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Generating real‐world evidence in Alzheimer's disease: Considerations for establishing a core dataset

James E. Galvin, Jeffrey L. Cummings, Mihaela Levitchi Benea, Carl de Moor, Ricardo Allegri, Alireza Atri, Howard Chertkow, Claire Paquet, Verna R. Porter, Craig Ritchie, Sietske A.M. Sikkes, Michael R. Smith, Christina M. Grassi, Ivana Rubino

2024Alzheimer s & Dementia19 citationsDOIOpen Access PDF

Abstract

Ongoing assessment of patients with Alzheimer's disease (AD) in postapproval studies is important for mapping disease progression and evaluating real-world treatment effectiveness and safety. However, interpreting outcomes in the real world is challenging owing to variation in data collected across centers and specialties and greater heterogeneity of patients compared with trial participants. Here, we share considerations for observational postapproval studies designed to collect harmonized longitudinal data from individuals with mild cognitive impairment or mild dementia stage of disease who receive therapies targeting the underlying pathological processes of AD in routine practice. This paper considers key study design parameters, including proposed aims and objectives, study populations, approaches to data collection, and measures of cognition, functional abilities, neuropsychiatric status, quality of life, health economics, safety, and drug utilization. Postapproval studies that capture these considerations will be important to provide standardized data on AD treatment effectiveness and safety in real-world settings.

Topics & Concepts

Observational studyDementiaReal world dataReal world evidenceDiseaseMedicineCognitionQuality of life (healthcare)Data collectionData sciencePsychiatryComputer sciencePathologyInternal medicineMathematicsStatisticsNursingDementia and Cognitive Impairment ResearchHealth Systems, Economic Evaluations, Quality of LifeAdvanced Causal Inference Techniques
Generating real‐world evidence in Alzheimer's disease: Considerations for establishing a core dataset | Litcius