Alzheimer's Biomarker Testing Surged 7-Fold After New Drug Approvals
A memory clinic study finds 70% of patients tested positive for Alzheimer's pathology, with testing volumes exploding since new treatments arrived.
Summary
Researchers at Washington University tracked Alzheimer's biomarker testing across 1,136 memory clinic patients between 2021 and 2025. Testing volume increased seven-fold over four years, driven largely by the approval of amyloid-targeting therapies like lecanemab and donanemab. Across all testing methods — amyloid PET scans, cerebrospinal fluid analysis, and blood tests — roughly 70% of patients tested positive for Alzheimer's pathology. Positivity rates were higher in older patients, women, and White individuals, and lower in those with hypertension or diabetes. The findings highlight how new disease-modifying treatments are rapidly reshaping diagnostic practice and underscore the importance of understanding who is most likely to test positive when being evaluated for these therapies.
Detailed Summary
The approval of amyloid-targeting Alzheimer's therapies has fundamentally changed how memory clinics operate. For the first time, confirming the presence of amyloid pathology is not just academically useful — it is a prerequisite for treatment eligibility. This study captures how that shift played out in real-world clinical practice at a leading academic memory center.
Researchers at Washington University's Memory Diagnostic Center retrospectively analyzed electronic health records from 1,136 patients who received at least one Alzheimer's biomarker test for clinical purposes between June 2021 and March 2025. Tests included amyloid PET imaging (455 scans), cerebrospinal fluid (CSF) analysis (505 tests), and blood-based biomarkers (242 tests). The cohort had a median age of 73.2 years, was 52% female, and was 93% White.
The headline finding is a seven-fold increase in biomarker testing volume over just four years — a dramatic acceleration that closely tracks the FDA approvals of lecanemab (2023) and donanemab (2024). Across all three testing modalities, approximately 70% of patients tested positive for Alzheimer's pathology, a notably high rate that reflects the pre-selected nature of memory clinic populations.
Positivity rates varied meaningfully by patient characteristics. Older age, female sex, and White race were associated with higher positivity, while hypertension and diabetes were associated with lower rates. These associations likely reflect both biological differences in amyloid accumulation and referral patterns within the clinic.
For clinicians, these findings provide a real-world benchmark for expected positivity rates and highlight demographic factors that may influence pre-test probability. For health systems, the seven-fold testing surge signals significant resource and infrastructure demands ahead. Limitations include the single-center design, a predominantly White patient population, and the fact that this summary is based on the abstract only.
Key Findings
- Alzheimer's biomarker testing increased seven-fold at a major memory clinic between 2021 and 2025.
- Approximately 70% of tested patients were positive for Alzheimer's pathology across all modalities.
- Older age, female sex, and White race were linked to higher biomarker positivity rates.
- Hypertension and diabetes were associated with lower rates of amyloid positivity.
- Testing surge closely follows FDA approvals of amyloid-targeting therapies lecanemab and donanemab.
Methodology
Retrospective analysis of electronic health records from 1,136 patients at Washington University's Memory Diagnostic Center who received at least one clinical Alzheimer's biomarker test between June 2021 and March 2025. Three modalities were assessed: amyloid PET (n=455), CSF testing (n=505), and blood-based biomarkers (n=242). No control group was included given the observational, descriptive design.
Study Limitations
This is a single-center study from an academic memory clinic with a predominantly White patient population (93%), limiting generalizability to more diverse or community-based settings. The retrospective design and reliance on electronic health records may introduce selection and documentation biases. This summary is based on the abstract only, as the full text was not available for review.
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