Evidence map›Paper›PMID 38381175›Full record

ArticleJournal of neurology2024

Real-word application of the AT(N) classification and disease-modifying treatment eligibility in a hospital-based cohort.

Elisa Canu, Giulia Rugarli, Federico Coraglia, Silvia Basaia, Giordano Cecchetti, Sonia Francesca Calloni, Paolo Quintiliano Vezzulli, Edoardo Gioele Spinelli, Roberto Santangelo, Francesca Caso and 4 more

Abstract read
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In one paragraph

Article in Journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Patient eligibility for amyloid-targeting immunotherapies in Alzheimer's disease.The journal of prevention of Alzheimer's disease · 2025
    Article
  5. Review
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

14 authors.

Elisa CanuNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0000-0001-5804-3378
Giulia RugarliNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0009-0004-2063-7735
Federico CoragliaNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0009-0008-7717-6406
Silvia BasaiaNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0000-0002-0722-6243
Giordano CecchettiNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0000-0002-6544-410X
Sonia Francesca CalloniNeuroradiology Unit and High Field MRI Center, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Paolo Quintiliano VezzulliNeuroradiology Unit and High Field MRI Center, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0000-0002-3568-4946
Edoardo Gioele SpinelliNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0000-0003-1492-7221
Roberto SantangeloNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0000-0002-8760-2703
Francesca CasoNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0000-0002-3072-1218
Andrea FaliniVita-Salute San Raffaele University, Milan, Italy.ORCID http://orcid.org/0000-0002-1461-8755
Giuseppe MagnaniNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0000-0001-8436-2903
Massimo FilippiNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID http://orcid.org/0000-0002-5485-0479
Federica AgostaNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy. agosta.federica@hsr.it.ORCID http://orcid.org/0000-0003-3121-4979

Funding

Ministero della Salute Next Generation EU [DM 1557 11.10.2022]
6 · The paper itself

Abstract

BACKGROUND AND

objectivesThe AT(N) classification system stratifies patients based on biomarker profiles, including amyloid-beta deposition (A), tau pathology (T), and neurodegeneration (N). This study aims to apply the AT(N) classification to a hospital-based cohort of patients with cognitive decline and/or dementia, within and outside the Alzheimer's disease (AD) continuum, to enhance our understanding of the multidimensional aspects of AD and related disorders. Furthermore, we wish to investigate how many cases from our cohort would be eligible for the available disease modifying treatments, such as aducanemab and lecanemab.

methodsWe conducted a retrospective evaluation of 429 patients referred to the Memory Center of IRCCS San Raffaele Hospital in Milan. Patients underwent clinical/neuropsychological assessments, lumbar puncture, structural brain imaging, and positron emission tomography (FDG-PET). Patients were stratified according to AT(N) classification, group comparisons were performed and the number of eligible cases for anti-β amyloid monoclonal antibodies was calculated.

resultsSociodemographic and clinical features were similar across groups. The most represented group was A + T + N + accounting for 38% of cases, followed by A + T - N + (21%) and A - T - N + (20%). Although the clinical presentation was similar, the A + T + N + group showed more severe cognitive impairment in memory, language, attention, executive, and visuospatial functions compared to other AT(N) groups. Notably, T + patients demonstrated greater memory complaints compared to T -  cases. FDG-PET outperformed MRI and CT in distinguishing A + from A -  patients. Although 61% of the observed cases were A + , only 17% of them were eligible for amyloid-targeting treatments. DISCUSSION: The AT(N) classification is applicable in a real-world clinical setting. The classification system provided insights into clinical management and treatment strategies. Low cognitive performance and specific regional FDG-PET hypometabolism at diagnosis are highly suggestive for A + T + or A - T + profiles. This work provides also a realistic picture of the proportion of AD patients eligible for disease modifying treatments emphasizing the need for early detection.

Indexed as

Amyloid beta-PeptidesCognitive DysfunctionAgedAged, 80 and overAlzheimer DiseaseBiomarkersBrainCohort StudiesDementiaFemaleHumansMaleMiddle AgedNeuropsychological TestsPositron-Emission TomographyRetrospective StudiesAmyloid beta-PeptidesBiomarkerstau ProteinsAlzheimer’s diseaseATN systemBiomarkersCognitive declineDisease modifying treatmentsEligibility

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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.