Generating real‐world evidence in early Alzheimer's disease: Considerations for applying the target trial emulation framework to study the safety of anti‐amyloid therapies
Abstract Anti‐amyloid beta monoclonal antibodies (anti‐Aβ mAbs) have received approval from the US Food and Drug Administration for the treatment of patients with mild cognitive impairment or mild dementia due to Alzheimer's disease (collectively known as early AD) based on evidence from clinic...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-04-01
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| Series: | Alzheimer’s & Dementia: Translational Research & Clinical Interventions |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/trc2.70080 |
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| Summary: | Abstract Anti‐amyloid beta monoclonal antibodies (anti‐Aβ mAbs) have received approval from the US Food and Drug Administration for the treatment of patients with mild cognitive impairment or mild dementia due to Alzheimer's disease (collectively known as early AD) based on evidence from clinical trials. However, whether findings from these trials are generalizable to the real world is uncertain. We need reliable evidence on the real‐world safety of these treatments to inform decision making for clinicians, patients, and caregivers. Using lecanemab as an exemplar, we outline the key considerations in designing and implementing an observational study on safety and utilization outcomes using established administrative healthcare claims data sources with the target trial emulation framework. The target trial emulation framework is a rigorous causal inference framework that minimizes common biases in observational studies. The approach proposed here can be applied to evaluation of additional mAbs as they become available. Highlights Little is known about real‐world safety of anti‐amyloid beta monoclonal antibodies for early Alzheimer's disease. Existing real‐world data can support studies of their safety and utilization outcomes. Target trial emulation can guide the design of these studies while minimizing bias. We provide key design and analytical considerations for future studies. |
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| ISSN: | 2352-8737 |