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Integrating MRI Volume and Plasma p-Tau217 for Amyloid Risk Stratification in Early-Stage Alzheimer Disease
Sohyun Yim, Seongbeom Park, Kyoungyoon Lim, Heekyung Kang, Daeun Shin, Hyunjin Jo, Hyemin Jang, Michael Walter Weiner et al.. Neurology, 2025-08-19
Topic: Amyloid, tau and blood-test diagnosis
A total of 807 K-ROAD participants (median age 72.0 years, 58.7% female) and 230 ADNI participants (median age 70.9 years, 49.1% female) were analyzed. Using a 95% sensitivity/specificity strategy, the low-risk group demonstrated NPVs of 94.7% (91.7%-97.7%, K-ROAD) and 99.0% (97.0%-100.0%, ADNI). The high-risk group showed PPVs of 97.6% (95.9%-99.3%, K-ROAD) and 98.8% (96.5%-100.0%, ADNI). Intermediate-risk groups comprised 33.3% (K-ROAD) and 20.9% (ADNI) of participants. Plasma p-tau217 testing in intermediate-risk groups yielded PPVs of 92.5% (88.7%-96.3%, K-ROAD) and 90.0% (79.0%-100.0%, ADNI) and NPVs of 83.1% (75.0%-91.2%, K-ROAD) and 83.3% (66.1%-100.0%, ADNI). The overall workflow accuracy was 94.2% (92.6%-95.8%, K-ROAD) and 96.5% (94.1%-98.9%, ADNI). The 2-stage diagnostic workflow integrating MRI-based risk stratification and plasma p-tau217 testing accurately identified individuals with Aβ PET positivity in early-stage AD, substantially reducing the need for additional biomarker testing. However, the generalizability may be limited by modest incremental improvement over baseline models and limited racial and ethnic diversity.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Yim, S., Park, S., Lim, K., Kang, H., Shin, D., Jo, H., et al. (2025). Integrating MRI Volume and Plasma p-Tau217 for Amyloid Risk Stratification in Early-Stage Alzheimer Disease. Neurology. https://doi.org/10.1212/wnl.0000000000213954
Vancouver
Yim S, Park S, Lim K, Kang H, Shin D, Jo H, et al. Integrating MRI Volume and Plasma p-Tau217 for Amyloid Risk Stratification in Early-Stage Alzheimer Disease. Neurology. 2025. doi:10.1212/wnl.0000000000213954. PMID: 40829110.
BibTeX
@article{yim2025-40829110,
author = {Yim, Sohyun and Park, Seongbeom and Lim, Kyoungyoon and Kang, Heekyung and Shin, Daeun and Jo, Hyunjin and Jang, Hyemin and Weiner, Michael Walter and others},
title = {{Integrating MRI Volume and Plasma p-Tau217 for Amyloid Risk Stratification in Early-Stage Alzheimer Disease}},
journal = {Neurology},
year = {2025},
doi = {10.1212/wnl.0000000000213954},
pmid = {40829110},
url = {https://doi.org/10.1212/wnl.0000000000213954}
}
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's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
Key findings
- A total of 807 K-ROAD participants (median age 72.0 years, 58.7% female) and 230 ADNI participants (median age 70.9 years, 49.1% female) were analyzed.
- Using a 95% sensitivity/specificity strategy, the low-risk group demonstrated NPVs of 94.7% (91.7%-97.7%, K-ROAD) and 99.0% (97.0%-100.0%, ADNI).
- The high-risk group showed PPVs of 97.6% (95.9%-99.3%, K-ROAD) and 98.8% (96.5%-100.0%, ADNI).
- Intermediate-risk groups comprised 33.3% (K-ROAD) and 20.9% (ADNI) of participants.
- Plasma p-tau217 testing in intermediate-risk groups yielded PPVs of 92.5% (88.7%-96.3%, K-ROAD) and 90.0% (79.0%-100.0%, ADNI) and NPVs of 83.1% (75.0%-91.2%, K-ROAD) and 83.3% (66.1%-100.0%, ADNI).
Why it matters
A two-stage workflow using MRI-based risk grouping plus plasma p-tau217 testing accurately identified amyloid PET positivity in early-stage Alzheimer's disease while reducing the need for extra biomarker tests. The authors note the improvement over baseline models was modest and the sample had limited racial and ethnic diversity.
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Study details
- Study designcohort study
- Participants807
- Effect size58.7%; 49.1%; 94.7%
- Evidence strengthModerate
How this study scored 63/100
Published in a leading specialty journal, and it is a cohort study following people over time. Scored zero for randomized / blinded because the record does not state it. We have no data on senior author's track record, so that was left out: it earned 60 of the 96 points we could judge it on, which is 63 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 9 / 10 | Tier 2 — leading specialty journal (Neurology) |
| Journal's citation record | 4 / 4 | Neurology: journal h-index 525 (OpenAlex, 2026-10-29) |
| Study design | 7 / 12 | A cohort study following 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 | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 2 / 4 | 807 participants |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 2 / 7 | Cited 6 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 2.0 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 3 / 6 | Cited 3.8× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 6 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | 2 / 3 | University College London: institution h-index 2,029 (OpenAlex) |
| Multicenter collaboration | 3 / 3 | OpenAlex lists 25 institution(s) in 7 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40829110) |
| Free to read | 2 / 2 | Free to read |
| Points | 60 / 96 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 60 of the 96 points we could judge it on is 63 out of 100. |
| Total | 63 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
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