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Published on: May 31, 2017
Reinventing "N" in the A/T/N framework: The case for digital
Rhoda Au1, Zachary Popp2, Spencer Low2
1Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA 02118; Boston University Alzheimer's Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA 02118; Departments of Neurology, Medicine, and Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine School of Medicine, Boston, MA, USA 02118; Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA 02118.
Digital measures offer accurate early Alzheimer's disease (AD) detection, complementing amyloid (A) and tau (T) biomarkers. Re-evaluating the A/T/N framework with digital tools is crucial for effective clinical trials and treatments.
Area of Science:
- Neurology
- Biomarkers
- Digital Health
Background:
- Alzheimer's disease (AD) diagnosis improved with amyloid (A), tau (T), and neurodegeneration (N) biomarkers.
- Clinical expression of AD pathology is not fully predictable, creating knowledge gaps for treatment decisions.
- Current assessment tools are insufficient for early-stage detection and monitoring of AD.
Purpose of the Study:
- To advocate for a re-evaluation of the existing A/T/N diagnostic framework for Alzheimer's disease.
- To highlight the potential of digital measures in complementing or replacing non-specific neurodegeneration markers.
- To emphasize the need for research into novel digital evaluation tools for early AD detection and clinical trial advancement.
Main Methods:
- Review of current diagnostic biomarkers for Alzheimer's disease (A, T, N).
- Analysis of evidence supporting the efficacy of digital measures in early disease detection.
- Conceptual framework proposed for integrating digital evaluation into AD diagnostics.
Main Results:
- Digital measures demonstrate accurate detection capabilities in early stages of Alzheimer's disease.
- The presence of AD pathology does not consistently correlate with clinical symptoms.
- Existing diagnostic tools limit the identification and monitoring of preclinical and early AD.
Conclusions:
- Digital evaluation tools are essential for advancing Alzheimer's disease clinical trials and treatment decisions.
- A revised A/T/N framework incorporating digital measures is proposed.
- Further research and support for novel digital evaluation tools are critical for Alzheimer's disease diagnosis and management.
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