Assessing Aβ status before disease-modifying therapies: Findings from a 10-year real-world study

22/11/2024

On 22 November, a study published in Alzheimer's Disease & Dementia: Diagnosis, Assessment & Disease Monitoring explored how amyloid beta (Aβ) status can be assessed efficiently in patients with suspected Alzheimer's disease (AD) ahead of potential treatment with disease-modifying therapies. The research team, led by Matthias Brendel, used data collected over a 10-year period through two independent cohorts in university memory clinics. With the emergence of disease-modifying therapies, accurately determining Aβ pathology is essential for patients with suspected AD. The study evaluated Aβ levels in cerebrospinal fluid (CSF) and positron emission tomography (PET) in real-world clinical settings to propose a practical diagnostic algorithm. The study included 402 patients from Ludwig Maximilian University in Germany and 144 patients from the Medical University of Vienna. The researchers compared CSF Aβ42/40 ratios with Aβ PET scans to determine optimal thresholds and validated these findings across both cohorts. 

Results showed that a CSF Aβ42/40 ratio of ≥ 7.1% was associated with a low risk of a positive Aβ PET scan (negative predictive value: 94.3%). For patients with intermediate results (CSF Aβ42/40 ratio between 5.5% and 7.1%, defined by the authors as borderline levels), Aβ PET imaging was beneficial, with 44% to 52% of these patients testing positive for Aβ pathology. The study supports a two-cutoff approach, combining CSF Aβ42/40 testing and Aβ PET imaging for intermediate cases. This approach provides a cost-effective and reliable way to assess Aβ status in clinical practice, ensuring that appropriate patients are identified for potential treatment with disease-modifying therapies. As anti-amyloid therapies approach potential approval in Europe, these findings could guide clinicians in optimising biomarker assessments. The two-cutoff method helps reduce unnecessary PET scans while ensuring accurate diagnosis. The study has been published open access and can be read here: https://doi.org/10.1002/dad2.70031