Dementia Data Landscape 1. Cohorts

Journal article

INTRODUCTION: Understanding and maximizing complex health data is crucial for accelerating discovery, translational research, funding priorities, and improving data management. Rapid, cost‐effective progress can be made by repurposing datasets. This work explores the dementia cohort landscape, identifies cohorts relevant to dementia translation, and highlights areas to strengthen health cohort infrastructure. METHOD: PubMed was searched for publications utilizing dementia‐related cohorts (1970–2024), supplemented by international dementia data platforms. A template aligned with the C‐Surv data model was used to summarize administrative details and the presence of measurements across 17 themes. RESULTS: From 4596 publications and 11 data platforms, 883 cohorts were identified (558 population and 325 clinical). Of these, 74% indicated data availability for future research, though metadata reporting varied. Cohort metadata are accessible via the landscape tool. DISCUSSION: This work reveals extensive global dementia‐related data for repurposing and identifies priority areas for improvement, including metadata transparency, data accessibility, and locations to prioritize for future research. Highlights: A total of 883 cohorts were identified globally (1970 to 2024): 558 population and 325 clinical The Global South is substantially underrepresented Seventy‐four percent of cohorts offer data access, but protocols and metadata quality vary widely Only 45% of cohorts were discoverable via existing data platforms The online landscape tool enables strategic discovery and reuse of dementia data

Authors: Morgan, A; Durkin, C; Tari, B; Squires, E; Young, S

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Alzheimer's & Dementia: The Journal of the Alzheimer's Association
• Volume: 21
• Issue: 11
• Article number: e70901
• Publication date: 2025-11-21
• Acceptance date: 2025-10-13
• DOI: 10.1002/alz.70901
• EISSN: 1552-5279
• ISSN: 1552-5260
• Language: English
• Keywords: data access; dataset discovery; data characterization; C‐Surv; clinical cohort; data reuse; dementia; metadata; Alzheimer's disease; cohort study; population cohort; data landscape; data repurpose