Evidence map›Paper›PMID 37389302›Full record

ReviewBrain communications2023

Key questions for the evaluation of anti-amyloid immunotherapies for Alzheimer's disease.

Kathy Y Liu, Nicolas Villain, Scott Ayton, Sarah F Ackley, Vincent Planche, Robert Howard, Madhav Thambisetty

Open access · goldAbstract readReview
In one paragraph

Review in Brain communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
8.8field-weighted citation impact, top 1% of its field
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

23 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
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  7. Repeated plasma p-tau217 measurements to monitor clinical progression heterogeneity.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
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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

7 authors at 5 institutions in 4 countries.

Kathy Y LiuDivision of Psychiatry, University College London, London W1T 7NF, UK.ORCID https://orcid.org/0000-0002-7482-2758
Nicolas VillainAP-HP.Sorbonne Université, Institut de la Mémoire et de la Maladie d'Alzheimer, Département de Neurologie, Hôpital Pitié-Salpêtrière, 75013 Paris, France.ORCID https://orcid.org/0000-0002-7429-4289
Scott AytonMelbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC 3052, Australia.ORCID https://orcid.org/0000-0002-3479-2427
Sarah F AckleyDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA.
Vincent PlancheUniv. Bordeaux, CNRS, UMR 5293, Institut des Maladies Neurodégénératives, F-33000 Bordeaux, France.ORCID https://orcid.org/0000-0003-3713-227X
Robert HowardDivision of Psychiatry, University College London, London W1T 7NF, UK.
Madhav ThambisettyClinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD 21224, USA.ORCID https://orcid.org/0000-0002-2200-2299
Centre National de la Recherche Scientifique · FRUniversity College London · GBNational Institute on Aging · USThe University of Melbourne · AUUniversity of California, San Francisco · US

Funding

Mathematical Models of Tau-PET Measures and Cognitive Decline in Alzheimer’s Disease Across the LifespanK99AG073454 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ACKLEY, SARAH · 2022 to 2024
$250k
Medical Research Council MR/S021418/1NIA NIH HHS K99 AG073454
6 · The paper itself

Abstract

The clinical benefit associated with anti-amyloid immunotherapies, a new class of drugs for the treatment of Alzheimer's disease, is predicated on their ability to modify disease course by lowering brain amyloid levels. At the time of writing, two amyloid-lowering antibodies, aducanumab and lecanemab, have obtained United States Food and Drug Administration accelerated approval, with further agents of this class in the Alzheimer's disease treatment pipeline. Based on limited published clinical trial data to date, regulators, payors and physicians will need to assess their efficacy, clinical effectiveness and safety, as well as cost and accessibility. We propose that attention to three important questions related to treatment efficacy, clinical effectiveness and safety should guide evidence-based consideration of this important class of drugs. These are: (1) Were trial statistical analyses appropriate and did they convincingly support claims of efficacy? (2) Do reported treatment effects outweigh safety concerns and are they generalizable to a representative clinical population of people with Alzheimer's disease? and (3) Do the data convincingly demonstrate disease course modification, suggesting that increasing clinical benefits beyond the duration of the trials are likely? We suggest specific approaches to interpreting trial results for these drugs and highlight important areas of uncertainty where additional data and a cautious interpretation of existing results is warranted. Safe, effective and accessible treatments for Alzheimer's disease are eagerly awaited by millions of patients and their caregivers worldwide. While amyloid-targeting immunotherapies may be promising disease-modifying Alzheimer's disease treatments, rigorous and unbiased assessment of clinical trial data is critical to regulatory decision-making and subsequently determining their provision and utility in routine clinical practice. Our recommendations provide a framework for evidence-based appraisal of these drugs by regulators, payors, physicians and patients.

Indexed as

Alzheimeramyloid immunotherapydementiadisease-modifyingMCI

Identifiers

PMID37389302
PMCPMC10306158
OpenAlexW4379958372

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.