Home › Research › Prevention and risk
Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review
Tang EY, Harrison SL, Errington L, Gordon MF, Visser PJ, Novak G, Dufouil C, Brayne C et al.. PloS one, 2015-09-03
Topic: Risk, prevention and care in population studies
Background Accurate identification of individuals at high risk of dementia influences clinical care, inclusion criteria for clinical trials and development of preventative strategies. Numerous models have been developed for predicting dementia. To evaluate these models we undertook a systematic review in 2010 and updated this in 2014 due to the increase in research published in this area. Here we include a critique of the variables selected for inclusion and an assessment of model prognostic performance. Methods Our previous systematic review was updated with a search from January 2009 to March 2014 in electronic databases (MEDLINE, Embase, Scopus, Web of Science). Articles examining risk of dementia in non-demented individuals and including measures of sensitivity, specificity or the area under the curve (AUC) or c-statistic were included. Findings In total, 1,234 articles were identified from the search; 21 articles met inclusion criteria. New developments in dementia risk prediction include the testing of non-APOE genes, use of non-traditional dementia risk factors, incorporation of diet, physical function and ethnicity, and model development in specific subgroups of the population including individuals with diabetes and those with different educational levels. Four models have been externally validated. Three studies considered time or cost implications of computing the model. Interpretation There is no one model that is recommended for dementia risk prediction in population-based settings. Further, it is unlikely that one model will fit all. Consideration of the optimal features of new models should focus on methodology (setting/sample, model development and testing in a replication cohort) and the acceptability and cost of attaining the risk variables included in the prediction score. Further work is required to validate existing models or develop new ones in different populations as well as determine the ethical implications of dementia risk prediction, before applying the particular models in population or clinical settings.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Tang, E. Y., Harrison, S. L., Errington, L., Gordon, M. F., Visser, P. J., Novak, G., et al. (2015). Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review. PloS one. https://doi.org/10.1371/journal.pone.0136181
Vancouver
Tang EY, Harrison SL, Errington L, Gordon MF, Visser PJ, Novak G, et al. Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review. PloS one. 2015. doi:10.1371/journal.pone.0136181. PMID: 26334524.
BibTeX
@article{tang2015-26334524,
author = {Tang, E. Y. and Harrison, S. L. and Errington, L. and Gordon, M. F. and Visser, P. J. and Novak, G. and Dufouil, C. and Brayne, C. and others},
title = {{Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review}},
journal = {PloS one},
year = {2015},
doi = {10.1371/journal.pone.0136181},
pmid = {26334524},
url = {https://doi.org/10.1371/journal.pone.0136181}
}
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
- Three studies considered time or cost implications of computing the model.
- Interpretation There is no one model that is recommended for dementia risk prediction in population-based settings.
- Further, it is unlikely that one model will fit all.
- Consideration of the optimal features of new models should focus on methodology (setting/sample, model development and testing in a replication cohort) and the acceptability and cost of attaining the risk variables included in the prediction score.
- Further work is required to validate existing models or develop new ones in different populations as well as determine the ethical implications of dementia risk prediction, before applying the particular models in population or clinical settings.
Why it matters
This review of dementia risk prediction models found no single model that can be recommended for predicting dementia risk in the general population. It is about tools for estimating risk, not about treating, curing or preventing Alzheimer's disease.
New to this subject? Start with our plain-English guide: Prevention →
Study details
- Study designsystematic review
- Evidence strengthHigh
How this study scored 66/100
Published in a peer-reviewed journal, and it is a systematic review of all the studies on the question. Scored zero for sample size, effect reported and studied in people because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (PloS one) |
| Journal's citation record | 4 / 4 | PLoS ONE: journal h-index 594 (OpenAlex, 2026-10-29) |
| Study design | 12 / 12 | A systematic review of all the studies on the question |
| Strength of evidence | 5 / 5 | Rated “high” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2015 — within 20 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 | A review of other studies — randomisation is not credited here |
| Times cited | 5 / 7 | Cited 174 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 13.4 citations a year over 13 year(s) since 2015 |
| Impact for its field and year | 2 / 6 | Cited 2.0× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 3 / 6 | Cited by 19 other studies in this library |
| Still being cited | 2 / 4 | Cited 34 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Blossom C. M. Stephan: h-index 62 (OpenAlex, whole career) |
| Institution's track record | 3 / 3 | National Institutes of Health: institution h-index 2,723 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 9 institution(s) in 4 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 26334524) |
| Free to read | 2 / 2 | Free to read |
| Total | 66 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here.
Later studies that cite this one
19 studies in the alzhub library list this one in their references. Showing the 8 highest-scoring.
Related studies in Prevention and risk
Also tagged “prevalence”
1,224 studies in the library carry the topic tag “prevalence”; these are this study's neighbours in a fixed, alphabetical-by-hash tour of them, not the closest in content. All 1,224 tagged studies.