Evidence map›Paper›PMID 40034500›Full record

ArticleJournal of Alzheimer's disease reports

Sentiment analysis of social media responses to the approval of lecanemab for the treatment of Alzheimer's disease in Japan.

Kenichiro Sato, Yoshiki Niimi, Ryoko Ihara, Atsushi Iwata, Kiyotaka Nemoto, Tetsuaki Arai, Shinji Higashi, Ataru Igarashi, Kensaku Kasuga, Takeshi Iwatsubo

Abstract read
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In one paragraph

Article in Journal of Alzheimer's disease reports. 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

10 authors.

Kenichiro SatoDepartment of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0003-4351-9526
Yoshiki NiimiUnit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, Tokyo, Japan.
Ryoko IharaDepartment of Neurology, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan.
Atsushi IwataDepartment of Neurology, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan.
Kiyotaka NemotoDepartment of Psychiatry, Institute of Medicine, University of Tsukuba, Ibaraki, Japan.
Tetsuaki AraiDepartment of Psychiatry, Institute of Medicine, University of Tsukuba, Ibaraki, Japan.
Shinji HigashiDepartment of Psychiatry, Ibaraki Medical Center, Tokyo Medical University, Ibaraki, Japan.
Ataru IgarashiDepartment of Public Health, Yokohama City University School of Medicine, Kanagawa, Japan.
Kensaku KasugaDepartment of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan.
Takeshi IwatsuboDepartment of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lecanemab, an anti-amyloid therapy for early Alzheimer's disease, received approval by the FDA and Japan in 2023. Public response on social media was scrutinized, aiming to obtain insights into communication and treatment development. For 478 posts from X and Facebook, their sentiments on efficacy, safety, societal significance, and overall lecanemab impression were assessed by GPT-4 and the authors. Results indicated impressions were 43.7% negative, 26.6% neutral, and 29.7% positive. Social significance concerns dominated negative views. Specific attitude patterns were observed in the overall impression to lecanemab's approval. These insights highlight the need for targeted communication and research on anti-amyloid therapies.

Indexed as

Alzheimer's diseaselarge language modellecanemabsentiment analysissocial media

Identifiers

PMID40034500
PMCPMC11864249

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.