Evidence map›Paper›PMID 42594414›Full record

ArticleThe journal of prevention of Alzheimer's disease2026

The missing improvers: Tau pathology, neuroplasticity, and the case for tau-informed patient selection before amyloid immunotherapy.

Eric Dinnerstein

Abstract read
In one paragraph

Article in The journal of prevention of Alzheimer's disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Eric DinnersteinNeurology department, The University of Texas Tyler School of Medicine, Tyler, TX, USA. Electronic address: Eric.Dinnerstein@uttyler.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amyloid immunotherapy with lecanemab and donanemab has been approved on the basis of statistically significant slowing of cognitive and functional decline in early Alzheimer's disease (1,2). Yet clinicians treating individual patients face the everyday challenge of estimating whether a given patient is declining at the rate that would be expected for them, and whether their trajectory reflects a response to treatment. I argue that this difficulty arises in large part because the field cannot yet routinely stratify patients by tau pathology before treatment, even though tau burden is among the strongest available predictors of both the rate of progression and the magnitude of response to amyloid-targeting therapy. Post-hoc and open-label analyses of the Clarity AD and TRAILBLAZER-ALZ 2 programmes suggest that patients with absent, low, or medium tau burden may constitute a biologically distinct group in whom amyloid clearance is most likely to permit clinical stabilization or measurable functional gain. These observations remain hypotheses, generated largely from subgroup, open-label, and biomarker data rather than from prospective trials designed to test them I propose that tau status should be given strong consideration in patient selection, that tau-guided selection should be evaluated prospectively, and that the access, reimbursement, and standardization barriers to tau positron emission tomography (PET) - together with the promise of scalable plasma tau biomarkers - be addressed deliberately as the field moves toward tau-informed treatment. One tau PET tracer is currently approved by the US Food and Drug Administration, and a regulatory decision on a second is anticipated in 2026.

Indexed as

Alzheimer's diseaseAmyloid immunotherapyCognitive trajectoryDisease-modifying therapyDonanemabLecanemabPatient selectionPlasma biomarkersTau PET

Identifiers

PMID42594414
PMCPMC13495380

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.