Neurofilament light (NfL) chain levels predict clinical decline in Alzheimer's disease: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Regulatory approval of new investigational Alzheimer's disease (AD) therapies could be accelerated if reasonably likely surrogate endpoints could be used. Neurofilament light chain (NfL) has potential utility as a prognostic biomarker of neurodegeneration in AD. Objective: To synthesize available evidence on the relationship between baseline NfL levels and longitudinal clinical decline. Methods: A systematic literature review identified 19 eligible studies, contributing 37 longitudinal statistical models evaluating the association between baseline NfL (plasma or cerebrospinal fluid [CSF]) with subsequent clinical decline based on validated clinical scales including Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-Cognitive Subscale, and Clinical Dementia Rating. Results were pooled via meta-analysis, using partial correlation coefficients (PCC), separately for patient sub-groups (mild cognitive impairment, AD or combined). Results: Across the AD continuum, higher baseline NfL levels were consistently associated with greater cognitive and global clinical decline in most analyses. This pattern was consistent for both plasma (pooled PCC = -0.17 [95% CI = -0.22, -0.12] for MMSE, any AD population) and CSF NfL (pooled PCC = -0.14 [95% CI = -0.24, -0.04] for MMSE, any AD population). The strength of association across multiple clinical endpoints and populations, measured by absolute value of pooled PCC, ranged from 0.13 to 0.25. Conclusions: The results support the utility of NfL as a predictive biomarker for progression of clinical decline in AD patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.011 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".