Real‐world evidence in Alzheimer's disease: The ROADMAP Data Cube. Issue 3 (6th January 2020)

• Record Type: Journal Article
• Authors: Janssen, Olin; Vos, Stephanie J. B.; García‐Negredo, Glòria; Tochel, Claire; Gustavsson, Anders; Smith, Michael; Ly, Amanda; Nelson, Mia; Baldwin, Helen; Sudlow, Catherine; Bexelius, Christin; Jindra, Christoph; Vaci, Nemanja; Bauermeister, Sarah; Gallacher, John; Ponjoan, Anna; Dufouil, Carole; Garre Olmo, Josep; Pedersen, Lars; Skoog, Ingmar; Hottgenroth, Antje; Visser, Pieter Jelle; van der Lei, Johan; Diaz, Carlos
• Is Part Of: Alzheimer's & dementia. Volume 16:Issue 3(2020)
• Page Start: 461
• Page End: 471
• Publication Date: 2020-01-06
• Subjects: Alzheimer's disease -- Disease spectrum -- Gap analysis -- Outcomes -- Real‐world data -- ROADMAP project -- Stakeholders; Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1016/j.jalz.2019.09.087
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Introduction: The ROADMAP project aimed to provide an integrated overview of European real‐world data on Alzheimer's disease (AD) across the disease spectrum. Methods: Metadata were identified from data sources in catalogs of European AD projects. Priority outcomes for different stakeholders were identified through systematic literature review, patient and public consultations, and stakeholder surveys. Results: Information about 66 data sources and 13 outcome domains were integrated into a Data Cube. Gap analysis identified cognitive ability, functional ability/independence, behavioral/neuropsychiatric symptoms, treatment, comorbidities, and mortality as the outcomes collected most. Data were most lacking in caregiver‐related outcomes. In general, electronic health records covered a broader, less detailed data spectrum than research cohorts. Discussion: This integrated real‐world AD data overview provides an intuitive visual model that facilitates initial assessment and identification of gaps in relevant outcomes data to inform future prospective data collection and matching of data sources and outcomes against research protocols.