The prevalence of tau‐PET positivity in aging and dementia
Bibliographic record
Abstract
Abstract Background Tau‐PET imaging allows in‐vivo detection of neurofibrillary tangles. One tau‐PET tracer (i.e., [18F]flortaucipir) has received FDA‐approval for clinical use, and multiple other tau‐PET tracers have been implemented into clinical trials for participant selection and/or as a primary or secondary outcome measure. To optimize future use of tau‐PET, it is essential to understand how demographic, clinical and genetic factors affect tau‐PET‐positivity rates. Method This large‐scale multi‐center study includes 9713 participants from 35 cohorts worldwide who underwent tau‐PET with [18F]flortaucipir (n = 6420), [18F]RO948 (n = 1999), [18F]MK6240 (n = 878) or [18F]PI2620 (n = 416) (Table‐1). We analyzed individual‐level tau‐PET SUVR data using a cerebellar reference region that were processed either centrally (n = 3855) or by each cohort (n = 5858). We computed cohort‐specific SUVR thresholds based on the mean + 2 standard deviations in a temporal meta‐region of amyloid‐negative cognitively normal (CN) individuals aged >50. Logistic generalized estimating equations were used to estimate tau‐PET‐positivity probabilities, using an exchangeable correlation structure to account for within‐cohort correlations. Analyses were performed with (interactions between) age, amyloid‐status, and APOE‐e4 carriership as independent variables, stratified for syndrome diagnosis. Result The study included 5962 CN participants (7.5% tau‐PET‐positive), 1683 participants with mild cognitive impairment (MCI, 33.8% tau‐PET‐positive) and 2068 participants with a clinical diagnosis of dementia (62.1% tau‐PET‐positive) (Figure‐1). From age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 1.2% [95% CI: 0.9%‐1.5%] to 3.7% [2.3%‐5.1%] among CN amyloid‐negative participants; and from 16.4% [10.8%‐22.1%] to 20.5% [18.8%‐22.2%] among CN amyloid‐positive participants. Among amyloid‐negative participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 3.5% [1.6%‐5.3%] to 11.8% [7.1%‐16.5%] and from 12.6% [4.5%‐20.7%] to 15.9% [6.7%‐25.1%] respectively. In contrast, among amyloid‐positive participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity decreased from 66.5% [57.0%‐76.0%] to 48.3% [42.9%‐53.8%] and from 92.3% [88.7%‐95.9%] to 73.4% [67.5%‐79.3%] respectively. APOE‐e4 status primarily modulated the association of age with tau‐PET‐positivity estimates among CN and MCI amyloid‐positive participants (Figure‐2). Conclusion This large‐scale multi‐cohort study provides robust prevalence estimates of tau‐PET‐positivity, which can aid the interpretation of tau‐PET in the clinic and inform clinical trial designs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".