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EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects
Gouw AA, Alsema AM, Tijms BM, Borta A, Scheltens P, Stam CJ, van der Flier WM.. Neurobiology of aging, 2017-06-01
Topic: Amyloid, tau and blood-test diagnosis
We studied whether electroencephalography (EEG)-derived measures of brain oscillatory activity are related to clinical progression in nondemented, amyloid positive subjects. We included 205 nondemented amyloid positive subjects (63 subjective cognitive decline [SCD]; 142 mild cognitive impairment [MCI]) with a baseline resting-state EEG data and ≥1-year follow-up. Peak frequency and relative power of 4 frequency bands were calculated. Relationships between normalized EEG measures and time to clinical progression (conversion from SCD to MCI/dementia or from MCI to dementia) were analyzed using Cox proportional hazard models. One hundred eight (53%) subjects clinically progressed after 2.1 (IQR 1.3-3.0) years. In the total sample, none of the EEG spectral measures were significant predictors. Stratified for baseline diagnosis, we found that in SCD patients higher delta and theta power (HR [95% CI] = 1.7 [1.0-2.7] resp. 2.3 [1.2-4.4]), and lower alpha power and peak frequency (HR [95% CI] = 0.5 [0.3-1.0] resp. 0.6 [0.4-1.0]) were associated with clinical progression over time. In amyloid positive subjects with normal cognition, slowing of oscillatory brain activity is related to clinical progression.
Key findings
- In the total sample, none of the EEG spectral measures were significant predictors.
- Stratified for baseline diagnosis, we found that in SCD patients higher delta and theta power (HR [95% CI] = 1.7 [1.0-2.7] resp. 2.3 [1.2-4.4]), and lower alpha power and peak frequency (HR [95% CI] = 0.5 [0.3-1.0] resp. 0.6 [0.4-1.0]) were associated with clinical progression over time.
Why it matters
In the total sample of nondemented amyloid-positive subjects, no EEG spectral measure significantly predicted clinical progression. Only in the subgroup with subjective cognitive decline were higher delta and theta power and lower alpha power and peak frequency associated with progression, so this is a preliminary finding.
Study details
- Participants205
- Evidence strengthLow
How this study scored 52/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Neurobiology of aging) |
| Journal's citation record | 3 / 4 | Neurobiology of Aging: journal h-index 263 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2017 — within 10 year(s) of the newest study here |
| Sample size | 2 / 4 | 205 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 5 / 7 | Cited 153 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 13.9 citations a year over 11 year(s) since 2017 |
| Impact for its field and year | 3 / 6 | Cited 7.0× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 7 other studies in this library |
| Still being cited | 3 / 4 | Cited 58 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Wiesje M. van der Flier: h-index 132 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Amsterdam UMC Location Vrije Universiteit Amsterdam: institution h-index 938 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 3 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 28646686) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 52 / 100 | — |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Gouw, A. A., Alsema, A. M., Tijms, B. M., Borta, A., Scheltens, P., Stam, C. J., et al. (2017). EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects. Neurobiology of aging. https://doi.org/10.1016/j.neurobiolaging.2017.05.017
Vancouver
Gouw AA, Alsema AM, Tijms BM, Borta A, Scheltens P, Stam CJ, et al. EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects. Neurobiology of aging. 2017. doi:10.1016/j.neurobiolaging.2017.05.017. PMID: 28646686.
BibTeX
@article{gouw2017-28646686,
author = {Gouw, A. A. and Alsema, A. M. and Tijms, B. M. and Borta, A. and Scheltens, P. and Stam, C. J. and van der Flier, W. M.},
title = {{EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects}},
journal = {Neurobiology of aging},
year = {2017},
doi = {10.1016/j.neurobiolaging.2017.05.017},
pmid = {28646686},
url = {https://doi.org/10.1016/j.neurobiolaging.2017.05.017}
}
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