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Predictive Value of 18F-Florbetapir and 18F-FDG PET for Conversion from Mild Cognitive Impairment to Alzheimer Dementia
Blazhenets G, Ma Y, Sörensen A, Schiller F, Rücker G, Eidelberg D, Frings L, Meyer PT et al.. Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2019-10-18
Topic: Amyloid, tau and blood-test diagnosis
On the basis of the independent validation dataset, the 18 F-FDG PET model yielded a significantly higher predictive value than the amyloid PET model. However, both were inferior to the nonimaging model and were significantly improved by the addition of nonimaging variables. The best prediction accuracy was reached by combining 18 F-FDG PET, amyloid PET, and nonimaging variables. The combined model yielded 5-y free-of-conversion rates of 100%, 64%, and 24% for the low-, medium- and high-risk groups, respectively. 18 F-FDG PET, amyloid PET, and nonimaging variables represent complementary predictors of conversion from MCI to AD. Especially in combination, they enable an accurate stratification of patients according to their conversion risks, which is of great interest for patient care and clinical trials.
Key findings
- On the basis of the independent validation dataset, the 18 F-FDG PET model yielded a significantly higher predictive value than the amyloid PET model.
- However, both were inferior to the nonimaging model and were significantly improved by the addition of nonimaging variables.
- The best prediction accuracy was reached by combining 18 F-FDG PET, amyloid PET, and nonimaging variables.
- The combined model yielded 5-y free-of-conversion rates of 100%, 64%, and 24% for the low-, medium- and high-risk groups, respectively. 18 F-FDG PET, amyloid PET, and nonimaging variables represent complementary predictors of conversion from MCI to AD.
- Especially in combination, they enable an accurate stratification of patients according to their conversion risks, which is of great interest for patient care and clinical trials.
Why it matters
For predicting conversion from mild cognitive impairment to Alzheimer dementia, an 18F-FDG PET model performed significantly better than an amyloid PET model, but both were inferior to a model using nonimaging variables alone and both improved when nonimaging variables were added. The best accuracy came from combining 18F-FDG PET, amyloid PET, and nonimaging variables, which allowed stratification of patients into low-, medium-, and high-risk groups with 5-year free-of-conversion rates of 100%, 64%, and 24%.
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Study details
- Participants159
- Evidence strengthLow
How this study scored 48/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Journal of nuclear medicine : official publication, Society of Nuclear Medicine) |
| Journal's citation record | 2 / 4 | Journal of Nuclear Medicine: journal h-index 230 (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 | 2 / 5 | 2020 — within 10 year(s) of the newest study here |
| Sample size | 2 / 4 | 159 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 | 4 / 7 | Cited 58 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 7.2 citations a year over 8 year(s) since 2020 |
| Impact for its field and year | 3 / 6 | Cited 3.7× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 4 other studies in this library |
| Still being cited | 2 / 4 | Cited 26 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Philipp Tobias Meyer: h-index 52 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | University of Freiburg: institution h-index 1,068 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 4 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 31628215) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 48 / 100 | — |
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Read the original
Full text: free to read — PubMed Central lists this copy as free to read: the link above (checked 10 Oct 2026).
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's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Blazhenets, G., Ma, Y., Sörensen, A., Schiller, F., Rücker, G., Eidelberg, D., et al. (2020). Predictive Value of 18F-Florbetapir and 18F-FDG PET for Conversion from Mild Cognitive Impairment to Alzheimer Dementia. Journal of nuclear medicine : official publication, Society of Nuclear Medicine. https://doi.org/10.2967/jnumed.119.230797
Vancouver
Blazhenets G, Ma Y, Sörensen A, Schiller F, Rücker G, Eidelberg D, et al. Predictive Value of 18F-Florbetapir and 18F-FDG PET for Conversion from Mild Cognitive Impairment to Alzheimer Dementia. Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 2020. doi:10.2967/jnumed.119.230797. PMID: 31628215.
BibTeX
@article{blazhenets2020-31628215,
author = {Blazhenets, G. and Ma, Y. and Sörensen, A. and Schiller, F. and Rücker, G. and Eidelberg, D. and Frings, L. and Meyer, P. T. and others},
title = {{Predictive Value of 18F-Florbetapir and 18F-FDG PET for Conversion from Mild Cognitive Impairment to Alzheimer Dementia}},
journal = {Journal of nuclear medicine : official publication, Society of Nuclear Medicine},
year = {2020},
doi = {10.2967/jnumed.119.230797},
pmid = {31628215},
url = {https://doi.org/10.2967/jnumed.119.230797}
}
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