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Development and internal validation of a risk prediction model for dementia in a rural older population in China
Keke Liu, Tingting Hou, Yuqi Li, Na Tian, Yifei Ren, Cuicui Liu, Yi Dong, Lin Song et al.. Alzheimer s & Dementia, 2025-02-01
Topic: Risk, prevention and care in population studies
During the 4-year follow-up, 134 individuals were diagnosed with dementia. We identified age, education, self-rated AD8 score, marital status, and stroke for the prediction model, with the C-index being 0.79 (95% confidence interval = 0.75-0.83) and the corrected C-index for internal validation being 0.79. Calibration plots showed good performance in predicting up to 4-year dementia risk and DCA indicated good clinical usefulness. The 4-year dementia risk can be accurately predicted using five easily available predictors in a rural Chinese older population. HIGHLIGHTS: We developed and internally validated a practical tool for dementia risk prediction among a rural older population in China. The prediction tool showed good discrimination and excellent calibration for predicting up to 4-year risk of dementia. The prediction tool can be used to identify individuals at a high risk for dementia for early preventive interventions.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Liu, K., Hou, T., Li, Y., Tian, N., Ren, Y., Liu, C., et al. (2025). Development and internal validation of a risk prediction model for dementia in a rural older population in China. Alzheimer s & Dementia. https://doi.org/10.1002/alz.14617
Vancouver
Liu K, Hou T, Li Y, Tian N, Ren Y, Liu C, et al. Development and internal validation of a risk prediction model for dementia in a rural older population in China. Alzheimer s & Dementia. 2025. doi:10.1002/alz.14617. PMID: 39988567.
BibTeX
@article{liu2025-39988567,
author = {Liu, Keke and Hou, Tingting and Li, Yuqi and Tian, Na and Ren, Yifei and Liu, Cuicui and Dong, Yi and Song, Lin and others},
title = {{Development and internal validation of a risk prediction model for dementia in a rural older population in China}},
journal = {Alzheimer s \& Dementia},
year = {2025},
doi = {10.1002/alz.14617},
pmid = {39988567},
url = {https://doi.org/10.1002/alz.14617}
}
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Key findings
- During the 4-year follow-up, 134 individuals were diagnosed with dementia.
- We identified age, education, self-rated AD8 score, marital status, and stroke for the prediction model, with the C-index being 0.79 (95% confidence interval = 0.75-0.83) and the corrected C-index for internal validation being 0.79.
- Calibration plots showed good performance in predicting up to 4-year dementia risk and DCA indicated good clinical usefulness.
- The 4-year dementia risk can be accurately predicted using five easily available predictors in a rural Chinese older population.
- HIGHLIGHTS: We developed and internally validated a practical tool for dementia risk prediction among a rural older population in China.
Why it matters
A risk model using age, education, self-rated AD8 score, marital status, and stroke predicted 4-year dementia risk with good accuracy in a rural Chinese older population. This tool was only internally validated, so it is not yet confirmed for use in other populations or for preventing dementia.
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Study details
- Study designcohort study
- Participants2,220
- Evidence strengthModerate
How this study scored 58/100
Published in a peer-reviewed journal, and it is a cohort study following people over time. Scored zero for effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Alzheimer s & Dementia) |
| Journal's citation record | 2 / 4 | Alzheimer s & Dementia: journal h-index 228 (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 | 3 / 4 | 2,220 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 | 2 / 7 | Cited 8 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 2.7 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 3 / 6 | Cited 5.1× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 3 other studies in this library |
| Still being cited | 1 / 4 | Cited 8 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Chengxuan Qiu: h-index 66 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Karolinska Institutet: institution h-index 1,477 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 39988567) |
| Free to read | 2 / 2 | Free to read |
| Total | 58 / 100 | — |
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