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Individualized prediction of transition from subjective cognitive decline to mild cognitive impairment based on multimodal MRI: a 10-year follow-up study
Xingyan Le, Junbang Feng, Xiaoli Yu, Yuyin Wang, Qingbiao Zhang, Yuwei Xia, Feng Shi, Chuanming Li. The Journal of Prevention of Alzheimer s Disease, 2026-01-01
Topic: Risk, prevention and care in population studies
The model incorporating age, brain volume, functional, and radiomics features demonstrated the highest predictive performance for SCD progression in training (C-index: 0.962; 95 % CI: 0.95-0.98) and testing (C-index: 0.911; 95 % CI: 0.861-0.968) sets. A nomogram comprising 10 predictors was constructed to estimate individualized risk of progression to MCI at 5-/7-/10-year. The calibration curve showed good agreement between predicted and observed values. Decision curve analysis demonstrated the nomogram had substantial clinical value. This multivariate model and nomogram could accurately predict the individual progression from SCD to MCI.
Key findings
- The model incorporating age, brain volume, functional, and radiomics features demonstrated the highest predictive performance for SCD progression in training (C-index: 0.962; 95 % CI: 0.95-0.98) and testing (C-index: 0.911; 95 % CI: 0.861-0.968) sets.
- A nomogram comprising 10 predictors was constructed to estimate individualized risk of progression to MCI at 5-/7-/10-year.
- The calibration curve showed good agreement between predicted and observed values.
- Decision curve analysis demonstrated the nomogram had substantial clinical value.
- This multivariate model and nomogram could accurately predict the individual progression from SCD to MCI.
Why it matters
This study developed a model using age, brain volume, functional, and radiomics features from MRI that accurately predicted progression from subjective cognitive decline to mild cognitive impairment over 10 years. This could help identify individuals for monitoring or early intervention, but no treatment is tested.
Study details
- Participants89
- Evidence strengthLow
How this study scored 38/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / 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 36 of the 96 points we could judge it on, which is 38 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (The Journal of Prevention of Alzheimer s Disease) |
| Journal's citation record | 0 / 4 | The Journal of Prevention of Alzheimer s Disease: journal h-index 63 (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 | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 1 / 4 | 89 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 | 1 / 7 | Cited 1 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.5 citations a year over 2 year(s) since 2026 |
| Impact for its field and year | 3 / 6 | Cited 4.7× 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 | 0 / 4 | Cited 1 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | — / 4 | OpenAlex's profile for last-listed author Chuanming Li holds only 6 work(s), too few to judge a track record — left out of this score |
| Institution's track record | 0 / 3 | Chongqing University: institution h-index 493 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 3 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41478831) |
| Free to read | 2 / 2 | Free to read |
| Points | 36 / 96 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 36 of the 96 points we could judge it on is 38 out of 100. |
| Total | 38 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1016/j.tjpad.2025.100462
- PubMed: 41478831
- Original source →
- Free full text: The Journal of Prevention of Alzheimer s Disease →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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 8 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
Le, X., Feng, J., Yu, X., Wang, Y., Zhang, Q., Xia, Y., et al. (2026). Individualized prediction of transition from subjective cognitive decline to mild cognitive impairment based on multimodal MRI: a 10-year follow-up study. The Journal of Prevention of Alzheimer s Disease. https://doi.org/10.1016/j.tjpad.2025.100462
Vancouver
Le X, Feng J, Yu X, Wang Y, Zhang Q, Xia Y, et al. Individualized prediction of transition from subjective cognitive decline to mild cognitive impairment based on multimodal MRI: a 10-year follow-up study. The Journal of Prevention of Alzheimer s Disease. 2026. doi:10.1016/j.tjpad.2025.100462. PMID: 41478831.
BibTeX
@article{le2026-41478831,
author = {Le, Xingyan and Feng, Junbang and Yu, Xiaoli and Wang, Yuyin and Zhang, Qingbiao and Xia, Yuwei and Shi, Feng and Li, Chuanming},
title = {{Individualized prediction of transition from subjective cognitive decline to mild cognitive impairment based on multimodal MRI: a 10-year follow-up study}},
journal = {The Journal of Prevention of Alzheimer s Disease},
year = {2026},
doi = {10.1016/j.tjpad.2025.100462},
pmid = {41478831},
url = {https://doi.org/10.1016/j.tjpad.2025.100462}
}
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