The effect of the tumour necrosis factor-alpha-inhibitor etanercept on microglial activation patients with mild cognitive impairment—a PET study
Bibliographic record
Abstract
Aim: Microglial activation is increasingly recognised as a factor in the progression of Alzheimer’s disease (AD) and may be modified by systemic inflammatory signals including serum tumour necrosis factor (TNF)-α. The aim was to investigate whether blockade of peripheral TNF-α with peripheral inhibitors such as etanercept reduces microglial activation in prodromal AD. Methods: A one-year, multi-centre, phase 2, double-blind randomised placebo-controlled trial (RPCT) was performed, to assess the effect of weekly 50 mg s.c. etanercept in amyloid positive mild cognitive impaired participants on the change in microglial activation as measured by [11C](R)-PK11195 positron emission tomography (PET). Secondary objectives were to ascertain the change in cortical amyloid load on PET and the change in the Montreal Cognitive Assessment (MoCA). Results: Forty-four subjects consented to the study. Twenty-eight subjects failed screening including six subjects who were amyloid negative on visual read of the AmyvidTM PET scans. Thirteen of sixteen subjects with mild cognitive impairment (MCI) due to AD completed the baseline [11C](R)-PK11195 PET scan and were randomised to either placebo or etanercept. Three patients who consented were not able to complete screening due to early termination of the study following delays in study commencement. [11C](R)-PK11195 binding potential (BP) at baseline showed an almost global increase in MCI patients as compared to age-matched controls. Compliance to medication was high over the twelve-month trial period with etanercept being well tolerated. The study did not achieve statistical power to show a significant effect of etanercept over 52 weeks in the limited number of patients with MCI on microglial activation as measured by [11C](R)-PK11195 PET. Overall uptake of florbetapir in the follow up (FU) scans remained stable. The study was not powered to show statistical differences in psychometric ratings between groups. Conclusions: This study did not show evidence that treatment with etanercept over one year would modulate microglial activation in amyloid positive MCI patients (EudraCT identifier: 2015-002145-63, https://www.clinicaltrialsregister.eu; International Standard Randomised Controlled Trial Number identifier: ISRCTN12472821, https://www.isrctn.com).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".