Evidence map›Paper›PMID 39865820›Full record

ReviewReviews on recent clinical trials2025

New Research on Biomarkers in Alzheimer's Continuum.

Immacolata Vecchio, Carmela Colica

Abstract readReview
PubMed Publisher
In one paragraph

Review in Reviews on recent clinical trials, 2025. 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

2 authors.

Immacolata VecchioCNR-IRIB, Secondary Site, Azienda Ospedaliero-Universitaria "Renato Dulbecco" Catanzaro, Italy.ORCID 0000-0001-7188-9861
Carmela ColicaCNR-IRIB, Secondary Site, Azienda Ospedaliero-Universitaria "Renato Dulbecco" Catanzaro, Italy.ORCID 0000-0001-6424-1223

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is a multifactorial pathology, responsible for neurodegenerative disorders which in more than 60% of patients evolve into dementia. Comprehension of the molecular mechanisms underlying the pathology and the development of reliable diagnostic methods have made new and more effective therapies possible. In recent years, in addition to the classic anticholinesterases (AChEs), which can control the clinical symptoms of the disease, compounds able to reduce deposits of amyloid-946; (A946;) and/or tau (964;) protein aggregates, which are disease- modifying therapeutics (DMTs), have been studied. The results have shown that symptomatic therapy works best when administered in the disease's mild to moderate clinical phase. On the other hand, treatment with DMTs has been found to be more effective in the preclinical stage of AD, when A946; and τ protein neurofibrillary tangles have not yet been compromised and patients still have a normal quality of life. This innovative approach requires the identification of specific biomarkers predictive of the disease, detectable many years before clinical signs are evident. Biomarkers allow early diagnosis, give indications of the possible development of dementia in the future, and make it possible to study the evolution of the disease. New scenarios, involving different pathways and approaches, could emerge and provide effective therapies to treat the very early stages of the disease and hamper its progression. The specific biomarkers studied so far have been reported here.

Indexed as

Alzheimer DiseaseBiomarkersHumanstau ProteinsBiomarkerstau ProteinsAlzheimer’s continuumamyloid-946;anticholinesterasesdisease-modifying therapeutics.multifactorial pathologyτ protein

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.