ArticleFrontiers in neuroinformatics2026
Safety of lecanemab in real-world patients with Alzheimer's disease: a prospective, observational case series supported by FAERS signal analysis.
Article in Frontiers in neuroinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Lecanemab, a humanized immunoglobulin monoclonal antibody, has been approved for the treatment of Alzheimer's disease (AD). Although clinical trials have demonstrated its favorable safety profile, real-world studies are crucial for identifying rare adverse events (AEs) and evaluating post-marketing safety. This study aimed to evaluate the safety of lecanemab by combining a clinical prospective, observational case cohort with data from the FAERS database, thereby providing a robust basis for the identification of potential safety signals. Methods: A prospective and observational study was conducted on patients with mild-to-moderate AD receiving lecanemab treatment at a tertiary medical center in China from July 2024 to February 2026. Extracted data included demographic characteristics, time to onset of AEs, and clinical symptoms. Exposure-adjusted incidence rates were calculated per 100 patient-years (PYs). Disproportionality analysis was performed using the US Food and Drug Administration Adverse Event Reporting System (FAERS), and safety signals for AEs observed in the cohort were evaluated utilizing reporting odds ratios (RORs) and proportional reporting ratios (PRRs). Additionally, data from these two real-world sources were compared and cross-validated. Results: The single-center prospective study enrolled a total of 91 patients. The median duration of lecanemab treatment was 185 days. Thirteen AEs were recorded (56.48/100 PYs), with the most frequent being amyloid-related imaging abnormalities-hemosiderin deposition (ARIA-H; defined as microhemorrhages and hemosiderin deposition) (12.39/100 PYs) and infusion-related reactions (IRRs) (8.85/100 PYs). In the FAERS database, the most frequently reported preferred terms (PTs) included headache, amyloid-related imaging abnormalities-edema/effusion (ARIA-E), ARIA-H, and IRRs. The majority of AEs occurred within the first 1-2 months after initiating lecanemab treatment ( Conclusion: In this single-center prospective observational study, lecanemab demonstrated a generally favorable safety profile. Patients with AD aged 65 to 85 years represent a high-risk demographic for AEs. Particular clinical vigilance is required regarding the occurrence of AEs within the first two months of lecanemab initiation. Notably, ARIA (including both ARIA-E and ARIA-H) can occur at any phase during the treatment course.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.