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Development of a novel dementia risk prediction model in the general population: A large, longitudinal, population-based machine-learning study
You J, Zhang YR, Wang HF, Yang M, Feng JF, Yu JT, Cheng W.. EClinicalMedicine, 2022-09-23
Topic: Risk, prevention and care in population studies
Our prediction model was internally evaluated based on five-fold cross-validation on discrimination and calibration, and it was further compared with existing prediction scales. The model was internally validated in the general population of European ancestry and White ethnicity; thus, further validation with independent datasets is necessary to confirm these findings.
Key findings
- Our prediction model was internally evaluated based on five-fold cross-validation on discrimination and calibration, and it was further compared with existing prediction scales.
- The model was internally validated in the general population of European ancestry and White ethnicity; thus, further validation with independent datasets is necessary to confirm these findings.
Why it matters
This study used machine learning on a large, long-running population sample to build a tool that estimates a person's chance of developing dementia. The authors tested it only inside their own data (five-fold cross-validation, checking both how well it separated people and how accurate its risk estimates were) and compared it with existing risk scales. They say it was validated only in people of European ancestry and White ethnicity and needs testing in independent datasets before the findings can be confirmed; it is a prediction tool, not a treatment or prevention.
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Study details
- Study designlongitudinal study
- Participants2,416
- Effect sizeAUC 0.848; AUC 0.862; AUC 0.705
- Evidence strengthModerate
How this study scored 69/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (EClinicalMedicine) |
| Journal's citation record | 2 / 4 | EClinicalMedicine: journal h-index 150 (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 | 3 / 5 | 2022 — within 6 year(s) of the newest study here |
| Sample size | 3 / 4 | 2,416 participants |
| Effect reported | 3 / 3 | Effect reported with a statistic (interval, p-value, ratio or similar) |
| 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 105 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 17.5 citations a year over 6 year(s) since 2022 |
| Impact for its field and year | 4 / 6 | Cited 12.2× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 3 / 6 | Cited by 12 other studies in this library |
| Still being cited | 3 / 4 | Cited 84 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Wei Cheng: h-index 53 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Fudan University: institution h-index 954 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 36187723) |
| Free to read | 2 / 2 | Free to read |
| Total | 69 / 100 | — |
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Read the original
- DOI: 10.1016/j.eclinm.2022.101665
- PubMed: 36187723
- Original source →
- Free full text: EClinicalMedicine →
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 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
You, J., Zhang, Y. R., Wang, H. F., Yang, M., Feng, J. F., Yu, J. T., et al. (2022). Development of a novel dementia risk prediction model in the general population: A large, longitudinal, population-based machine-learning study. EClinicalMedicine. https://doi.org/10.1016/j.eclinm.2022.101665
Vancouver
You J, Zhang YR, Wang HF, Yang M, Feng JF, Yu JT, et al. Development of a novel dementia risk prediction model in the general population: A large, longitudinal, population-based machine-learning study. EClinicalMedicine. 2022. doi:10.1016/j.eclinm.2022.101665. PMID: 36187723.
BibTeX
@article{you2022-36187723,
author = {You, J. and Zhang, Y. R. and Wang, H. F. and Yang, M. and Feng, J. F. and Yu, J. T. and Cheng, W.},
title = {{Development of a novel dementia risk prediction model in the general population: A large, longitudinal, population-based machine-learning study}},
journal = {EClinicalMedicine},
year = {2022},
doi = {10.1016/j.eclinm.2022.101665},
pmid = {36187723},
url = {https://doi.org/10.1016/j.eclinm.2022.101665}
}
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