A head‐to‐head comparison between plasma p‐tau217 and tau‐PET for predicting future cognitive decline among cognitively unimpaired individuals
Bibliographic record
Abstract
Abstract Background An accurate prediction of Alzheimer’s disease (AD) progression is important for patient management and optimization of participant selection for trials. Here, we compared and combined plasma p‐tau217 and tau‐PET measures for predicting longitudinal cognitive decline and clinical progression in cognitively unimpaired participants. Method We included 982 participants from six independent cohorts (AiBL, BioFINDER‐1, BioFINDER‐2, TRIAD, PREVENT‐AD and WRAP; Table 1) with available plasma p‐tau217 and tau‐PET measures (measured less than one‐year apart), being either amyloid‐positive or amyloid‐negative. Biomarker and cognitive data were z‐scored by cohort using cognitively unimpaired CSF/PET amyloid‐negative participants as reference for a unified analysis. We performed linear mixed models (for predicting cognitive decline on the mPACC and MMSE) and Cox‐proportional hazards models (to assess progression to MCI or dementia), testing among both amyloid‐negative and amyloid‐positive individuals. We entered baseline plasma p‐tau217, and tau‐PET uptake in the medial temporal lobe (MTL) or in the temporal neocortex individually, and also performed combined plasma/PET models. Age, sex, years of education and cohort were used as covariates. Result All individual tau biomarkers significantly predicted cognitive decline for both mPACC (R2p‐tau217=0.27, R2MTL‐tau=0.31, R2neotemporal‐tau=0.28, Figure 1) and MMSE (R2p‐tau217=0.12, R2MTL‐tau=0.16, R2neotemporal‐tau=0.19, Figure 2). The best model for predicting mPACC change included plasma p‐tau217 and MTL tau‐uptake (R2=0.32, pcomparison<0.001), while for MMSE change included plasma p‐tau217 and tau‐uptake in the temporal neocortex (R2=0.20, pcomparison≤0.007). Progression to MCI or dementia was also best predicted when including both plasma p‐tau217 (HR[95%CI]=1.29[1.14,1.47], p<0.001) and MTL tau‐uptake (HR[95%CI]=1.39[1.25,1.54], p<0.001, c‐index=0.83). Analyses by individual cohorts showed similar trends. Conclusion Our data suggest that plasma p‐tau217 is a suitable screening method for clinical trials in CU populations given its logistic advantages. In scenarios where a more refined prediction of cognitive decline is mandated, Tau‐PET (preferably in a combined algorithm with plasma p‐tau217) would be the methodology of choice.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".