cohorts and prevention trial participation is that we know little about the natural history of prodromal PD. To move toward prevention trials, it is critical that we better understand common prodromal feature patterns and be able to predict the probability of progression and phenoconversion. Ongoing research in cohort studies and administrative databases is beginning to address these questions, but further longitudinal analyses in a large population-based sample are necessary to provide a convincing and definitive strategy for identifying individuals to be enrolled in a prevention trial.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Cited by
8 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献