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Digital biomarker-based individualized prognosis for people at risk of dementia
Buegler M, Harms R, Balasa M, Meier IB, Exarchos T, Rai L, Boyle R, Tort A et al.. Alzheimer's & dementia (Amsterdam, Netherlands), 2020-08-19
Topic: Risk, prevention and care in population studies
Background Research investigating treatments and interventions for cognitive decline fail due to difficulties in accurately recognizing behavioral signatures in the presymptomatic stages of the disease. For this validation study, we took our previously constructed digital biomarker-based prognostic models and focused on generalizability and robustness of the models. Method We validated prognostic models characterizing subjects using digital biomarkers in a longitudinal, multi-site, 40-month prospective study collecting data in memory clinics, general practitioner offices, and home environments. Results Our models were able to accurately discriminate between healthy subjects and individuals at risk to progress to dementia within 3 years. The model was also able to differentiate between people with or without amyloid neuropathology and classify fast and slow cognitive decliners with a very good diagnostic performance. Conclusion Digital biomarker prognostic models can be a useful tool to assist large-scale population screening for the early detection of cognitive impairment and patient monitoring over time.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Buegler, M., Harms, R., Balasa, M., Meier, I. B., Exarchos, T., Rai, L., et al. (2020). Digital biomarker-based individualized prognosis for people at risk of dementia. Alzheimer's & dementia (Amsterdam, Netherlands). https://doi.org/10.1002/dad2.12073
Vancouver
Buegler M, Harms R, Balasa M, Meier IB, Exarchos T, Rai L, et al. Digital biomarker-based individualized prognosis for people at risk of dementia. Alzheimer's & dementia (Amsterdam, Netherlands). 2020. doi:10.1002/dad2.12073. PMID: 32832589.
BibTeX
@article{buegler2020-32832589,
author = {Buegler, M. and Harms, R. and Balasa, M. and Meier, I. B. and Exarchos, T. and Rai, L. and Boyle, R. and Tort, A. and others},
title = {{Digital biomarker-based individualized prognosis for people at risk of dementia}},
journal = {Alzheimer's \& dementia (Amsterdam, Netherlands)},
year = {2020},
doi = {10.1002/dad2.12073},
pmid = {32832589},
url = {https://doi.org/10.1002/dad2.12073}
}
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Key findings
- Results Our models were able to accurately discriminate between healthy subjects and individuals at risk to progress to dementia within 3 years.
Why it matters
This validation study found that digital biomarker-based prognostic models could discriminate between healthy subjects and individuals at risk of progressing to dementia within 3 years. The models could also differentiate people with or without amyloid neuropathology and classify fast and slow cognitive decliners.
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Study details
- Study designlongitudinal study
- Evidence strengthModerate
How this study scored 55/100
Published in a leading specialty journal, and it is a longitudinal study following the same people over time. Scored zero for sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 9 / 10 | Tier 2 — leading specialty journal (Alzheimer's & dementia (Amsterdam, Netherlands)) |
| Journal's citation record | 1 / 4 | Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring: journal h-index 86 (OpenAlex, 2026-10-29) |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2020 — within 10 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 4 / 7 | Cited 63 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 7.9 citations a year over 8 year(s) since 2020 |
| Impact for its field and year | 3 / 6 | Cited 5.9× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 1 other studies in this library |
| Still being cited | 2 / 4 | Cited 26 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Ioannis Tarnanas: h-index 24 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | Johns Hopkins University: institution h-index 2,306 (OpenAlex) |
| Multi-centre collaboration | 3 / 3 | OpenAlex lists 19 institution(s) in 7 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 32832589) |
| Free to read | 2 / 2 | Free to read |
| Total | 55 / 100 | — |
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Read the original
- DOI: 10.1002/dad2.12073
- PubMed: 32832589
- Original source →
- Free full text: Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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