Reinventing “N” in the A/T/N framework: The case for digital

TL;DR

The paper argues for integrating digital evaluation tools into Alzheimer's disease diagnosis to improve early detection and treatment decisions.

Contribution

The paper proposes redefining the 'N' in the A/T/N framework by incorporating digital measures for more accurate and clinically relevant Alzheimer's diagnosis.

Findings

Digital measures can accurately detect Alzheimer's disease at early stages.

Current diagnostic tools are outdated and hinder early detection and monitoring.

Digital evaluation tools could replace non-specific neurodegeneration markers in the A/T/N framework.

Abstract

Breakthroughs in biomarkers for amyloid (A), tau (T), and neurodegeneration (N) have advanced the prospects of accurate Alzheimer’s disease (AD) diagnosis. However, presence of pathology does not always translate into clinical expression and there are still clear knowledge gaps as to whether someone with AD biological indicators will lead to clinically apparent disease necessary to warrant drug treatments that carry toxicity risk. Reliance on decades-old assessment tools inhibits detection and monitoring at preclinical and early disease stages when new treatments could prove most effective. Evidence has accumulated that digital measures provide accurate detection of disease at early stages. We call for a re-evaluation of the A/T/N diagnostic framework, with digital evaluation measures complementing non-AD specific neurodegeneration markers, and even potentially replacing those non-specific to AD, to provide a clinically relevant feature critical to clinical trial advances and treatment decisions. Achieving this will only be possible if further research into novel digital evaluation tools is pursued with the same support and consideration as amyloid and tau.